From 0a1cea73c1448820a5ac4a69c60dd024e233c880 Mon Sep 17 00:00:00 2001 From: Danil Date: Thu, 6 Aug 2020 13:51:32 +0500 Subject: [PATCH 01/81] Add dot to yml extension (#469) --- mmcv/utils/config.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/utils/config.py b/mmcv/utils/config.py index a141881a9d..c7eaa6f18c 100644 --- a/mmcv/utils/config.py +++ b/mmcv/utils/config.py @@ -119,7 +119,7 @@ def _file2dict(filename, use_predefined_variables=True): filename = osp.abspath(osp.expanduser(filename)) check_file_exist(filename) fileExtname = osp.splitext(filename)[1] - if fileExtname not in ['.py', '.json', '.yaml', 'yml']: + if fileExtname not in ['.py', '.json', '.yaml', '.yml']: raise IOError('Only py/yml/yaml/json type are supported now!') with tempfile.TemporaryDirectory() as temp_config_dir: From 6b43ae3700aee7be07a1092887bed414e5e9c086 Mon Sep 17 00:00:00 2001 From: ChaseMonsterAway <58807745+ChaseMonsterAway@users.noreply.github.com> Date: Thu, 6 Aug 2020 16:51:58 +0800 Subject: [PATCH 02/81] Update cnn.md (#466) --- docs/cnn.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/cnn.md b/docs/cnn.md index 1c56b340f5..b3052d1196 100644 --- a/docs/cnn.md +++ b/docs/cnn.md @@ -1,6 +1,6 @@ ## CNN -We provide some building bricks for CNNs, includeing layer building, module bundles and weight initialization. +We provide some building bricks for CNNs, including layer building, module bundles and weight initialization. ### Layer building From edbbc0f2158ed140fadf91dd033133d60b03c437 Mon Sep 17 00:00:00 2001 From: Jintao Lin Date: Thu, 6 Aug 2020 22:07:31 +0800 Subject: [PATCH 03/81] fix bug for self.warmup_iters when warmup_by_epoch (#470) --- mmcv/runner/hooks/lr_updater.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/mmcv/runner/hooks/lr_updater.py b/mmcv/runner/hooks/lr_updater.py index 0f98bcb268..8cbb85b10c 100644 --- a/mmcv/runner/hooks/lr_updater.py +++ b/mmcv/runner/hooks/lr_updater.py @@ -110,11 +110,11 @@ def before_run(self, runner): group['initial_lr'] for group in runner.optimizer.param_groups ] - if self.warmup_by_epoch: + def before_train_epoch(self, runner): + if self.warmup_iters is None: epoch_len = len(runner.data_loader) self.warmup_iters = self.warmup_epochs * epoch_len - def before_train_epoch(self, runner): if not self.by_epoch: return From 9b36c1ab3edacb1e4b3b5f21603a6f0654c61780 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Sun, 9 Aug 2020 00:04:48 +0800 Subject: [PATCH 04/81] Fixed iter_base_runner logger (#474) --- mmcv/runner/iter_based_runner.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/mmcv/runner/iter_based_runner.py b/mmcv/runner/iter_based_runner.py index 3a3d22f2fc..f41a86a9d4 100644 --- a/mmcv/runner/iter_based_runner.py +++ b/mmcv/runner/iter_based_runner.py @@ -222,5 +222,6 @@ def register_training_hooks(self, self.register_checkpoint_hook(checkpoint_config) self.register_hook(IterTimerHook()) if log_config is not None: - log_config.setdefault('by_epoch', False) + for info in log_config['hooks']: + info.setdefault('by_epoch', False) self.register_logger_hooks(log_config) From 530ae2004656212b5a140e9ec466ae396f9781a7 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Sun, 9 Aug 2020 15:44:44 +0800 Subject: [PATCH 05/81] add pre-build packages for pytorch 1.6 (#475) --- README.md | 50 +++++++++++++++++++++++++++++++++----------------- 1 file changed, 33 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index c09ecb4663..d26a1d474d 100644 --- a/README.md +++ b/README.md @@ -54,23 +54,39 @@ Before installing mmcv-full, make sure that PyTorch has been successfully instal We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building. - - - - - - -
CUDA torch 1.5torch 1.4torch 1.3
10.2
install 
pip install mmcv-full==latest+torch1.5.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
10.1
install 
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
10.0
9.2
install 
 pip install mmcv-full==latest+torch1.5.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
cpu
install 
 pip install mmcv-full==latest+torch1.5.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
CUDA torch 1.6torch 1.5torch 1.4torch 1.3
10.2
install 
pip install mmcv-full==latest+torch1.6.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.5.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
10.1
install 
 pip install mmcv-full==latest+torch1.6.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.4.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.3.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
9.2
install 
 pip install mmcv-full==latest+torch1.6.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
 pip install mmcv-full==latest+torch1.5.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.4.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.3.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
cpu
install 
 pip install mmcv-full==latest+torch1.6.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
 pip install mmcv-full==latest+torch1.5.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.4.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
install 
pip install mmcv-full==latest+torch1.3.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
Another way is to compile locally by running From 56e71a718b6115bf3fb70b191490b54e72c6fea8 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Sun, 9 Aug 2020 17:29:02 +0800 Subject: [PATCH 06/81] Add Depthwise Seperable ConvModule (#477) --- mmcv/cnn/__init__.py | 12 +-- mmcv/cnn/bricks/__init__.py | 3 +- .../bricks/depthwise_separable_conv_module.py | 89 ++++++++++++++++++ .../test_depthwise_seperable_conv_module.py | 90 +++++++++++++++++++ 4 files changed, 187 insertions(+), 7 deletions(-) create mode 100644 mmcv/cnn/bricks/depthwise_separable_conv_module.py create mode 100644 tests/test_cnn/test_depthwise_seperable_conv_module.py diff --git a/mmcv/cnn/__init__.py b/mmcv/cnn/__init__.py index 77a7878e32..e44b0226f7 100644 --- a/mmcv/cnn/__init__.py +++ b/mmcv/cnn/__init__.py @@ -3,11 +3,11 @@ from .bricks import (ACTIVATION_LAYERS, CONV_LAYERS, NORM_LAYERS, PADDING_LAYERS, PLUGIN_LAYERS, UPSAMPLE_LAYERS, ContextBlock, ConvAWS2d, ConvModule, ConvWS2d, - GeneralizedAttention, HSigmoid, HSwish, NonLocal1d, - NonLocal2d, NonLocal3d, Scale, build_activation_layer, - build_conv_layer, build_norm_layer, build_padding_layer, - build_plugin_layer, build_upsample_layer, conv_ws_2d, - is_norm) + DepthwiseSeparableConvModule, GeneralizedAttention, + HSigmoid, HSwish, NonLocal1d, NonLocal2d, NonLocal3d, + Scale, build_activation_layer, build_conv_layer, + build_norm_layer, build_padding_layer, build_plugin_layer, + build_upsample_layer, conv_ws_2d, is_norm) from .resnet import ResNet, make_res_layer from .utils import (bias_init_with_prob, caffe2_xavier_init, constant_init, fuse_conv_bn, get_model_complexity_info, kaiming_init, @@ -24,5 +24,5 @@ 'HSigmoid', 'HSwish', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'get_model_complexity_info', 'conv_ws_2d', - 'ConvAWS2d', 'ConvWS2d', 'fuse_conv_bn' + 'ConvAWS2d', 'ConvWS2d', 'fuse_conv_bn', 'DepthwiseSeparableConvModule' ] diff --git a/mmcv/cnn/bricks/__init__.py b/mmcv/cnn/bricks/__init__.py index 841102cbed..6cffa166cd 100644 --- a/mmcv/cnn/bricks/__init__.py +++ b/mmcv/cnn/bricks/__init__.py @@ -3,6 +3,7 @@ from .conv import build_conv_layer from .conv_module import ConvModule from .conv_ws import ConvAWS2d, ConvWS2d, conv_ws_2d +from .depthwise_separable_conv_module import DepthwiseSeparableConvModule from .generalized_attention import GeneralizedAttention from .hsigmoid import HSigmoid from .hswish import HSwish @@ -22,5 +23,5 @@ 'NonLocal2d', 'NonLocal3d', 'ContextBlock', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'ConvAWS2d', 'ConvWS2d', - 'conv_ws_2d' + 'conv_ws_2d', 'DepthwiseSeparableConvModule' ] diff --git a/mmcv/cnn/bricks/depthwise_separable_conv_module.py b/mmcv/cnn/bricks/depthwise_separable_conv_module.py new file mode 100644 index 0000000000..4eaf34c182 --- /dev/null +++ b/mmcv/cnn/bricks/depthwise_separable_conv_module.py @@ -0,0 +1,89 @@ +import torch.nn as nn + +from .conv_module import ConvModule + + +class DepthwiseSeparableConvModule(nn.Module): + """Depthwise separable convolution module. + + See https://arxiv.org/pdf/1704.04861.pdf for details. + + This module can replace a ConvModule with the conv block replaced by two + conv block: depthwise conv block and pointwise conv block. The depthwise + conv block contains depthwise-conv/norm/activation layers. The pointwise + conv block contains pointwise-conv/norm/activation layers. It should be + noted that there will be norm/activation layer in the depthwise conv block + if `norm_cfg` and `act_cfg` are specified. + + Args: + in_channels (int): Same as nn.Conv2d. + out_channels (int): Same as nn.Conv2d. + kernel_size (int or tuple[int]): Same as nn.Conv2d. + stride (int or tuple[int]): Same as nn.Conv2d. Default: 1. + padding (int or tuple[int]): Same as nn.Conv2d. Default: 0. + dilation (int or tuple[int]): Same as nn.Conv2d. Default: 1. + norm_cfg (dict): Default norm config for both depthwise ConvModule and + pointwise ConvModule. Default: None. + act_cfg (dict): Default activation config for both depthwise ConvModule + and pointwise ConvModule. Default: dict(type='ReLU'). + dw_norm_cfg (dict): Norm config of depthwise ConvModule. If it is + 'default', it will be the same as `norm_cfg`. Default: 'default'. + dw_act_cfg (dict): Activation config of depthwise ConvModule. If it is + 'default', it will be the same as `act_cfg`. Default: 'default'. + pw_norm_cfg (dict): Norm config of pointwise ConvModule. If it is + 'default', it will be the same as `norm_cfg`. Default: 'default'. + pw_act_cfg (dict): Activation config of pointwise ConvModule. If it is + 'default', it will be the same as `act_cfg`. Default: 'default'. + kwargs (optional): Other shared arguments for depthwise and pointwise + ConvModule. See ConvModule for ref. + """ + + def __init__(self, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + dilation=1, + norm_cfg=None, + act_cfg=dict(type='ReLU'), + dw_norm_cfg='default', + dw_act_cfg='default', + pw_norm_cfg='default', + pw_act_cfg='default', + **kwargs): + super(DepthwiseSeparableConvModule, self).__init__() + assert 'groups' not in kwargs, 'groups should not be specified' + + # if norm/activation config of depthwise/pointwise ConvModule is not + # specified, use default config. + dw_norm_cfg = dw_norm_cfg if dw_norm_cfg != 'default' else norm_cfg + dw_act_cfg = dw_act_cfg if dw_act_cfg != 'default' else act_cfg + pw_norm_cfg = pw_norm_cfg if pw_norm_cfg != 'default' else norm_cfg + pw_act_cfg = pw_act_cfg if pw_act_cfg != 'default' else act_cfg + + # depthwise convolution + self.depthwise_conv = ConvModule( + in_channels, + in_channels, + kernel_size, + stride=stride, + padding=padding, + dilation=dilation, + groups=in_channels, + norm_cfg=dw_norm_cfg, + act_cfg=dw_act_cfg, + **kwargs) + + self.pointwise_conv = ConvModule( + in_channels, + out_channels, + 1, + norm_cfg=pw_norm_cfg, + act_cfg=pw_act_cfg, + **kwargs) + + def forward(self, x): + x = self.depthwise_conv(x) + x = self.pointwise_conv(x) + return x diff --git a/tests/test_cnn/test_depthwise_seperable_conv_module.py b/tests/test_cnn/test_depthwise_seperable_conv_module.py new file mode 100644 index 0000000000..10b4c56824 --- /dev/null +++ b/tests/test_cnn/test_depthwise_seperable_conv_module.py @@ -0,0 +1,90 @@ +import pytest +import torch +import torch.nn as nn + +from mmcv.cnn.bricks import DepthwiseSeparableConvModule + + +def test_depthwise_separable_conv(): + with pytest.raises(AssertionError): + # conv_cfg must be a dict or None + DepthwiseSeparableConvModule(4, 8, 2, groups=2) + + # test default config + conv = DepthwiseSeparableConvModule(3, 8, 2) + assert conv.depthwise_conv.conv.groups == 3 + assert conv.pointwise_conv.conv.kernel_size == (1, 1) + assert not conv.depthwise_conv.with_norm + assert not conv.pointwise_conv.with_norm + assert conv.depthwise_conv.activate.__class__.__name__ == 'ReLU' + assert conv.pointwise_conv.activate.__class__.__name__ == 'ReLU' + x = torch.rand(1, 3, 256, 256) + output = conv(x) + assert output.shape == (1, 8, 255, 255) + + # test dw_norm_cfg + conv = DepthwiseSeparableConvModule(3, 8, 2, dw_norm_cfg=dict(type='BN')) + assert conv.depthwise_conv.norm_name == 'bn' + assert not conv.pointwise_conv.with_norm + x = torch.rand(1, 3, 256, 256) + output = conv(x) + assert output.shape == (1, 8, 255, 255) + + # test pw_norm_cfg + conv = DepthwiseSeparableConvModule(3, 8, 2, pw_norm_cfg=dict(type='BN')) + assert not conv.depthwise_conv.with_norm + assert conv.pointwise_conv.norm_name == 'bn' + x = torch.rand(1, 3, 256, 256) + output = conv(x) + assert output.shape == (1, 8, 255, 255) + + # test norm_cfg + conv = DepthwiseSeparableConvModule(3, 8, 2, norm_cfg=dict(type='BN')) + assert conv.depthwise_conv.norm_name == 'bn' + assert conv.pointwise_conv.norm_name == 'bn' + x = torch.rand(1, 3, 256, 256) + output = conv(x) + assert output.shape == (1, 8, 255, 255) + + # add test for ['norm', 'conv', 'act'] + conv = DepthwiseSeparableConvModule(3, 8, 2, order=('norm', 'conv', 'act')) + x = torch.rand(1, 3, 256, 256) + output = conv(x) + assert output.shape == (1, 8, 255, 255) + + conv = DepthwiseSeparableConvModule( + 3, 8, 3, padding=1, with_spectral_norm=True) + assert hasattr(conv.depthwise_conv.conv, 'weight_orig') + assert hasattr(conv.pointwise_conv.conv, 'weight_orig') + output = conv(x) + assert output.shape == (1, 8, 256, 256) + + conv = DepthwiseSeparableConvModule( + 3, 8, 3, padding=1, padding_mode='reflect') + assert isinstance(conv.depthwise_conv.padding_layer, nn.ReflectionPad2d) + output = conv(x) + assert output.shape == (1, 8, 256, 256) + + # test dw_act_cfg + conv = DepthwiseSeparableConvModule( + 3, 8, 3, padding=1, dw_act_cfg=dict(type='LeakyReLU')) + assert conv.depthwise_conv.activate.__class__.__name__ == 'LeakyReLU' + assert conv.pointwise_conv.activate.__class__.__name__ == 'ReLU' + output = conv(x) + assert output.shape == (1, 8, 256, 256) + + # test pw_act_cfg + conv = DepthwiseSeparableConvModule( + 3, 8, 3, padding=1, pw_act_cfg=dict(type='LeakyReLU')) + assert conv.depthwise_conv.activate.__class__.__name__ == 'ReLU' + assert conv.pointwise_conv.activate.__class__.__name__ == 'LeakyReLU' + output = conv(x) + assert output.shape == (1, 8, 256, 256) + + # test act_cfg + conv = DepthwiseSeparableConvModule( + 3, 8, 3, padding=1, act_cfg=dict(type='LeakyReLU')) + assert conv.depthwise_conv.activate.__class__.__name__ == 'LeakyReLU' + assert conv.pointwise_conv.activate.__class__.__name__ == 'LeakyReLU' + output = conv(x) + assert output.shape == (1, 8, 256, 256) From cac22f8cf5a904477e3b5461b1cc36856c2793da Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Sun, 9 Aug 2020 21:56:15 +0800 Subject: [PATCH 07/81] Add pytorch 1.6 to CI (#476) * add pytorch 1.6 to CI * fix typo * fix ci error Co-authored-by: Cao Yuhang --- .github/workflows/build.yml | 81 +++++++++++++++++++++---------------- README.md | 4 +- tests/test_parallel.py | 8 +++- 3 files changed, 55 insertions(+), 38 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index d713a9ee0b..c97c47faa0 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -31,6 +31,30 @@ jobs: extensions: h,c,cpp,hpp,cu,cuh style: google + build_without_torch: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: [3.7] + + steps: + - uses: actions/checkout@v2 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v2 + with: + python-version: ${{ matrix.python-version }} + - name: Install system dependencies + run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg + - name: Install unittest dependencies + run: pip install pytest coverage lmdb PyTurboJPEG + - name: Build and install + run: rm -rf .eggs && pip install -e . + - name: Install Pillow + run: pip install Pillow + - name: Run unittests and generate coverage report + run: | + pytest tests/ --ignore=tests/test_runner --ignore=tests/test_optimizer.py --ignore=tests/test_cnn --ignore=tests/test_parallel.py --ignore=tests/test_ops --ignore=tests/test_load_model_zoo.py --ignore=tests/test_logging.py --ignore=tests/test_image/test_io.py --ignore=tests/test_registry.py --ignore=tests/test_fp16.py + build_without_ops: runs-on: ubuntu-latest env: @@ -38,10 +62,10 @@ jobs: strategy: matrix: python-version: [3.7] - torch: [1.5.1] + torch: [1.6.0] include: - - torch: 1.5.1 - torchvision: 0.6.1 + - torch: 1.6.0 + torchvision: 0.7.0 steps: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} @@ -67,10 +91,16 @@ jobs: strategy: matrix: python-version: [3.7] - torch: [1.4.0] + torch: [1.3.1, 1.4.0, 1.5.1, 1.6.0] include: - - torch: 1.4.0 + - torch: 1.3.1 torchvision: 0.4.2 + - torch: 1.4.0 + torchvision: 0.5.0 + - torch: 1.5.1 + torchvision: 0.6.1 + - torch: 1.6.0 + torchvision: 0.7.0 steps: - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} @@ -104,16 +134,21 @@ jobs: MMCV_CUDA_ARGS: -gencode=arch=compute_61,code=sm_61 strategy: matrix: - python-version: [3.6, 3.7] - torch: [1.3.1, 1.5.1+cu101] + python-version: [3.7] + torch: [1.3.1, 1.5.1+cu101, 1.6.0+cu101] include: - torch: 1.3.1 torchvision: 0.4.2 - torch: 1.5.1+cu101 torchvision: 0.6.1+cu101 + - torch: 1.6.0+cu101 + torchvision: 0.7.0+cu101 + - python-version: 3.6 + torch: 1.6.0+cu101 + torchvision: 0.7.0+cu101 - python-version: 3.8 - torch: 1.5.1+cu101 - torchvision: 0.6.1+cu101 + torch: 1.6.0+cu101 + torchvision: 0.7.0+cu101 steps: - uses: actions/checkout@v2 @@ -162,40 +197,18 @@ jobs: name: codecov-umbrella fail_ci_if_error: false - build_no_torch: - runs-on: ubuntu-latest - strategy: - matrix: - python-version: [3.7] - - steps: - - uses: actions/checkout@v2 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 - with: - python-version: ${{ matrix.python-version }} - - name: Install system dependencies - run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg - - name: Install unittest dependencies - run: pip install pytest coverage lmdb PyTurboJPEG - - name: Build and install - run: rm -rf .eggs && pip install -e . - - name: Install Pillow - run: pip install Pillow - - name: Run unittests and generate coverage report - run: | - pytest tests/ --ignore=tests/test_runner --ignore=tests/test_optimizer.py --ignore=tests/test_cnn --ignore=tests/test_parallel.py --ignore=tests/test_ops --ignore=tests/test_load_model_zoo.py --ignore=tests/test_logging.py --ignore=tests/test_image/test_io.py --ignore=tests/test_registry.py --ignore=tests/test_fp16.py - build_macos: runs-on: macos-latest strategy: matrix: - torch: [1.5.1, 1.3.1] + torch: [1.3.1, 1.5.1, 1.6.0] include: - torch: 1.3.1 torchvision: 0.4.2 - torch: 1.5.1 torchvision: 0.6.1 + - torch: 1.6.0 + torchvision: 0.7.0 steps: - uses: actions/checkout@v2 - name: Set up Python 3.7 diff --git a/README.md b/README.md index d26a1d474d..2a76297296 100644 --- a/README.md +++ b/README.md @@ -122,13 +122,13 @@ You can either If you are on macOS, add the following environment variables before the installing command. ```bash -CC=lang CXX=clang++ CFLAGS='-stdlib=libc++' +CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' ``` e.g., ```bash -CC=lang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e . +CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e . ``` Note: If you would like to use `opencv-python-headless` instead of `opencv-python`, diff --git a/tests/test_parallel.py b/tests/test_parallel.py index 92fc8e7f00..93c8f57054 100644 --- a/tests/test_parallel.py +++ b/tests/test_parallel.py @@ -9,8 +9,12 @@ MMDistributedDataParallel as DeprecatedMMDDP -@patch('torch.distributed._broadcast_coalesced', MagicMock) -@patch('torch.distributed.broadcast', MagicMock) +def mock(*args, **kwargs): + pass + + +@patch('torch.distributed._broadcast_coalesced', mock) +@patch('torch.distributed.broadcast', mock) @patch('torch.nn.parallel.DistributedDataParallel._ddp_init_helper', MagicMock) def test_is_module_wrapper(): From e92f826abc6933ef115958f776c15db17e386684 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Tue, 11 Aug 2020 21:28:44 +0800 Subject: [PATCH 08/81] close the config file after opening (#480) --- mmcv/utils/config.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/mmcv/utils/config.py b/mmcv/utils/config.py index c7eaa6f18c..70da0df968 100644 --- a/mmcv/utils/config.py +++ b/mmcv/utils/config.py @@ -88,7 +88,7 @@ class Config: @staticmethod def _validate_py_syntax(filename): - with open(filename) as f: + with open(filename, 'r') as f: content = f.read() try: ast.parse(content) @@ -107,7 +107,8 @@ def _substitute_predefined_vars(filename, temp_config_name): fileBasename=file_basename, fileBasenameNoExtension=file_basename_no_extension, fileExtname=file_extname) - config_file = open(filename).read() + with open(filename, 'r') as f: + config_file = f.read() for key, value in support_templates.items(): regexp = r'\{\{\s*' + str(key) + r'\s*\}\}' config_file = re.sub(regexp, value, config_file) From 17e4732c49a5d58d236a3006df0130d166001c18 Mon Sep 17 00:00:00 2001 From: su Date: Wed, 12 Aug 2020 22:09:07 +0800 Subject: [PATCH 09/81] Change the epoch runner to use the data_loader from attributes rather than args. (#483) --- mmcv/runner/epoch_based_runner.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py index 6d5a09462d..aec827f3be 100644 --- a/mmcv/runner/epoch_based_runner.py +++ b/mmcv/runner/epoch_based_runner.py @@ -21,10 +21,10 @@ def train(self, data_loader, **kwargs): self.model.train() self.mode = 'train' self.data_loader = data_loader - self._max_iters = self._max_epochs * len(data_loader) + self._max_iters = self._max_epochs * len(self.data_loader) self.call_hook('before_train_epoch') time.sleep(2) # Prevent possible deadlock during epoch transition - for i, data_batch in enumerate(data_loader): + for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_train_iter') if self.batch_processor is None: @@ -52,7 +52,7 @@ def val(self, data_loader, **kwargs): self.data_loader = data_loader self.call_hook('before_val_epoch') time.sleep(2) # Prevent possible deadlock during epoch transition - for i, data_batch in enumerate(data_loader): + for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_val_iter') with torch.no_grad(): From 51c65c97ec73a4599c1ac04f342de22977e3b8b5 Mon Sep 17 00:00:00 2001 From: Yuanhao Zhu Date: Thu, 13 Aug 2020 19:27:05 +0800 Subject: [PATCH 10/81] fix syncbn parameter order mismatch and parrots bug (#488) --- mmcv/ops/csrc/pytorch/pybind.cpp | 12 ++++++------ mmcv/ops/csrc/pytorch/sync_bn.cpp | 10 +++++----- mmcv/ops/sync_bn.py | 16 ++++++---------- tests/test_ops/test_syncbn.py | 12 ++++++------ 4 files changed, 23 insertions(+), 27 deletions(-) diff --git a/mmcv/ops/csrc/pytorch/pybind.cpp b/mmcv/ops/csrc/pytorch/pybind.cpp index 544670a8fc..7aff46d20a 100644 --- a/mmcv/ops/csrc/pytorch/pybind.cpp +++ b/mmcv/ops/csrc/pytorch/pybind.cpp @@ -121,9 +121,9 @@ void sync_bn_forward_mean(const Tensor input, Tensor mean); void sync_bn_forward_var(const Tensor input, const Tensor mean, Tensor var); void sync_bn_forward_output(const Tensor input, const Tensor mean, - const Tensor var, Tensor running_mean, - Tensor running_var, const Tensor weight, - const Tensor bias, Tensor norm, Tensor std, + const Tensor var, const Tensor weight, + const Tensor bias, Tensor running_mean, + Tensor running_var, Tensor norm, Tensor std, Tensor output, float eps, float momentum, int group_size); @@ -299,9 +299,9 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { py::arg("input"), py::arg("mean"), py::arg("var")); m.def("sync_bn_forward_output", &sync_bn_forward_output, "sync_bn forward_output", py::arg("input"), py::arg("mean"), - py::arg("var"), py::arg("running_mean"), py::arg("running_var"), - py::arg("weight"), py::arg("bias"), py::arg("norm"), py::arg("std"), - py::arg("output"), py::arg("eps"), py::arg("momentum"), + py::arg("var"), py::arg("weight"), py::arg("bias"), + py::arg("running_mean"), py::arg("running_var"), py::arg("norm"), + py::arg("std"), py::arg("output"), py::arg("eps"), py::arg("momentum"), py::arg("group_size")); m.def("sync_bn_backward_param", &sync_bn_backward_param, "sync_bn backward_param", py::arg("grad_output"), py::arg("norm"), diff --git a/mmcv/ops/csrc/pytorch/sync_bn.cpp b/mmcv/ops/csrc/pytorch/sync_bn.cpp index 94b9b7c941..b8b29a8b18 100644 --- a/mmcv/ops/csrc/pytorch/sync_bn.cpp +++ b/mmcv/ops/csrc/pytorch/sync_bn.cpp @@ -89,9 +89,9 @@ void sync_bn_forward_var(const Tensor input, const Tensor mean, Tensor var) { } void sync_bn_forward_output(const Tensor input, const Tensor mean, - const Tensor var, Tensor running_mean, - Tensor running_var, const Tensor weight, - const Tensor bias, Tensor norm, Tensor std, + const Tensor var, const Tensor weight, + const Tensor bias, Tensor running_mean, + Tensor running_var, Tensor norm, Tensor std, Tensor output, float eps, float momentum, int group_size) { if (input.device().is_cuda()) { @@ -99,10 +99,10 @@ void sync_bn_forward_output(const Tensor input, const Tensor mean, CHECK_CUDA_INPUT(input); CHECK_CUDA_INPUT(mean); CHECK_CUDA_INPUT(var); - CHECK_CUDA_INPUT(running_mean); - CHECK_CUDA_INPUT(running_var); CHECK_CUDA_INPUT(weight); CHECK_CUDA_INPUT(bias); + CHECK_CUDA_INPUT(running_mean); + CHECK_CUDA_INPUT(running_var); CHECK_CUDA_INPUT(norm); CHECK_CUDA_INPUT(std); CHECK_CUDA_INPUT(output); diff --git a/mmcv/ops/sync_bn.py b/mmcv/ops/sync_bn.py index 9419100009..b2499f9dcc 100644 --- a/mmcv/ops/sync_bn.py +++ b/mmcv/ops/sync_bn.py @@ -52,14 +52,10 @@ def forward(self, input, running_mean, running_var, weight, bias, momentum, input3d.size(1), dtype=torch.float, device=input3d.device) var = torch.empty( input3d.size(1), dtype=torch.float, device=input3d.device) - if input3d.requires_grad or weight.requires_grad or bias.requires_grad: - norm = torch.empty_like( - input3d, dtype=torch.float, device=input3d.device) - std = torch.empty( - input3d.size(1), dtype=torch.float, device=input3d.device) - else: - norm = torch.empty(0, dtype=torch.float, device=input3d.device) - std = torch.empty(0, dtype=torch.float, device=input3d.device) + norm = torch.empty_like( + input3d, dtype=torch.float, device=input3d.device) + std = torch.empty( + input3d.size(1), dtype=torch.float, device=input3d.device) ext_module.sync_bn_forward_mean(input3d, mean) if self.group_size > 1: @@ -73,10 +69,10 @@ def forward(self, input, running_mean, running_var, weight, bias, momentum, input3d, mean, var, - running_mean, - running_var, weight, bias, + running_mean, + running_var, norm, std, output3d, diff --git a/tests/test_ops/test_syncbn.py b/tests/test_ops/test_syncbn.py index 6c0d87b1ed..01507d9542 100644 --- a/tests/test_ops/test_syncbn.py +++ b/tests/test_ops/test_syncbn.py @@ -21,13 +21,13 @@ def dist_init(self): node_list = str(os.environ['SLURM_NODELIST']) node_parts = re.findall('[0-9]+', node_list) - host_ip = '{}.{}.{}.{}'.format(node_parts[1], node_parts[2], - node_parts[3], node_parts[4]) - port = '12341' - init_method = 'tcp://{}:{}'.format(host_ip, port) + os.environ['MASTER_ADDR'] = (f'{node_parts[1]}.{node_parts[2]}' + + f'.{node_parts[3]}.{node_parts[4]}') + os.environ['MASTER_PORT'] = '12341' + os.environ['WORLD_SIZE'] = str(world_size) + os.environ['RANK'] = str(rank) - dist.init_process_group( - 'nccl', init_method=init_method, world_size=world_size, rank=rank) + dist.init_process_group('nccl') torch.cuda.set_device(local_rank) def _test_syncbn_train(self, size=1, half=False): From e7e0c89f5cd49b090a3994d14e0b5c7c6f1e2ea2 Mon Sep 17 00:00:00 2001 From: Zijian He Date: Thu, 13 Aug 2020 19:30:28 +0800 Subject: [PATCH 11/81] fix the bug (#472) (#484) * fix the bug (#472) * fix the bug (#472) * fix the bug (#472) Co-authored-by: hezijian --- mmcv/runner/hooks/sampler_seed.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/mmcv/runner/hooks/sampler_seed.py b/mmcv/runner/hooks/sampler_seed.py index e57f1e9e8a..93793f7c22 100644 --- a/mmcv/runner/hooks/sampler_seed.py +++ b/mmcv/runner/hooks/sampler_seed.py @@ -6,4 +6,9 @@ class DistSamplerSeedHook(Hook): def before_epoch(self, runner): - runner.data_loader.sampler.set_epoch(runner.epoch) + if hasattr(runner.data_loader.sampler, 'set_epoch'): + # in case the data loader uses `SequentialSampler` in Pytorch + runner.data_loader.sampler.set_epoch(runner.epoch) + if hasattr(runner.data_loader.batch_sampler.sampler, 'set_epoch'): + # batch sampler in pytorch warps a sampler as its attributes. + runner.data_loader.batch_sampler.sampler.set_epoch(runner.epoch) From 4cc48073bc778b26a12da1cd902a7f11bed65551 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Thu, 13 Aug 2020 19:32:28 +0800 Subject: [PATCH 12/81] Change pretrain url from aws to aliyun (#490) --- mmcv/model_zoo/open_mmlab.json | 74 +++++++++++++++++----------------- 1 file changed, 37 insertions(+), 37 deletions(-) diff --git a/mmcv/model_zoo/open_mmlab.json b/mmcv/model_zoo/open_mmlab.json index 387af4e001..2acc3f3383 100644 --- a/mmcv/model_zoo/open_mmlab.json +++ b/mmcv/model_zoo/open_mmlab.json @@ -1,41 +1,41 @@ { - "vgg16_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/vgg16_caffe-292e1171.pth", - "detectron/resnet50_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_caffe-788b5fa3.pth", - "detectron2/resnet50_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_msra-5891d200.pth", - "detectron/resnet101_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet101_caffe-3ad79236.pth", - "detectron2/resnet101_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet101_msra-6cc46731.pth", - "detectron2/resnext101_32x8d": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext101_32x8d-1516f1aa.pth", - "resnext50_32x4d": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext50-32x4d-0ab1a123.pth", - "resnext101_32x4d": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext101_32x4d-a5af3160.pth", - "resnext101_64x4d": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext101_64x4d-ee2c6f71.pth", - "contrib/resnet50_gn": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_gn_thangvubk-ad1730dd.pth", - "detectron/resnet50_gn": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_gn-9186a21c.pth", - "detectron/resnet101_gn": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet101_gn-cac0ab98.pth", - "jhu/resnet50_gn_ws": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_gn_ws-15beedd8.pth", - "jhu/resnet101_gn_ws": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet101_gn_ws-3e3c308c.pth", - "jhu/resnext50_32x4d_gn_ws": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext50_32x4d_gn_ws-0d87ac85.pth", - "jhu/resnext101_32x4d_gn_ws": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext101_32x4d_gn_ws-34ac1a9e.pth", - "jhu/resnext50_32x4d_gn": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext50_32x4d_gn-c7e8b754.pth", - "jhu/resnext101_32x4d_gn": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnext101_32x4d_gn-ac3bb84e.pth", - "msra/hrnetv2_w18_small": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w18_small-b5a04e21.pth", - "msra/hrnetv2_w18": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w18-00eb2006.pth", - "msra/hrnetv2_w32": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w32-dc9eeb4f.pth", - "msra/hrnetv2_w40": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w40-ed0b031c.pth", - "msra/hrnetv2_w48": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", - "bninception_caffe": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/bn_inception_caffe-ed2e8665.pth", - "kin400/i3d_r50_f32s2_k400": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/i3d_r50_f32s2_k400-2c57e077.pth", - "kin400/nl3d_r50_f32s2_k400": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/nl3d_r50_f32s2_k400-fa7e7caa.pth", - "res2net101_v1d_26w_4s": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/res2net101_v1d_26w_4s_mmdetv2-f0a600f9.pth", - "regnetx_400mf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_400mf-a5b10d96.pth", - "regnetx_800mf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_800mf-1f4be4c7.pth", - "regnetx_1.6gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_1.6gf-5791c176.pth", - "regnetx_3.2gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_3.2gf-c2599b0f.pth", - "regnetx_4.0gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_4.0gf-a88f671e.pth", - "regnetx_6.4gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_6.4gf-006af45d.pth", - "regnetx_8.0gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_8.0gf-3c68abe7.pth", - "regnetx_12gf": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/regnetx_12gf-4c2a3350.pth", - "resnet50_v1c": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet50_v1c-2cccc1ad.pth", - "resnet101_v1c": "https://open-mmlab.s3.ap-northeast-2.amazonaws.com/pretrain/third_party/resnet101_v1c-e67eebb6.pth", + "vgg16_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/vgg16_caffe-292e1171.pth", + "detectron/resnet50_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_caffe-788b5fa3.pth", + "detectron2/resnet50_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_msra-5891d200.pth", + "detectron/resnet101_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_caffe-3ad79236.pth", + "detectron2/resnet101_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_msra-6cc46731.pth", + "detectron2/resnext101_32x8d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x8d-1516f1aa.pth", + "resnext50_32x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50-32x4d-0ab1a123.pth", + "resnext101_32x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d-a5af3160.pth", + "resnext101_64x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_64x4d-ee2c6f71.pth", + "contrib/resnet50_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn_thangvubk-ad1730dd.pth", + "detectron/resnet50_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn-9186a21c.pth", + "detectron/resnet101_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_gn-cac0ab98.pth", + "jhu/resnet50_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn_ws-15beedd8.pth", + "jhu/resnet101_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_gn_ws-3e3c308c.pth", + "jhu/resnext50_32x4d_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50_32x4d_gn_ws-0d87ac85.pth", + "jhu/resnext101_32x4d_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d_gn_ws-34ac1a9e.pth", + "jhu/resnext50_32x4d_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50_32x4d_gn-c7e8b754.pth", + "jhu/resnext101_32x4d_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d_gn-ac3bb84e.pth", + "msra/hrnetv2_w18_small": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w18_small-b5a04e21.pth", + "msra/hrnetv2_w18": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w18-00eb2006.pth", + "msra/hrnetv2_w32": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w32-dc9eeb4f.pth", + "msra/hrnetv2_w40": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w40-ed0b031c.pth", + "msra/hrnetv2_w48": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", + "bninception_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/bn_inception_caffe-ed2e8665.pth", + "kin400/i3d_r50_f32s2_k400": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/i3d_r50_f32s2_k400-2c57e077.pth", + "kin400/nl3d_r50_f32s2_k400": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/nl3d_r50_f32s2_k400-fa7e7caa.pth", + "res2net101_v1d_26w_4s": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/res2net101_v1d_26w_4s_mmdetv2-f0a600f9.pth", + "regnetx_400mf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_400mf-a5b10d96.pth", + "regnetx_800mf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_800mf-1f4be4c7.pth", + "regnetx_1.6gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_1.6gf-5791c176.pth", + "regnetx_3.2gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_3.2gf-c2599b0f.pth", + "regnetx_4.0gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_4.0gf-a88f671e.pth", + "regnetx_6.4gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_6.4gf-006af45d.pth", + "regnetx_8.0gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_8.0gf-3c68abe7.pth", + "regnetx_12gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_12gf-4c2a3350.pth", + "resnet50_v1c": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_v1c-2cccc1ad.pth", + "resnet101_v1c": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_v1c-e67eebb6.pth", "mmedit/vgg16": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/vgg_state_dict.pth", "mmedit/res34_en_nomixup": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/model_best_resnet34_En_nomixup.pth", "mmedit/mobilenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/mobilenet_v2.pth", From 5ade35f4cf84c67409e68a178825346d92881952 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Thu, 13 Aug 2020 20:38:27 +0800 Subject: [PATCH 13/81] use elif rather than if (#491) --- mmcv/runner/hooks/sampler_seed.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/mmcv/runner/hooks/sampler_seed.py b/mmcv/runner/hooks/sampler_seed.py index 93793f7c22..535d801ec5 100644 --- a/mmcv/runner/hooks/sampler_seed.py +++ b/mmcv/runner/hooks/sampler_seed.py @@ -9,6 +9,6 @@ def before_epoch(self, runner): if hasattr(runner.data_loader.sampler, 'set_epoch'): # in case the data loader uses `SequentialSampler` in Pytorch runner.data_loader.sampler.set_epoch(runner.epoch) - if hasattr(runner.data_loader.batch_sampler.sampler, 'set_epoch'): - # batch sampler in pytorch warps a sampler as its attributes. + elif hasattr(runner.data_loader.batch_sampler.sampler, 'set_epoch'): + # batch sampler in pytorch warps the sampler as its attributes. runner.data_loader.batch_sampler.sampler.set_epoch(runner.epoch) From dc778481cbe10a099d98543e6adee728999b7d54 Mon Sep 17 00:00:00 2001 From: Cao Yuhang Date: Thu, 13 Aug 2020 22:04:58 +0800 Subject: [PATCH 14/81] add op trouble shooting (#479) * add op trouble shooting * update trouble_shooting.md * clean ops.md * add trouble shooting to index.rst * reorder * add troubleshooting in readme --- README.md | 5 +++++ docs/index.rst | 1 + docs/trouble_shooting.md | 37 +++++++++++++++++++++++++++++++++++++ 3 files changed, 43 insertions(+) create mode 100644 docs/trouble_shooting.md diff --git a/README.md b/README.md index 2a76297296..fe22efc91d 100644 --- a/README.md +++ b/README.md @@ -134,3 +134,8 @@ CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e . Note: If you would like to use `opencv-python-headless` instead of `opencv-python`, e.g., in a minimum container environment or servers without GUI, you can first install it before installing MMCV to skip the installation of `opencv-python`. + + +### TroubleShooting + +If you meet issues when running or compiling mmcv, we list some common issues in [TROUBLESHOOTING.md](docs/trouble_shooting.md). diff --git a/docs/index.rst b/docs/index.rst index 0fd8dbb33b..c7ef3936d8 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -15,6 +15,7 @@ Contents runner.md cnn.md ops.md + trouble_shooting.md api.rst diff --git a/docs/trouble_shooting.md b/docs/trouble_shooting.md new file mode 100644 index 0000000000..928027540d --- /dev/null +++ b/docs/trouble_shooting.md @@ -0,0 +1,37 @@ +## Trouble Shooting + +We list some common troubles faced by many users and their corresponding solutions here. +Feel free to enrich the list if you find any frequent issues and have ways to help others to solve them. + +- Compatibility issue between MMCV and MMDetection; "ConvWS is already registered in conv layer" + + Please install the correct version of MMCV for the version of your MMDetection following the instruction above. + +- "No module named 'mmcv.ops'"; "No module named 'mmcv._ext'". + + 1. Uninstall existing mmcv in the environment using `pip uninstall mmcv`. + 2. Install mmcv-full following the instruction above. + +- "invalid device function" or "no kernel image is available for execution". + + 1. Check the CUDA compute capability of you GPU. + 2. Run `python mmdet/utils/collect_env.py` to check whether PyTorch, torchvision, + and MMCV are built for the correct GPU architecture. + You may need to set `TORCH_CUDA_ARCH_LIST` to reinstall MMCV. + The compatibility issue could happen when using old GPUS, e.g., Tesla K80 (3.7) on colab. + 3. Check whether the running environment is the same as that when mmcv/mmdet is compiled. + For example, you may compile mmcv using CUDA 10.0 bug run it on CUDA9.0 environments. + +- "undefined symbol" or "cannot open xxx.so". + + 1. If those symbols are CUDA/C++ symbols (e.g., libcudart.so or GLIBCXX), check + whether the CUDA/GCC runtimes are the same as those used for compiling mmcv. + 2. If those symbols are Pytorch symbols (e.g., symbols containing caffe, aten, and TH), check whether + the Pytorch version is the same as that used for compiling mmcv. + 3. Run `python mmdet/utils/collect_env.py` to check whether PyTorch, torchvision, + and MMCV are built by and running on the same environment. + +- "RuntimeError: CUDA error: invalid configuration argument". + + This error may be due to your poor GPU. Try to decrease the value of [THREADS_PER_BLOCK](https://github.com/open-mmlab/mmcv/blob/cac22f8cf5a904477e3b5461b1cc36856c2793da/mmcv/ops/csrc/common_cuda_helper.hpp#L10) + and recompile mmcv. From d19fad02bab88b501b30c0121024ca767b02ad9a Mon Sep 17 00:00:00 2001 From: Wang Xinjiang Date: Thu, 13 Aug 2020 22:05:43 +0800 Subject: [PATCH 15/81] Add json set_default for unserializable values (#485) * Add json set_default for unserializable values * kwargs.setdefault --- mmcv/fileio/handlers/json_handler.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/mmcv/fileio/handlers/json_handler.py b/mmcv/fileio/handlers/json_handler.py index 0573b9a321..7da9020918 100644 --- a/mmcv/fileio/handlers/json_handler.py +++ b/mmcv/fileio/handlers/json_handler.py @@ -1,16 +1,32 @@ # Copyright (c) Open-MMLab. All rights reserved. import json +import numpy as np + from .base import BaseFileHandler +def set_default(obj): + """Set default json values for non-serializable values. + + It helps convert ``set``, ``range`` and ``np.ndarray`` data types to list. + """ + if isinstance(obj, (set, range)): + return list(obj) + elif isinstance(obj, np.ndarray): + return obj.tolist() + raise TypeError + + class JsonHandler(BaseFileHandler): def load_from_fileobj(self, file): return json.load(file) def dump_to_fileobj(self, obj, file, **kwargs): + kwargs.setdefault('default', set_default) json.dump(obj, file, **kwargs) def dump_to_str(self, obj, **kwargs): + kwargs.setdefault('default', set_default) return json.dumps(obj, **kwargs) From 15537c5a397bc5e95da0bc34af26f0c956487287 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Fri, 14 Aug 2020 20:35:05 +0800 Subject: [PATCH 16/81] Add LOCAL_RANK env var for slurm (#496) --- mmcv/runner/dist_utils.py | 1 + 1 file changed, 1 insertion(+) diff --git a/mmcv/runner/dist_utils.py b/mmcv/runner/dist_utils.py index b89a3c8891..c6e544d475 100644 --- a/mmcv/runner/dist_utils.py +++ b/mmcv/runner/dist_utils.py @@ -63,6 +63,7 @@ def _init_dist_slurm(backend, port=None): os.environ['MASTER_PORT'] = '29500' os.environ['MASTER_ADDR'] = addr os.environ['WORLD_SIZE'] = str(ntasks) + os.environ['LOCAL_RANK'] = str(proc_id % num_gpus) os.environ['RANK'] = str(proc_id) dist.init_process_group(backend=backend) From c8e85b28e4b22c3ad86def014185ebf8d459795f Mon Sep 17 00:00:00 2001 From: Jintao Lin <528557675@qq.com> Date: Sat, 15 Aug 2020 22:29:07 +0800 Subject: [PATCH 17/81] Add `tin_shift` function (#492) * add tin shift * add unittest * add docstring * add docstring * parrots for tin_shift * fix lint * fix lint Co-authored-by: jiaomenglei --- mmcv/ops/__init__.py | 3 +- mmcv/ops/csrc/parrots/tin_shift.cpp | 42 ++++++++++ mmcv/ops/csrc/parrots/tin_shift_cuda.cu | 51 ++++++++++++ mmcv/ops/csrc/pytorch/pybind.cpp | 9 ++ mmcv/ops/csrc/pytorch/tin_shift.cpp | 51 ++++++++++++ mmcv/ops/csrc/pytorch/tin_shift_cuda.cu | 53 ++++++++++++ mmcv/ops/csrc/tin_shift_cuda_kernel.cuh | 60 ++++++++++++++ mmcv/ops/tin_shift.py | 62 ++++++++++++++ tests/test_ops/test_tin_shift.py | 106 ++++++++++++++++++++++++ 9 files changed, 436 insertions(+), 1 deletion(-) create mode 100644 mmcv/ops/csrc/parrots/tin_shift.cpp create mode 100644 mmcv/ops/csrc/parrots/tin_shift_cuda.cu create mode 100644 mmcv/ops/csrc/pytorch/tin_shift.cpp create mode 100644 mmcv/ops/csrc/pytorch/tin_shift_cuda.cu create mode 100644 mmcv/ops/csrc/tin_shift_cuda_kernel.cuh create mode 100644 mmcv/ops/tin_shift.py create mode 100644 tests/test_ops/test_tin_shift.py diff --git a/mmcv/ops/__init__.py b/mmcv/ops/__init__.py index 39d9bce8d8..b38aff9253 100644 --- a/mmcv/ops/__init__.py +++ b/mmcv/ops/__init__.py @@ -20,6 +20,7 @@ from .roi_pool import RoIPool, roi_pool from .saconv import SAConv2d from .sync_bn import SyncBatchNorm +from .tin_shift import TINShift, tin_shift from .wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d __all__ = [ @@ -34,5 +35,5 @@ 'RoIAlign', 'roi_align', 'RoIPool', 'roi_pool', 'SyncBatchNorm', 'Conv2d', 'ConvTranspose2d', 'Linear', 'MaxPool2d', 'CrissCrossAttention', 'PSAMask', 'point_sample', 'rel_roi_point_to_rel_img_point', 'SimpleRoIAlign', - 'SAConv2d' + 'SAConv2d', 'TINShift', 'tin_shift' ] diff --git a/mmcv/ops/csrc/parrots/tin_shift.cpp b/mmcv/ops/csrc/parrots/tin_shift.cpp new file mode 100644 index 0000000000..a31444bfdd --- /dev/null +++ b/mmcv/ops/csrc/parrots/tin_shift.cpp @@ -0,0 +1,42 @@ +#include "parrots_cpp_helper.hpp" + +void TINShiftForwardCUDAKernelLauncher(const DArrayLite input, + const DArrayLite shift, + DArrayLite output, cudaStream_t stream); + +void TINShiftBackwardCUDAKernelLauncher(const DArrayLite grad_output, + const DArrayLite shift, + DArrayLite grad_input, + cudaStream_t stream); + +void tin_shift_forward_cuda(CudaContext &ctx, const SSElement &attr, + const OperatorBase::in_list_t &ins, + OperatorBase::out_list_t &outs) { + const auto &input = ins[0]; + const auto &shift = ins[1]; + auto &output = outs[0]; + cudaStream_t stream = getStreamNative(ctx.getStream()); + TINShiftForwardCUDAKernelLauncher(input, shift, output, stream); +} + +void tin_shift_backward_cuda(CudaContext &ctx, const SSElement &attr, + const OperatorBase::in_list_t &ins, + OperatorBase::out_list_t &outs) { + const auto &grad_output = ins[0]; + const auto &shift = ins[1]; + auto &grad_input = outs[0]; + cudaStream_t stream = getStreamNative(ctx.getStream()); + TINShiftBackwardCUDAKernelLauncher(grad_output, shift, grad_input, stream); +} + +PARROTS_EXTENSION_REGISTER(tin_shift_forward) + .input(2) + .output(1) + .apply(tin_shift_forward_cuda) + .done(); + +PARROTS_EXTENSION_REGISTER(tin_shift_backward) + .input(2) + .output(1) + .apply(tin_shift_backward_cuda) + .done(); \ No newline at end of file diff --git a/mmcv/ops/csrc/parrots/tin_shift_cuda.cu b/mmcv/ops/csrc/parrots/tin_shift_cuda.cu new file mode 100644 index 0000000000..e5deaec061 --- /dev/null +++ b/mmcv/ops/csrc/parrots/tin_shift_cuda.cu @@ -0,0 +1,51 @@ +#include "parrots_cuda_helper.hpp" +#include "tin_shift_cuda_kernel.cuh" + +void TINShiftForwardCUDAKernelLauncher(const DArrayLite input, + const DArrayLite shift, + DArrayLite output, cudaStream_t stream) { + int output_size = output.size(); + int batch_size = input.dim(0); + int t_size = input.dim(1); + int channels = input.dim(2); + int hw_size = input.dim(3); + int group_size = shift.dim(1); + int group_channel = channels / group_size; + int num_kernels = batch_size * hw_size * channels; + + PARROTS_DISPATCH_FLOATING_TYPES_AND_HALF( + input.elemType().prim(), ([&] { + tin_shift_forward_cuda_kernel + <<>>( + output_size, input.ptr(), shift.ptr(), + output.ptr(), batch_size, channels, t_size, hw_size, + group_size, group_channel); + })); + + PARROTS_CUDA_CHECK(cudaGetLastError()); +} + +void TINShiftBackwardCUDAKernelLauncher(const DArrayLite grad_output, + const DArrayLite shift, + DArrayLite grad_input, + cudaStream_t stream) { + int output_size = grad_output.size(); + int batch_size = grad_output.dim(0); + int t_size = grad_output.dim(1); + int channels = grad_output.dim(2); + int hw_size = grad_output.dim(3); + int group_size = shift.dim(1); + int group_channel = channels / group_size; + int num_kernels = batch_size * hw_size * channels; + + PARROTS_DISPATCH_FLOATING_TYPES_AND_HALF( + grad_output.elemType().prim(), ([&] { + tin_shift_backward_cuda_kernel + <<>>( + output_size, grad_output.ptr(), shift.ptr(), + grad_input.ptr(), batch_size, channels, t_size, + hw_size, group_size, group_channel); + })); + + PARROTS_CUDA_CHECK(cudaGetLastError()); +} diff --git a/mmcv/ops/csrc/pytorch/pybind.cpp b/mmcv/ops/csrc/pytorch/pybind.cpp index 7aff46d20a..a2224fdb3d 100644 --- a/mmcv/ops/csrc/pytorch/pybind.cpp +++ b/mmcv/ops/csrc/pytorch/pybind.cpp @@ -155,6 +155,11 @@ void psamask_backward(Tensor grad_output, const Tensor grad_input, const int w_feature, const int h_mask, const int w_mask, const int half_h_mask, const int half_w_mask); +void tin_shift_forward(const Tensor input, const Tensor shift, Tensor output); + +void tin_shift_backward(Tensor grad_output, const Tensor shift, + const Tensor grad_input); + Tensor bottom_pool_forward(Tensor input); Tensor bottom_pool_backward(Tensor input, Tensor grad_output); @@ -329,6 +334,10 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { py::arg("num_"), py::arg("h_feature"), py::arg("w_feature"), py::arg("h_mask"), py::arg("w_mask"), py::arg("half_h_mask"), py::arg("half_w_mask")); + m.def("tin_shift_forward", &tin_shift_forward, "tin_shift forward", + py::arg("input"), py::arg("shift"), py::arg("output")); + m.def("tin_shift_backward", &tin_shift_backward, "tin_shift backward", + py::arg("grad_output"), py::arg("shift"), py::arg("grad_input")); m.def("bottom_pool_forward", &bottom_pool_forward, "Bottom Pool Forward", py::arg("input"), py::call_guard()); m.def("bottom_pool_backward", &bottom_pool_backward, "Bottom Pool Backward", diff --git a/mmcv/ops/csrc/pytorch/tin_shift.cpp b/mmcv/ops/csrc/pytorch/tin_shift.cpp new file mode 100644 index 0000000000..255ce4fffe --- /dev/null +++ b/mmcv/ops/csrc/pytorch/tin_shift.cpp @@ -0,0 +1,51 @@ +#include "pytorch_cpp_helper.hpp" + +#ifdef MMCV_WITH_CUDA +void TINShiftForwardCUDAKernelLauncher(Tensor input, Tensor shift, + Tensor output); + +void TINShiftBackwardCUDAKernelLauncher(Tensor grad_output, Tensor shift, + Tensor grad_input); + +void tin_shift_forward_cuda(Tensor input, Tensor shift, Tensor output) { + TINShiftForwardCUDAKernelLauncher(input, shift, output); +} + +void tin_shift_backward_cuda(Tensor grad_output, Tensor shift, + Tensor grad_input) { + TINShiftBackwardCUDAKernelLauncher(grad_output, shift, grad_input); +} + +#endif + +void tin_shift_forward(Tensor input, Tensor shift, Tensor output) { + if (input.device().is_cuda()) { +#ifdef MMCV_WITH_CUDA + CHECK_CUDA_INPUT(input); + CHECK_CUDA_INPUT(shift); + CHECK_CUDA_INPUT(output); + + tin_shift_forward_cuda(input, shift, output); +#else + AT_ERROR("TINShift is not compiled with GPU support"); +#endif + } else { + AT_ERROR("TINShift is not implemented on CPU"); + } +} + +void tin_shift_backward(Tensor grad_output, Tensor shift, Tensor grad_input) { + if (grad_output.device().is_cuda()) { +#ifdef MMCV_WITH_CUDA + CHECK_CUDA_INPUT(grad_output); + CHECK_CUDA_INPUT(shift); + CHECK_CUDA_INPUT(grad_input); + + tin_shift_backward_cuda(grad_output, shift, grad_input); +#else + AT_ERROR("TINShift is not compiled with GPU support"); +#endif + } else { + AT_ERROR("TINShift is not implemented on CPU"); + } +} diff --git a/mmcv/ops/csrc/pytorch/tin_shift_cuda.cu b/mmcv/ops/csrc/pytorch/tin_shift_cuda.cu new file mode 100644 index 0000000000..996816ee4f --- /dev/null +++ b/mmcv/ops/csrc/pytorch/tin_shift_cuda.cu @@ -0,0 +1,53 @@ +#include "pytorch_cuda_helper.hpp" +#include "tin_shift_cuda_kernel.cuh" + +void TINShiftForwardCUDAKernelLauncher(Tensor input, Tensor shift, + Tensor output) { + int output_size = output.numel(); + int batch_size = input.size(0); + int t_size = input.size(1); + int channels = input.size(2); + int hw_size = input.size(3); + int group_size = shift.size(1); + int group_channel = channels / group_size; + int num_kernels = batch_size * hw_size * channels; + + at::cuda::CUDAGuard device_guard(input.device()); + cudaStream_t stream = at::cuda::getCurrentCUDAStream(); + AT_DISPATCH_FLOATING_TYPES_AND_HALF( + input.scalar_type(), "tin_shift_forward_cuda_kernel", [&] { + tin_shift_forward_cuda_kernel + <<>>( + output_size, input.data_ptr(), shift.data_ptr(), + output.data_ptr(), batch_size, channels, t_size, + hw_size, group_size, group_channel); + }); + + AT_CUDA_CHECK(cudaGetLastError()); +} + +void TINShiftBackwardCUDAKernelLauncher(Tensor grad_output, Tensor shift, + Tensor grad_input) { + int output_size = grad_output.numel(); + int batch_size = grad_output.size(0); + int t_size = grad_output.size(1); + int channels = grad_output.size(2); + int hw_size = grad_output.size(3); + int group_size = shift.size(1); + int group_channel = channels / group_size; + int num_kernels = batch_size * hw_size * channels; + + at::cuda::CUDAGuard device_guard(grad_output.device()); + cudaStream_t stream = at::cuda::getCurrentCUDAStream(); + AT_DISPATCH_FLOATING_TYPES_AND_HALF( + grad_output.scalar_type(), "tin_shift_backward_cuda_kernel", [&] { + tin_shift_backward_cuda_kernel + <<>>( + output_size, grad_output.data_ptr(), + shift.data_ptr(), grad_input.data_ptr(), + batch_size, channels, t_size, hw_size, group_size, + group_channel); + }); + + AT_CUDA_CHECK(cudaGetLastError()); +} diff --git a/mmcv/ops/csrc/tin_shift_cuda_kernel.cuh b/mmcv/ops/csrc/tin_shift_cuda_kernel.cuh new file mode 100644 index 0000000000..352244bb21 --- /dev/null +++ b/mmcv/ops/csrc/tin_shift_cuda_kernel.cuh @@ -0,0 +1,60 @@ +#ifndef TIN_SHIFT_CUDA_KERNEL_CUH +#define TIN_SHIFT_CUDA_KERNEL_CUH + +#ifdef MMCV_USE_PARROTS +#include "parrots_cuda_helper.hpp" +#else +#include "pytorch_cuda_helper.hpp" +#endif + +template +__global__ void tin_shift_forward_cuda_kernel( + const int nthreads, const T* input, const int* shift, T* output, + const int batch_size, const int channels, const int t_size, + const int hw_size, const int group_size, const int group_channel) { + CUDA_1D_KERNEL_LOOP(index, nthreads) { + const int hw_index = index % hw_size; + const int j = (index / hw_size) % channels; + + const int n_index = (index / hw_size / channels) % batch_size; + int group_id = j / group_channel; + int t_shift = shift[n_index * group_size + group_id]; + int offset = n_index * t_size * hw_size * channels + hw_size * j + hw_index; + for (int i = 0; i < t_size; i++) { + int now_t = i + t_shift; + int data_id = i * hw_size * channels + offset; + if (now_t < 0 || now_t >= t_size) { + continue; + } + int out_id = now_t * hw_size * channels + offset; + output[out_id] = input[data_id]; + } + } +} + +template +__global__ void tin_shift_backward_cuda_kernel( + const int nthreads, const T* input, const int* shift, T* output, + const int batch_size, const int channels, const int t_size, + const int hw_size, const int group_size, const int group_channel) { + CUDA_1D_KERNEL_LOOP(index, nthreads) { + const int hw_index = index % hw_size; + const int j = (index / hw_size) % channels; + + const int n_index = (index / hw_size / channels) % batch_size; + int group_id = j / group_channel; + int t_shift = shift[n_index * group_size + group_id]; + int offset = n_index * t_size * hw_size * channels + hw_size * j + hw_index; + for (int i = 0; i < t_size; i++) { + int now_t = i + t_shift; + int data_id = i * hw_size * channels + offset; + if (now_t < 0 || now_t >= t_size) { + continue; + } + int out_id = now_t * hw_size * channels + offset; + output[out_id] = input[data_id]; + } + } +} + +#endif // TIN_SHIFT_CUDA_KERNEL_CUH diff --git a/mmcv/ops/tin_shift.py b/mmcv/ops/tin_shift.py new file mode 100644 index 0000000000..5560af4469 --- /dev/null +++ b/mmcv/ops/tin_shift.py @@ -0,0 +1,62 @@ +# Code reference from "Temporal Interlacing Network" +# https://github.com/deepcs233/TIN/blob/master/cuda_shift/rtc_wrap.py +# Hao Shao, Shengju Qian, Yu Liu +# shaoh19@mails.tsinghua.edu.cn, sjqian@cse.cuhk.edu.hk, yuliu@ee.cuhk.edu.hk + +import torch +import torch.nn as nn +from torch.autograd import Function + +from ..utils import ext_loader + +ext_module = ext_loader.load_ext('_ext', + ['tin_shift_forward', 'tin_shift_backward']) + + +class TINShiftFunction(Function): + + @staticmethod + def forward(ctx, input, shift): + + ctx.save_for_backward(shift) + + out = torch.zeros_like(input) + ext_module.tin_shift_forward(input, shift, out) + + return out + + @staticmethod + def backward(ctx, grad_output): + + shift = ctx.saved_tensors[0] + data_grad_input = grad_output.new(*grad_output.size()).zero_() + shift_grad_input = shift.new(*shift.size()).zero_() + ext_module.tin_shift_backward(grad_output, shift, data_grad_input) + + return data_grad_input, shift_grad_input + + +tin_shift = TINShiftFunction.apply + + +class TINShift(nn.Module): + """Temporal Interlace Shift. + + Temporal Interlace shift is a differentiable temporal-wise frame shifting + which is proposed in "Temporal Interlacing Network" + + Please refer to https://arxiv.org/abs/2001.06499 for more details. + Code is modified from https://github.com/mit-han-lab/temporal-shift-module + """ + + def forward(self, input, shift): + """Perform temporal interlace shift. + + Args: + input (Tensor): Feature map with shape [N, num_segments, C, H * W]. + shift (Tensor): Shift tensor with shape [N, num_segments]. + + Returns: + Feature map after temporal interlace shift. + """ + return tin_shift(input, shift) diff --git a/tests/test_ops/test_tin_shift.py b/tests/test_ops/test_tin_shift.py new file mode 100644 index 0000000000..898c46e4c4 --- /dev/null +++ b/tests/test_ops/test_tin_shift.py @@ -0,0 +1,106 @@ +import os + +import numpy as np +import pytest +import torch + +_USING_PARROTS = True +try: + from parrots.autograd import gradcheck +except ImportError: + from torch.autograd import gradcheck + + _USING_PARROTS = False + +cur_dir = os.path.dirname(os.path.abspath(__file__)) + +inputs = ([[[[0.4369, -3.7571], [-1.1835, -1.6374], [0.9534, -0.1321]], + [[-0.4658, 0.2162], [-0.8135, -0.3903], [-0.1720, -0.0599]], + [[0.4851, 1.8224], [0.8973, 0.3779], [2.3454, 1.0319]], + [[0.0420, 0.3574], [0.7641, 0.2384], [0.2759, 0.4931]]], + [[[-0.5897, 0.7544], [1.0593, 0.8388], [-0.5732, 0.5692]], + [[-0.6766, -1.4657], [1.2362, 0.4913], [-1.1820, -1.4341]], + [[0.6476, -0.7391], [1.4314, -0.3522], [0.8401, -0.7757]], + [[1.4306, 0.9726], [1.0518, -0.8820], [-0.5129, -0.7876]]]]) + +shifts = [([[1, 0, 1, -2], [-2, 1, -1, 1]]), ([[2, 1, 2, -1], [-1, 2, 0, 2]])] + +outputs = [([[[[0.4369, -3.7571], [-1.1835, -1.6374], [0.9534, -0.1321]], + [[-0.4658, 0.2162], [-0.8135, -0.3903], [-0.1720, -0.0599]], + [[0.4851, 1.8224], [0.8973, 0.3779], [2.3454, 1.0319]], + [[0.0420, 0.3574], [0.7641, 0.2384], [0.2759, 0.4931]]], + [[[0.6476, -0.7391], [1.4314, -0.3522], [0.8401, -0.7757]], + [[1.4306, 0.9726], [1.0518, -0.8820], [-0.5129, -0.7876]], + [[0.0000, 0.0000], [0.0000, 0.0000], [0.0000, 0.0000]], + [[0.0000, 0.0000], [0.0000, 0.0000], [0.0000, 0.0000]]]]), + ([[[[0.4369, -3.7571], [-1.1835, -1.6374], [0.9534, -0.1321]], + [[-0.4658, 0.2162], [-0.8135, -0.3903], [-0.1720, -0.0599]], + [[0.4851, 1.8224], [0.8973, 0.3779], [2.3454, 1.0319]], + [[0.0420, 0.3574], [0.7641, 0.2384], [0.2759, 0.4931]]], + [[[-0.6766, -1.4657], [1.2362, 0.4913], [-1.1820, -1.4341]], + [[0.6476, -0.7391], [1.4314, -0.3522], [0.8401, -0.7757]], + [[1.4306, 0.9726], [1.0518, -0.8820], [-0.5129, -0.7876]], + [[0.0000, 0.0000], [0.0000, 0.0000], [0.0000, 0.0000]]]])] + +grads = [[[[[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]], + [[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]]], + [[[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]], + [[0., 0.], [0., 0.], [0., 0.]], [[0., 0.], [0., 0.], [0., 0.]]]], + [[[[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]], + [[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]]], + [[[1., 1.], [1., 1.], [1., 1.]], [[1., 1.], [1., 1.], [1., 1.]], + [[1., 1.], [1., 1.], [1., 1.]], [[0., 0.], [0., 0.], [0., 0.]]]]] + + +def _test_tinshift_gradcheck(dtype): + try: + from mmcv.ops import tin_shift + except ModuleNotFoundError: + pytest.skip('TinShift op is not successfully compiled') + + if dtype == torch.half: + pytest.skip('"add_cpu/sub_cpu" not implemented for Half') + + for shift in shifts: + np_input = np.array(inputs) + np_shift = np.array(shift) + + x = torch.tensor( + np_input, dtype=dtype, device='cuda', requires_grad=True) + shift = torch.tensor(np_shift, device='cuda').int() + if torch.__version__ == 'parrots': + gradcheck(tin_shift, (x, shift)) + else: + gradcheck(tin_shift, (x, shift), atol=1, rtol=0.1) + + +def _test_tinshift_allclose(dtype): + try: + from mmcv.ops import tin_shift + except ModuleNotFoundError: + pytest.skip('TinShift op is not successfully compiled') + + for shift, output, grad in zip(shifts, outputs, grads): + np_input = np.array(inputs) + np_shift = np.array(shift) + np_output = np.array(output) + np_grad = np.array(grad) + + x = torch.tensor( + np_input, dtype=dtype, device='cuda', requires_grad=True) + shift = torch.tensor(np_shift, device='cuda').int() + + output = tin_shift(x, shift) + output.backward(torch.ones_like(output)) + assert np.allclose( + output.data.type(torch.float).cpu().numpy(), np_output, 1e-3) + assert np.allclose( + x.grad.data.type(torch.float).cpu().numpy(), np_grad, 1e-3) + + +@pytest.mark.skipif( + not torch.cuda.is_available(), reason='requires CUDA support') +@pytest.mark.parametrize('dtype', [torch.float, torch.double, torch.half]) +def test_tinshift(dtype): + _test_tinshift_allclose(dtype=dtype) + _test_tinshift_gradcheck(dtype=dtype) From eacaf475f738381d96f897528a08a7396d06f80e Mon Sep 17 00:00:00 2001 From: Wang Xinjiang Date: Sun, 16 Aug 2020 01:20:08 +0800 Subject: [PATCH 18/81] fix some pavi logger hooks (#481) * fix some pavi logger hooks * fix unittest * fix small bugs * small change * fix unittest * Add EpochBasedRunner conditions * Add session text * fix small bug * fetch runner mode from log buffer * Add max_iter to pavi session text * change yaml.dump to yamp.dump(yaml.load(mmcv.dump)) * Directly use by_epoch * fix unittest * add comments * Use runner.epoch + 1 in pavi log * fix runner.epoch issue for runner.mode=='val' * fix runner.epoch issue for runner.mode=='val' * Use abspath instead of realpath * Add meta dump unittest * small change * Add comments --- mmcv/runner/hooks/logger/pavi.py | 39 +++++++++++++++++++++++++++----- tests/test_runner/test_hooks.py | 9 ++++---- 2 files changed, 38 insertions(+), 10 deletions(-) diff --git a/mmcv/runner/hooks/logger/pavi.py b/mmcv/runner/hooks/logger/pavi.py index 9eb7d21696..22c02a2b1c 100644 --- a/mmcv/runner/hooks/logger/pavi.py +++ b/mmcv/runner/hooks/logger/pavi.py @@ -1,10 +1,14 @@ # Copyright (c) Open-MMLab. All rights reserved. +import json import numbers +import os import os.path as osp import numpy as np import torch +import yaml +import mmcv from ...dist_utils import master_only from ..hook import HOOKS from .base import LoggerHook @@ -61,7 +65,16 @@ def before_run(self, runner): self.init_kwargs = dict() self.init_kwargs['task'] = self.run_name self.init_kwargs['model'] = runner._model_name - + if runner.meta is not None and 'config_dict' in runner.meta: + config_dict = runner.meta['config_dict'].copy() + # 'max_.*iter' is parsed in pavi sdk as the maximum iterations + # to properly set up the progress bar. + config_dict.setdefault('max_iter', runner.max_iters) + # non-serializable values are first converted in mmcv.dump to json + config_dict = json.loads( + mmcv.dump(config_dict, file_format='json')) + session_text = yaml.dump(config_dict) + self.init_kwargs['session_text'] = session_text self.writer = SummaryWriter(**self.init_kwargs) if self.add_graph: @@ -90,13 +103,27 @@ def log(self, runner): tags['momentum'] = momentums[0] if tags: - self.writer.add_scalars(runner.mode, tags, runner.iter) + if runner.mode == 'val': + mode = runner.mode + # runner.epoch += 1 has been done before val workflow + epoch = runner.epoch + else: + mode = 'train' if 'time' in runner.log_buffer.output else 'val' + epoch = runner.epoch + 1 + if mode == 'val' and self.by_epoch: + self.writer.add_scalars(mode, tags, epoch) + else: + self.writer.add_scalars(mode, tags, runner.iter) @master_only def after_run(self, runner): if self.add_last_ckpt: ckpt_path = osp.join(runner.work_dir, 'latest.pth') - self.writer.add_snapshot_file( - tag=self.run_name, - snapshot_file_path=ckpt_path, - iteration=runner.iter) + if osp.isfile(ckpt_path): + ckpt_path = osp.join(runner.work_dir, os.readlink(ckpt_path)) + # runner.epoch += 1 has been done before `after_run`. + iteration = runner.epoch if self.by_epoch else runner.iter + return self.writer.add_snapshot_file( + tag=self.run_name, + snapshot_file_path=ckpt_path, + iteration=iteration) diff --git a/tests/test_runner/test_hooks.py b/tests/test_runner/test_hooks.py index 000d86ff6e..a7f105a3fb 100644 --- a/tests/test_runner/test_hooks.py +++ b/tests/test_runner/test_hooks.py @@ -98,6 +98,7 @@ def test_pavi_hook(): loader = DataLoader(torch.ones((5, 2))) runner = _build_demo_runner() + runner.meta = dict(config_dict=dict(lr=0.02, gpu_ids=range(1))) hook = PaviLoggerHook(add_graph=False, add_last_ckpt=True) runner.register_hook(hook) runner.run([loader, loader], [('train', 1), ('val', 1)], 1) @@ -107,11 +108,11 @@ def test_pavi_hook(): hook.writer.add_scalars.assert_called_with('val', { 'learning_rate': 0.02, 'momentum': 0.95 - }, 5) + }, 1) hook.writer.add_snapshot_file.assert_called_with( tag=runner.work_dir.split('/')[-1], - snapshot_file_path=osp.join(runner.work_dir, 'latest.pth'), - iteration=5) + snapshot_file_path=osp.join(runner.work_dir, 'epoch_1.pth'), + iteration=1) def test_sync_buffers_hook(): @@ -378,6 +379,6 @@ def val_step(self, x, optimizer, **kwargs): work_dir=tmp_dir, optimizer=optimizer, logger=logging.getLogger()) - + runner.register_checkpoint_hook(dict(interval=1)) runner.register_logger_hooks(log_config) return runner From 7b18b97791167556643ed04ea8354f19c6306044 Mon Sep 17 00:00:00 2001 From: Cao Yuhang Date: Sun, 16 Aug 2020 01:45:01 +0800 Subject: [PATCH 19/81] fix saconv (#489) * fix saconv * add parrots condition * add unittest * fix torch version --- mmcv/ops/saconv.py | 11 +++++++-- tests/test_ops/test_saconv.py | 46 +++++++++++++++++++++++++++++++++++ 2 files changed, 55 insertions(+), 2 deletions(-) create mode 100644 tests/test_ops/test_saconv.py diff --git a/mmcv/ops/saconv.py b/mmcv/ops/saconv.py index 29ee6a7b79..cd7eea122f 100644 --- a/mmcv/ops/saconv.py +++ b/mmcv/ops/saconv.py @@ -4,6 +4,7 @@ from mmcv.cnn import CONV_LAYERS, ConvAWS2d, constant_init from mmcv.ops.deform_conv import deform_conv2d +from mmcv.utils import TORCH_VERSION @CONV_LAYERS.register_module(name='SAC') @@ -102,7 +103,10 @@ def forward(self, x): out_s = deform_conv2d(x, offset, weight, self.stride, self.padding, self.dilation, self.groups, 1) else: - out_s = super().conv2d_forward(x, weight) + if TORCH_VERSION < '1.5.0' or TORCH_VERSION == 'parrots': + out_s = super().conv2d_forward(x, weight) + else: + out_s = super()._conv_forward(x, weight) ori_p = self.padding ori_d = self.dilation self.padding = tuple(3 * p for p in self.padding) @@ -113,7 +117,10 @@ def forward(self, x): out_l = deform_conv2d(x, offset, weight, self.stride, self.padding, self.dilation, self.groups, 1) else: - out_l = super().conv2d_forward(x, weight) + if TORCH_VERSION < '1.5.0' or TORCH_VERSION == 'parrots': + out_l = super().conv2d_forward(x, weight) + else: + out_l = super()._conv_forward(x, weight) out = switch * out_s + (1 - switch) * out_l self.padding = ori_p self.dilation = ori_d diff --git a/tests/test_ops/test_saconv.py b/tests/test_ops/test_saconv.py new file mode 100644 index 0000000000..10fc2c5b72 --- /dev/null +++ b/tests/test_ops/test_saconv.py @@ -0,0 +1,46 @@ +import pytest +import torch +import torch.nn as nn + +from mmcv.ops import SAConv2d + + +def test_sacconv(): + + # test with normal cast + x = torch.rand(1, 3, 256, 256) + saconv = SAConv2d(3, 5, kernel_size=3, padding=1) + sac_out = saconv(x) + refer_conv = nn.Conv2d(3, 5, kernel_size=3, padding=1) + refer_out = refer_conv(x) + assert sac_out.shape == refer_out.shape + + # test with dilation >= 2 + dalited_saconv = SAConv2d(3, 5, kernel_size=3, padding=2, dilation=2) + dalited_sac_out = dalited_saconv(x) + refer_conv = nn.Conv2d(3, 5, kernel_size=3, padding=2, dilation=2) + refer_out = refer_conv(x) + assert dalited_sac_out.shape == refer_out.shape + + # test with deform + deform_saconv = SAConv2d(3, 5, kernel_size=3, padding=1, use_deform=True) + if torch.cuda.is_available(): + x = torch.rand(1, 3, 256, 256).cuda() + deform_saconv = SAConv2d( + 3, 5, kernel_size=3, padding=1, use_deform=True).cuda() + deform_sac_out = deform_saconv(x).cuda() + refer_conv = nn.Conv2d(3, 5, kernel_size=3, padding=1).cuda() + refer_out = refer_conv(x) + assert deform_sac_out.shape == refer_out.shape + else: + with pytest.raises(RuntimeError): + # deform conv is not implemented on cpu + deform_saconv(x) + + # test with groups >= 2 + x = torch.rand(1, 4, 256, 256) + group_saconv = SAConv2d(4, 4, kernel_size=3, padding=1, groups=2) + group_sac_out = group_saconv(x) + refer_conv = nn.Conv2d(4, 4, kernel_size=3, padding=1, groups=2) + refer_out = refer_conv(x) + assert group_sac_out.shape == refer_out.shape From 4ec73abbcc30314604d7afa6f59c1d6be5e8426c Mon Sep 17 00:00:00 2001 From: Jintao Lin Date: Mon, 17 Aug 2020 18:50:19 +0800 Subject: [PATCH 20/81] Logging mode by using runner.mode (#495) * log mode by using runner.mode * add IterTimerHook to fix unittest * correct the logic * display fix when using EvalHook in train mode * simplify logic --- mmcv/runner/hooks/logger/text.py | 33 ++++++++++++++++++-------------- 1 file changed, 19 insertions(+), 14 deletions(-) diff --git a/mmcv/runner/hooks/logger/text.py b/mmcv/runner/hooks/logger/text.py index a174c4e682..23a26f4b3a 100644 --- a/mmcv/runner/hooks/logger/text.py +++ b/mmcv/runner/hooks/logger/text.py @@ -68,7 +68,7 @@ def _log_info(self, log_dict, runner): exp_info = f'Exp name: {runner.meta["exp_name"]}' runner.logger.info(exp_info) - if runner.mode == 'train': + if log_dict['mode'] == 'train': if isinstance(log_dict['lr'], dict): lr_str = [] for k, val in log_dict['lr'].items(): @@ -101,7 +101,7 @@ def _log_info(self, log_dict, runner): else: if self.by_epoch: log_str = f'Epoch({log_dict["mode"]}) ' \ - f'[{log_dict["epoch"] - 1}][{log_dict["iter"]}]\t' + f'[{log_dict["epoch"]}][{log_dict["iter"]}]\t' else: log_str = f'Iter({log_dict["mode"]}) [{log_dict["iter"]}]\t' @@ -142,10 +142,20 @@ def _round_float(self, items): def log(self, runner): log_dict = OrderedDict() - # training mode if the output contains the key "time" - mode = 'train' if 'time' in runner.log_buffer.output else 'val' - log_dict['mode'] = mode - log_dict['epoch'] = runner.epoch + 1 + + if runner.mode == 'train': + log_dict['mode'] = 'train' if 'time' in runner.log_buffer.output \ + else 'val' + log_dict['epoch'] = runner.epoch + 1 + elif runner.mode == 'val': + # normal val mode + # runner.epoch += 1 has been done before val workflow + log_dict['mode'] = 'val' + log_dict['epoch'] = runner.epoch + else: + raise ValueError(f"runner mode should be 'train' or 'val', " + f'but got {runner.mode}') + if self.by_epoch: log_dict['iter'] = runner.inner_iter + 1 else: @@ -161,17 +171,12 @@ def log(self, runner): assert isinstance(lr_, list) log_dict['lr'].update({k: lr_[0]}) - if mode == 'train': - log_dict['time'] = runner.log_buffer.output['time'] - log_dict['data_time'] = runner.log_buffer.output['data_time'] - + if 'time' in runner.log_buffer.output: # statistic memory if torch.cuda.is_available(): log_dict['memory'] = self._get_max_memory(runner) - for name, val in runner.log_buffer.output.items(): - if name in ['time', 'data_time']: - continue - log_dict[name] = val + + log_dict = dict(log_dict, **runner.log_buffer.output) self._log_info(log_dict, runner) self._dump_log(log_dict, runner) From 7a6285b19078ce128c7e8c3d9bafd5bca3ed18b7 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Wed, 19 Aug 2020 14:22:40 +0800 Subject: [PATCH 21/81] Fix mmcv-dataparallel (#497) * Fix mmcv-dataparallel * Fix (parallel): fix CPU inference with MMDataParallel * Update docstrings * Doc (parallel): refine docstrings * Fix (parallel): fix missing changes of train/val step function * resolve comments * Fix (data_parallel): fix bug when single gpu test return None --- mmcv/parallel/_functions.py | 11 +++++++--- mmcv/parallel/data_parallel.py | 39 +++++++++++++++++++++++++++++++++ mmcv/parallel/scatter_gather.py | 6 ++++- 3 files changed, 52 insertions(+), 4 deletions(-) diff --git a/mmcv/parallel/_functions.py b/mmcv/parallel/_functions.py index ea5cbb6a23..4cd02fbe67 100644 --- a/mmcv/parallel/_functions.py +++ b/mmcv/parallel/_functions.py @@ -19,8 +19,13 @@ def scatter(input, devices, streams=None): output = input.contiguous() # TODO: copy to a pinned buffer first (if copying from CPU) stream = streams[0] if output.numel() > 0 else None - with torch.cuda.device(devices[0]), torch.cuda.stream(stream): - output = output.cuda(devices[0], non_blocking=True) + if devices != [-1]: + with torch.cuda.device(devices[0]), torch.cuda.stream(stream): + output = output.cuda(devices[0], non_blocking=True) + else: + # unsquzee the first dimension thus the tensor's shape is the + # same as those scattered with GPU. + output = output.unsqueeze(0) return output else: raise Exception(f'Unknown type {type(input)}.') @@ -62,7 +67,7 @@ class Scatter: def forward(target_gpus, input): input_device = get_input_device(input) streams = None - if input_device == -1: + if input_device == -1 and target_gpus != [-1]: # Perform CPU to GPU copies in a background stream streams = [_get_stream(device) for device in target_gpus] diff --git a/mmcv/parallel/data_parallel.py b/mmcv/parallel/data_parallel.py index c397c4388a..4b05b443b9 100644 --- a/mmcv/parallel/data_parallel.py +++ b/mmcv/parallel/data_parallel.py @@ -7,12 +7,48 @@ class MMDataParallel(DataParallel): + """The DataParallel module that supports DataContainer. + + MMDataParallel has two main differences with PyTorch DataParallel: + + - It supports a custom type :class:`DataContainer` which allows more + flexible control of input data during both GPU and CPU inference. + - It implement two more APIs ``train_step()`` and ``val_step()``. + + Args: + module (:class:`nn.Module`): Module to be encapsulated. + device_ids (list[int]): Device IDS of modules to be scattered to. + Defaults to None when GPU is not available. + output_device (str | int): Device ID for output. Defaults to None. + dim (int): Dimension used to scatter the data. Defaults to 0. + """ + + def __init__(self, *args, dim=0, **kwargs): + super(MMDataParallel, self).__init__(*args, dim=dim, **kwargs) + self.dim = dim + + def forward(self, *inputs, **kwargs): + """Override the original forward function. + + The main difference lies in the CPU inference where the datas in + :class:`DataContainers` will still be gathered. + """ + if not self.device_ids: + # We add the following line thus the module could gather and + # convert data containers as those in GPU inference + inputs, kwargs = self.scatter(inputs, kwargs, [-1]) + return self.module(*inputs[0], **kwargs[0]) + else: + return super().forward(*inputs, **kwargs) def scatter(self, inputs, kwargs, device_ids): return scatter_kwargs(inputs, kwargs, device_ids, dim=self.dim) def train_step(self, *inputs, **kwargs): if not self.device_ids: + # We add the following line thus the module could gather and + # convert data containers as those in GPU inference + inputs, kwargs = self.scatter(inputs, kwargs, [-1]) return self.module.train_step(*inputs, **kwargs) assert len(self.device_ids) == 1, \ @@ -32,6 +68,9 @@ def train_step(self, *inputs, **kwargs): def val_step(self, *inputs, **kwargs): if not self.device_ids: + # We add the following line thus the module could gather and + # convert data containers as those in GPU inference + inputs, kwargs = self.scatter(inputs, kwargs, [-1]) return self.module.val_step(*inputs, **kwargs) assert len(self.device_ids) == 1, \ diff --git a/mmcv/parallel/scatter_gather.py b/mmcv/parallel/scatter_gather.py index c45fb1643c..78dba14ebb 100644 --- a/mmcv/parallel/scatter_gather.py +++ b/mmcv/parallel/scatter_gather.py @@ -15,7 +15,11 @@ def scatter(inputs, target_gpus, dim=0): def scatter_map(obj): if isinstance(obj, torch.Tensor): - return OrigScatter.apply(target_gpus, None, dim, obj) + if target_gpus != [-1]: + return OrigScatter.apply(target_gpus, None, dim, obj) + else: + # for CPU inference we use self-implemented scatter + return Scatter.forward(target_gpus, obj) if isinstance(obj, DataContainer): if obj.cpu_only: return obj.data From eb65c21da219e79d2fbc27dd056e94991b8718a8 Mon Sep 17 00:00:00 2001 From: su Date: Wed, 19 Aug 2020 16:13:20 +0800 Subject: [PATCH 22/81] Fix issue#505 (#506) --- mmcv/runner/base_runner.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/mmcv/runner/base_runner.py b/mmcv/runner/base_runner.py index 912d84bd27..c8a5513bf2 100644 --- a/mmcv/runner/base_runner.py +++ b/mmcv/runner/base_runner.py @@ -386,6 +386,8 @@ def register_checkpoint_hook(self, checkpoint_config): self.register_hook(hook) def register_logger_hooks(self, log_config): + if log_config is None: + return log_interval = log_config['interval'] for info in log_config['hooks']: logger_hook = mmcv.build_from_cfg( From 6159dac24c884e77e89f0502ad05e49755c58dd3 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Wed, 19 Aug 2020 18:29:49 +0800 Subject: [PATCH 23/81] Update darknet url (#507) --- mmcv/model_zoo/open_mmlab.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/model_zoo/open_mmlab.json b/mmcv/model_zoo/open_mmlab.json index 2acc3f3383..fd79ce9a35 100644 --- a/mmcv/model_zoo/open_mmlab.json +++ b/mmcv/model_zoo/open_mmlab.json @@ -42,5 +42,5 @@ "resnest50": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest50_d2-7497a55b.pth", "resnest101": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest101_d2-f3b931b2.pth", "resnest200": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest200_d2-ca88e41f.pth", - "darknet53": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/darknet53-7aecc596.pth" + "darknet53": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/darknet53-a628ea1b.pth" } From 5e3f56f8a6b1b4eb0b71ea61cb3600e557e7adda Mon Sep 17 00:00:00 2001 From: ychan <31604046+hanyc0914@users.noreply.github.com> Date: Wed, 19 Aug 2020 23:58:14 +0800 Subject: [PATCH 24/81] fix mdconv addmm bug for parrots (#450) * fix mdconv addmm bug for parrots * fix mdconv ctv save tensor Co-authored-by: hanyachao --- .../parrots/modulated_deform_conv_cuda.cu | 28 +++++++++++++------ mmcv/ops/csrc/parrots_cuda_helper.hpp | 1 + mmcv/ops/modulated_deform_conv.py | 4 +-- 3 files changed, 22 insertions(+), 11 deletions(-) diff --git a/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu b/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu index ea58eeea0c..3e8c096edc 100644 --- a/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu +++ b/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu @@ -219,14 +219,26 @@ void ModulatedDeformConvBackwardCUDAKernelLauncher( weight.dim(2), weight.dim(3)}); for (size_t g = 0; g < group; g++) { - auto columns_g = columns[g]; - gemm(ctx, 1, true, - weight[g].view( - {weight.dim(1), weight.dim(2) * weight.dim(3) * weight.dim(4)}), - false, - grad_output[b][g].view( - {grad_output.dim(2), grad_output.dim(3) * grad_output.dim(4)}), - 0, columns_g); + auto columns_g = ctx.createDArrayLite( + weight.elemType(), DArrayShape(columns.dim(1), columns.dim(2))); + copy(ctx, columns_g, columns[g]); + auto weight_g = weight[g].view( + {weight.dim(1), weight.dim(2) * weight.dim(3) * weight.dim(4)}); + weight_g = transpose(ctx, weight_g, 0, 1); + + auto grad_output_bg = ctx.createDArrayLite( + grad_output.elemType(), + DArrayShape(grad_output.dim(2), grad_output.dim(3), + grad_output.dim(4))); + copy(ctx, grad_output_bg, grad_output[b][g]); + grad_output_bg = + grad_output_bg.view({grad_output_bg.dim(0), + grad_output_bg.dim(1) * grad_output_bg.dim(2)}); + + columns_g = + parrots::op::addmm(ctx, columns[g], weight_g, grad_output_bg, 0, 1); + auto columns_out = columns[g]; + copy(ctx, columns_out, columns_g); } columns = columns.view({columns.dim(0) * columns.dim(1), columns.dim(2)}); diff --git a/mmcv/ops/csrc/parrots_cuda_helper.hpp b/mmcv/ops/csrc/parrots_cuda_helper.hpp index d732e3a526..539009c3f9 100644 --- a/mmcv/ops/csrc/parrots_cuda_helper.hpp +++ b/mmcv/ops/csrc/parrots_cuda_helper.hpp @@ -5,6 +5,7 @@ #include #include +#include #include #include #include diff --git a/mmcv/ops/modulated_deform_conv.py b/mmcv/ops/modulated_deform_conv.py index be90f9f2a4..1770b65798 100644 --- a/mmcv/ops/modulated_deform_conv.py +++ b/mmcv/ops/modulated_deform_conv.py @@ -57,9 +57,7 @@ def forward(ctx, ctx.with_bias = bias is not None if not ctx.with_bias: bias = input.new_empty(0) # fake tensor - if weight.requires_grad or mask.requires_grad or offset.requires_grad \ - or input.requires_grad: - ctx.save_for_backward(input, offset, mask, weight, bias) + ctx.save_for_backward(input, offset, mask, weight, bias) output = input.new_empty( ModulatedDeformConv2dFunction._output_size(ctx, input, weight)) ctx._bufs = [input.new_empty(0), input.new_empty(0)] From 11d8dd533d56f4b3fa6dd4c22b22cd3cf2555388 Mon Sep 17 00:00:00 2001 From: robin Han Date: Thu, 20 Aug 2020 00:43:35 +0800 Subject: [PATCH 25/81] support ONNX adaptive average pooling (#504) * support ONNX adaptive average pooling * fix double quotes Co-authored-by: Kai Chen --- mmcv/onnx/symbolic.py | 47 +++++++++++++++++++++++++++++ mmcv/ops/csrc/parrots/tin_shift.cpp | 2 +- 2 files changed, 48 insertions(+), 1 deletion(-) diff --git a/mmcv/onnx/symbolic.py b/mmcv/onnx/symbolic.py index 5dee10c6e0..4a301b7274 100644 --- a/mmcv/onnx/symbolic.py +++ b/mmcv/onnx/symbolic.py @@ -305,6 +305,50 @@ def softmax(g, input, dim, dtype=None): return softmax +def _adaptive_pool(name, type, tuple_fn, fn=None): + + @parse_args('v', 'is') + def symbolic_fn(g, input, output_size): + if output_size == [1] * len(output_size) and type == 'AveragePool': + return g.op('GlobalAveragePool', input) + if not input.isCompleteTensor(): + if output_size == [1] * len(output_size): + return g.op('GlobalMaxPool', input), None + raise NotImplementedError( + '[Adaptive pool]:input size not accessible') + dim = input.type().sizes()[2:] + if output_size == [1] * len(output_size) and type == 'MaxPool': + return g.op('GlobalMaxPool', input), None + + # compute stride = floor(input_size / output_size) + s = [int(dim[i] / output_size[i]) for i in range(0, len(dim))] + + # compute kernel_size = input_size - (output_size - 1) * stride + k = [dim[i] - (output_size[i] - 1) * s[i] for i in range(0, len(dim))] + + # call max_poolxd_with_indices to get indices in the output + if type == 'MaxPool': + return fn(g, input, k, k, (0, ) * len(dim), (1, ) * len(dim), + False) + output = g.op( + type, + input, + kernel_shape_i=tuple_fn(k), + strides_i=tuple_fn(s), + ceil_mode_i=False) + return output + + return symbolic_fn + + +adaptive_avg_pool1d = _adaptive_pool('adaptive_avg_pool1d', 'AveragePool', + _single) +adaptive_avg_pool2d = _adaptive_pool('adaptive_avg_pool2d', 'AveragePool', + _pair) +adaptive_avg_pool3d = _adaptive_pool('adaptive_avg_pool3d', 'AveragePool', + _triple) + + def register_extra_symbolics(opset=11): register_op('one_hot', one_hot, '', opset) register_op('im2col', im2col, '', opset) @@ -317,6 +361,9 @@ def register_extra_symbolics(opset=11): register_op('avg_pool1d', avg_pool1d, '', opset) register_op('avg_pool2d', avg_pool2d, '', opset) register_op('avg_pool3d', avg_pool3d, '', opset) + register_op('adaptive_avg_pool1d', adaptive_avg_pool1d, '', opset) + register_op('adaptive_avg_pool2d', adaptive_avg_pool2d, '', opset) + register_op('adaptive_avg_pool3d', adaptive_avg_pool3d, '', opset) register_op('masked_select', masked_select, '', opset) register_op('upsample_nearest1d', upsample_nearest1d, '', opset) register_op('upsample_nearest2d', upsample_nearest2d, '', opset) diff --git a/mmcv/ops/csrc/parrots/tin_shift.cpp b/mmcv/ops/csrc/parrots/tin_shift.cpp index a31444bfdd..17b48af41c 100644 --- a/mmcv/ops/csrc/parrots/tin_shift.cpp +++ b/mmcv/ops/csrc/parrots/tin_shift.cpp @@ -39,4 +39,4 @@ PARROTS_EXTENSION_REGISTER(tin_shift_backward) .input(2) .output(1) .apply(tin_shift_backward_cuda) - .done(); \ No newline at end of file + .done(); From 77c03f44b8d8b903c9c713cbdcb00782f606a37f Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Thu, 20 Aug 2020 01:05:28 +0800 Subject: [PATCH 26/81] bump version to 1.1.0 (#508) --- mmcv/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/version.py b/mmcv/version.py index 9a2c0d8a88..7c2c24932d 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,2 +1,2 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.0.5' +__version__ = '1.1.0' From 95a9728c42c94371c247d48651b5ca95d2535143 Mon Sep 17 00:00:00 2001 From: Kevin Date: Fri, 21 Aug 2020 13:06:00 +0800 Subject: [PATCH 27/81] Support pickle.loads (#499) (#500) --- mmcv/utils/config.py | 9 +++++++++ tests/test_config.py | 14 +++++++++++++- 2 files changed, 22 insertions(+), 1 deletion(-) diff --git a/mmcv/utils/config.py b/mmcv/utils/config.py index 70da0df968..be1b4daede 100644 --- a/mmcv/utils/config.py +++ b/mmcv/utils/config.py @@ -372,6 +372,15 @@ def __setitem__(self, name, value): def __iter__(self): return iter(self._cfg_dict) + def __getstate__(self): + return (self._cfg_dict, self._filename, self._text) + + def __setstate__(self, state): + _cfg_dict, _filename, _text = state + super(Config, self).__setattr__('_cfg_dict', _cfg_dict) + super(Config, self).__setattr__('_filename', _filename) + super(Config, self).__setattr__('_text', _text) + def dump(self, file=None): cfg_dict = super(Config, self).__getattribute__('_cfg_dict').to_dict() if self.filename.endswith('.py'): diff --git a/tests/test_config.py b/tests/test_config.py index 7ca0bf7e39..432c4fab73 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -7,7 +7,7 @@ import pytest import yaml -from mmcv import Config, DictAction +from mmcv import Config, DictAction, dump, load def test_construct(): @@ -354,3 +354,15 @@ def test_syntax_error(): f'file {temp_cfg_path}'): Config.fromfile(temp_cfg_path) temp_cfg_file.close() + + +def test_pickle_support(): + cfg_file = osp.join(osp.dirname(__file__), 'data/config/n.py') + cfg = Config.fromfile(cfg_file) + + with tempfile.TemporaryDirectory() as temp_config_dir: + pkl_cfg_filename = osp.join(temp_config_dir, '_pickle.pkl') + dump(cfg, pkl_cfg_filename) + pkl_cfg = load(pkl_cfg_filename) + + assert pkl_cfg._cfg_dict == cfg._cfg_dict From 5e7f785364243d4292c517e0bad2e84bb9ced0d1 Mon Sep 17 00:00:00 2001 From: John Zhu <31381602+johnzja@users.noreply.github.com> Date: Fri, 21 Aug 2020 14:04:42 +0800 Subject: [PATCH 28/81] fix regex bugs in Widows paths (#513) --- mmcv/utils/config.py | 1 + 1 file changed, 1 insertion(+) diff --git a/mmcv/utils/config.py b/mmcv/utils/config.py index be1b4daede..1d95d46dd9 100644 --- a/mmcv/utils/config.py +++ b/mmcv/utils/config.py @@ -111,6 +111,7 @@ def _substitute_predefined_vars(filename, temp_config_name): config_file = f.read() for key, value in support_templates.items(): regexp = r'\{\{\s*' + str(key) + r'\s*\}\}' + value = value.replace('\\', '/') config_file = re.sub(regexp, value, config_file) with open(temp_config_name, 'w') as tmp_config_file: tmp_config_file.write(config_file) From eb0414f495c798fcaae73fb851b83f2b1d804be3 Mon Sep 17 00:00:00 2001 From: Matthew Dawkins Date: Sat, 22 Aug 2020 02:24:16 -0400 Subject: [PATCH 29/81] Fix windows compile issues (#510) --- mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh b/mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh index 9d44e9ee92..c8ff05b840 100644 --- a/mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh +++ b/mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh @@ -59,8 +59,8 @@ __global__ void softmax_focal_loss_backward_cuda2_kernel( int c = index % num_classes; int64_t label = target[n]; - T flag = (label == c) * (T)1.; if (label >= 0) { + T flag = (label == c ? (T)1. : (T)0.); grad_input[index] = buff[n] * (flag - softmax[index]); } else { grad_input[index] = 0; From 83d9a9c89b5467a00c4976fd60a75d0b9412110a Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Sat, 22 Aug 2020 14:29:27 +0800 Subject: [PATCH 30/81] [Feature] Add diagonal flip (#515) --- mmcv/image/geometric.py | 18 +++++++---- tests/test_image/test_geometric.py | 49 ++++++++++++++++++++++++++++++ 2 files changed, 61 insertions(+), 6 deletions(-) diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index 3bebde90a9..42afc8cbca 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -187,16 +187,19 @@ def imflip(img, direction='horizontal'): Args: img (ndarray): Image to be flipped. - direction (str): The flip direction, either "horizontal" or "vertical". + direction (str): The flip direction, either "horizontal" or + "vertical" or "diagonal". Returns: ndarray: The flipped image. """ - assert direction in ['horizontal', 'vertical'] + assert direction in ['horizontal', 'vertical', 'diagonal'] if direction == 'horizontal': return np.flip(img, axis=1) - else: + elif direction == 'vertical': return np.flip(img, axis=0) + else: + return np.flip(img, axis=(0, 1)) def imflip_(img, direction='horizontal'): @@ -204,16 +207,19 @@ def imflip_(img, direction='horizontal'): Args: img (ndarray): Image to be flipped. - direction (str): The flip direction, either "horizontal" or "vertical". + direction (str): The flip direction, either "horizontal" or + "vertical" or "diagonal". Returns: ndarray: The flipped image (inplace). """ - assert direction in ['horizontal', 'vertical'] + assert direction in ['horizontal', 'vertical', 'diagonal'] if direction == 'horizontal': return cv2.flip(img, 1, img) - else: + elif direction == 'vertical': return cv2.flip(img, 0, img) + else: + return cv2.flip(img, -1, img) def imrotate(img, diff --git a/tests/test_image/test_geometric.py b/tests/test_image/test_geometric.py index 12dbd7a73a..9a1c9b1c86 100644 --- a/tests/test_image/test_geometric.py +++ b/tests/test_image/test_geometric.py @@ -108,6 +108,10 @@ def test_imrescale(self): mmcv.imrescale(self.img, [100, 100]) def test_imflip(self): + # direction must be "horizontal" or "vertical" or "diagonal" + with pytest.raises(AssertionError): + mmcv.imflip(np.random.rand(80, 60, 3), direction='random') + # test horizontal flip (color image) img = np.random.rand(80, 60, 3) h, w, c = img.shape @@ -117,6 +121,7 @@ def test_imflip(self): for j in range(w): for k in range(c): assert flipped_img[i, j, k] == img[i, w - 1 - j, k] + # test vertical flip (color image) flipped_img = mmcv.imflip(img, direction='vertical') assert flipped_img.shape == img.shape @@ -124,6 +129,15 @@ def test_imflip(self): for j in range(w): for k in range(c): assert flipped_img[i, j, k] == img[h - 1 - i, j, k] + + # test diagonal flip (color image) + flipped_img = mmcv.imflip(img, direction='diagonal') + assert flipped_img.shape == img.shape + for i in range(h): + for j in range(w): + for k in range(c): + assert flipped_img[i, j, k] == img[h - 1 - i, w - 1 - j, k] + # test horizontal flip (grayscale image) img = np.random.rand(80, 60) h, w = img.shape @@ -132,6 +146,7 @@ def test_imflip(self): for i in range(h): for j in range(w): assert flipped_img[i, j] == img[i, w - 1 - j] + # test vertical flip (grayscale image) flipped_img = mmcv.imflip(img, direction='vertical') assert flipped_img.shape == img.shape @@ -139,7 +154,18 @@ def test_imflip(self): for j in range(w): assert flipped_img[i, j] == img[h - 1 - i, j] + # test diagonal flip (grayscale image) + flipped_img = mmcv.imflip(img, direction='diagonal') + assert flipped_img.shape == img.shape + for i in range(h): + for j in range(w): + assert flipped_img[i, j] == img[h - 1 - i, w - 1 - j] + def test_imflip_(self): + # direction must be "horizontal" or "vertical" or "diagonal" + with pytest.raises(AssertionError): + mmcv.imflip_(np.random.rand(80, 60, 3), direction='random') + # test horizontal flip (color image) img = np.random.rand(80, 60, 3) h, w, c = img.shape @@ -166,6 +192,18 @@ def test_imflip_(self): assert flipped_img[i, j, k] == img[h - 1 - i, j, k] assert flipped_img[i, j, k] == img_for_flip[i, j, k] + # test diagonal flip (color image) + img_for_flip = img.copy() + flipped_img = mmcv.imflip_(img_for_flip, direction='diagonal') + assert flipped_img.shape == img.shape + assert flipped_img.shape == img_for_flip.shape + assert id(flipped_img) == id(img_for_flip) + for i in range(h): + for j in range(w): + for k in range(c): + assert flipped_img[i, j, k] == img[h - 1 - i, w - 1 - j, k] + assert flipped_img[i, j, k] == img_for_flip[i, j, k] + # test horizontal flip (grayscale image) img = np.random.rand(80, 60) h, w = img.shape @@ -190,6 +228,17 @@ def test_imflip_(self): assert flipped_img[i, j] == img[h - 1 - i, j] assert flipped_img[i, j] == img_for_flip[i, j] + # test diagonal flip (grayscale image) + img_for_flip = img.copy() + flipped_img = mmcv.imflip_(img_for_flip, direction='diagonal') + assert flipped_img.shape == img.shape + assert flipped_img.shape == img_for_flip.shape + assert id(flipped_img) == id(img_for_flip) + for i in range(h): + for j in range(w): + assert flipped_img[i, j] == img[h - 1 - i, w - 1 - j] + assert flipped_img[i, j] == img_for_flip[i, j] + def test_imcrop(self): # yapf: disable bboxes = np.array([[100, 100, 199, 199], # center From f4a5446e152b221422aa074e9055d157f2cbe481 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Mon, 24 Aug 2020 00:32:39 +0800 Subject: [PATCH 31/81] Support to split batched_nms when box number is too large (#516) * Support to split batched_nms when box number is too large * mv data from gpu to cpu * Set split_thr through nms_cfg * clean code * Update motivation in docstring * fix typos --- mmcv/ops/nms.py | 33 ++++++++++++++++++++++++++++---- tests/data/batched_nms_data.pkl | Bin 0 -> 38896 bytes tests/test_ops/test_nms.py | 25 ++++++++++++++++++++++++ 3 files changed, 54 insertions(+), 4 deletions(-) create mode 100644 tests/data/batched_nms_data.pkl diff --git a/mmcv/ops/nms.py b/mmcv/ops/nms.py index 3eade44db0..e982b1472a 100644 --- a/mmcv/ops/nms.py +++ b/mmcv/ops/nms.py @@ -223,9 +223,18 @@ def batched_nms(boxes, scores, idxs, nms_cfg, class_agnostic=False): and NMS will not be applied between elements of different idxs, shape (N, ). nms_cfg (dict): specify nms type and other parameters like iou_thr. + Possible keys includes the following. + + - iou_thr (float): IoU threshold used for NMS. + - split_thr (float): threshold number of boxes. In some cases the + number of boxes is large (e.g., 200k). To avoid OOM during + training, the users could set `split_thr` to a small value. + If the number of boxes is greater than the threshold, it will + perform NMS on each group of boxes separately and sequentially. + Defaults to 10000. class_agnostic (bool): if true, nms is class agnostic, i.e. IoU thresholding happens over all boxes, - regardless of the predicted class + regardless of the predicted class. Returns: tuple: kept dets and indice. @@ -238,11 +247,27 @@ def batched_nms(boxes, scores, idxs, nms_cfg, class_agnostic=False): max_coordinate = boxes.max() offsets = idxs.to(boxes) * (max_coordinate + 1) boxes_for_nms = boxes + offsets[:, None] + nms_type = nms_cfg_.pop('type', 'nms') nms_op = eval(nms_type) - dets, keep = nms_op(boxes_for_nms, scores, **nms_cfg_) - boxes = boxes[keep] - scores = dets[:, -1] + + split_thr = nms_cfg_.pop('split_thr', 10000) + if len(boxes_for_nms) < split_thr: + dets, keep = nms_op(boxes_for_nms, scores, **nms_cfg_) + boxes = boxes[keep] + scores = dets[:, -1] + else: + total_mask = scores.new_zeros(scores.size(), dtype=torch.bool) + for id in torch.unique(idxs): + mask = (idxs == id).nonzero(as_tuple=False).view(-1) + dets, keep = nms_op(boxes_for_nms[mask], scores[mask], **nms_cfg_) + total_mask[mask[keep]] = True + + keep = total_mask.nonzero(as_tuple=False).view(-1) + keep = keep[scores[keep].argsort(descending=True)] + boxes = boxes[keep] + scores = scores[keep] + return torch.cat([boxes, scores[:, None]], -1), keep diff --git a/tests/data/batched_nms_data.pkl b/tests/data/batched_nms_data.pkl new file mode 100644 index 0000000000000000000000000000000000000000..a28aeb6a06eadd69d2432e3fe0e2775f01643089 GIT binary patch literal 38896 zcmdS>XIE9h(gg}5!GMT>ihwAJiijvd5k#e7b*q>aQBlcBKoE%nl5@^UauSdvl0k$q zs{YuWYvVc3dB=F~54e6RP+hxG2NOHO$P&$S5{FFCi;qUtD&2W?a&> zsGRKN)GYI;%!JsS6uZv-sTy`uK&)-!l^MI6U?Jh(_`YJ5;N1&qGI#2 z6SB-ROyZ*A(&H22vdj}c>mSTBOvA!n7#UHiG1Z%=@-_|J=gqSzH2uQ<8U~;8PZRxr z!(^;5nJ<~?+39iVsZqHJnOVu{pELI9r-U8BpHh>vvr`kI5IHD>G!JBo9>Zg_g$^zrlZ@$tIpbIUtp@6K^waxzSwa;N39 z>%)>o8%2g8j{gmO0$xBd64GifdFciv_VxgC`~Xj zE3JYt%)cbYbM0wZ-sN_hk(oR|3o?kd64c3Jn$k|bOIBZa>ViDLKcW;*=Fxyg6}%j) zXwcSOW<8>I>GJ?jd+v^_xxa)KWn6@v;z3(n?Zd67mD@2Z$SDBd%&j!2g+9de7Q(K`7}}&}$s<0va~usrjEU5$ zPjdaLgM3AmN3gW;8`X#xW|3aYDnL`7T)^6*6nef2_c#hgiB<<4DeOVkqjgnTa zze#G(jaJn7o`yAUq^dZ@e|hVOEDFGA{bTCWxXdF?m4w^NOHp5xF(&y_;}-7ER=gW? 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ze~>%_iKH!q{wM`qG-b3epoURy8O_p7RX3d&&z50o-%`b}wC^Zk{8`4?Cg#^qlaC|} zEc=O)FCg4A3V`$9fPuh~z)`@_z%jt_zzM*Kz{x;)3lc;@4aihrFfar-4LBV*1GoVg z3Je2=1GfUDhvYFy3rR0XEHIIZ*C6XCXeD_{@&?3R;9r!}=S>z?x{G{nj4sM89A4=z V_AkmU8CsNETHr48xv_;y{sAsBRpS5v literal 0 HcmV?d00001 diff --git a/tests/test_ops/test_nms.py b/tests/test_ops/test_nms.py index 88e29f7e87..634469fff8 100644 --- a/tests/test_ops/test_nms.py +++ b/tests/test_ops/test_nms.py @@ -132,3 +132,28 @@ def test_nms_match(self): wrong_dets = np.zeros((2, 3)) with pytest.raises(AssertionError): nms_match(wrong_dets, iou_thr) + + def test_batched_nms(self): + import mmcv + from mmcv.ops import batched_nms + results = mmcv.load('./tests/data/batched_nms_data.pkl') + + nms_cfg = dict(type='nms', iou_threshold=0.7) + boxes, keep = batched_nms( + results['boxes'], + results['scores'], + results['idxs'], + nms_cfg, + class_agnostic=False) + + nms_cfg.update(split_thr=100) + seq_boxes, seq_keep = batched_nms( + results['boxes'], + results['scores'], + results['idxs'], + nms_cfg, + class_agnostic=False) + + assert torch.equal(keep, seq_keep) + assert torch.equal(boxes, seq_boxes) + assert torch.equal(keep, results['keep']) From aebdcb66611a8a5e2c186476f3c398809d105593 Mon Sep 17 00:00:00 2001 From: Matthew Dawkins Date: Mon, 24 Aug 2020 00:46:04 -0400 Subject: [PATCH 32/81] Fix inconsistent return types in pybind11 function prototypes (#509) * Fix function types * Remove const --- mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu | 14 +-- mmcv/ops/csrc/pytorch/pybind.cpp | 139 ++++++++++----------- 2 files changed, 75 insertions(+), 78 deletions(-) diff --git a/mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu b/mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu index b9529c70b5..ffc05c8fa5 100644 --- a/mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu +++ b/mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu @@ -1,11 +1,11 @@ #include "carafe_naive_cuda_kernel.cuh" #include "pytorch_cuda_helper.hpp" -int CARAFENAIVEForwardCUDAKernelLauncher(const Tensor features, - const Tensor masks, Tensor output, - const int kernel_size, - const int group_size, - const int scale_factor) { +void CARAFENAIVEForwardCUDAKernelLauncher(const Tensor features, + const Tensor masks, Tensor output, + const int kernel_size, + const int group_size, + const int scale_factor) { int output_size = output.numel(); int channels = output.size(1); int height = output.size(2); @@ -23,10 +23,9 @@ int CARAFENAIVEForwardCUDAKernelLauncher(const Tensor features, })); AT_CUDA_CHECK(cudaGetLastError()); - return 0; } -int CARAFENAIVEBackwardCUDAKernelLauncher( +void CARAFENAIVEBackwardCUDAKernelLauncher( const Tensor top_grad, const Tensor features, const Tensor masks, Tensor bottom_grad, Tensor mask_grad, const int kernel_size, const int group_size, const int scale_factor) { @@ -49,5 +48,4 @@ int CARAFENAIVEBackwardCUDAKernelLauncher( })); AT_CUDA_CHECK(cudaGetLastError()); - return 0; } diff --git a/mmcv/ops/csrc/pytorch/pybind.cpp b/mmcv/ops/csrc/pytorch/pybind.cpp index a2224fdb3d..abf5dedf1c 100644 --- a/mmcv/ops/csrc/pytorch/pybind.cpp +++ b/mmcv/ops/csrc/pytorch/pybind.cpp @@ -3,43 +3,43 @@ std::string get_compiler_version(); std::string get_compiling_cuda_version(); -int carafe_naive_forward(Tensor features, Tensor masks, Tensor output, - int kernel_size, int group_size, int scale_factor); - -int carafe_naive_backward(Tensor top_grad, Tensor features, Tensor masks, - Tensor bottom_grad, Tensor mask_grad, int kernel_size, - int group_size, int scale_factor); - -int carafe_forward(Tensor features, Tensor masks, Tensor rfeatures, - Tensor routput, Tensor rmasks, Tensor output, - int kernel_size, int group_size, int scale_factor); - -int carafe_backward(Tensor top_grad, Tensor rfeatures, Tensor masks, - Tensor rtop_grad, Tensor rbottom_grad_hs, - Tensor rbottom_grad, Tensor rmask_grad, Tensor bottom_grad, - Tensor mask_grad, int kernel_size, int group_size, - int scale_factor); - -int deform_conv_forward(Tensor input, Tensor weight, Tensor offset, - Tensor output, Tensor columns, Tensor ones, int kW, - int kH, int dW, int dH, int padW, int padH, - int dilationW, int dilationH, int group, - int deformable_group, int im2col_step); - -int deform_conv_backward_input(Tensor input, Tensor offset, Tensor gradOutput, - Tensor gradInput, Tensor gradOffset, - Tensor weight, Tensor columns, int kW, int kH, - int dW, int dH, int padW, int padH, - int dilationW, int dilationH, int group, - int deformable_group, int im2col_step); - -int deform_conv_backward_parameters(Tensor input, Tensor offset, - Tensor gradOutput, Tensor gradWeight, - Tensor columns, Tensor ones, int kW, int kH, - int dW, int dH, int padW, int padH, - int dilationW, int dilationH, int group, - int deformable_group, float scale, - int im2col_step); +void carafe_naive_forward(Tensor features, Tensor masks, Tensor output, + int kernel_size, int group_size, int scale_factor); + +void carafe_naive_backward(Tensor top_grad, Tensor features, Tensor masks, + Tensor bottom_grad, Tensor mask_grad, + int kernel_size, int group_size, int scale_factor); + +void carafe_forward(Tensor features, Tensor masks, Tensor rfeatures, + Tensor routput, Tensor rmasks, Tensor output, + int kernel_size, int group_size, int scale_factor); + +void carafe_backward(Tensor top_grad, Tensor rfeatures, Tensor masks, + Tensor rtop_grad, Tensor rbottom_grad_hs, + Tensor rbottom_grad, Tensor rmask_grad, Tensor bottom_grad, + Tensor mask_grad, int kernel_size, int group_size, + int scale_factor); + +void deform_conv_forward(Tensor input, Tensor weight, Tensor offset, + Tensor output, Tensor columns, Tensor ones, int kW, + int kH, int dW, int dH, int padW, int padH, + int dilationW, int dilationH, int group, + int deformable_group, int im2col_step); + +void deform_conv_backward_input(Tensor input, Tensor offset, Tensor gradOutput, + Tensor gradInput, Tensor gradOffset, + Tensor weight, Tensor columns, int kW, int kH, + int dW, int dH, int padW, int padH, + int dilationW, int dilationH, int group, + int deformable_group, int im2col_step); + +void deform_conv_backward_parameters(Tensor input, Tensor offset, + Tensor gradOutput, Tensor gradWeight, + Tensor columns, Tensor ones, int kW, + int kH, int dW, int dH, int padW, int padH, + int dilationW, int dilationH, int group, + int deformable_group, float scale, + int im2col_step); void deform_roi_pool_forward(Tensor input, Tensor rois, Tensor offset, Tensor output, int pooled_height, int pooled_width, @@ -52,39 +52,39 @@ void deform_roi_pool_backward(Tensor grad_output, Tensor input, Tensor rois, int pooled_width, float spatial_scale, int sampling_ratio, float gamma); -int sigmoid_focal_loss_forward(Tensor input, Tensor target, Tensor weight, - Tensor output, float gamma, float alpha); +void sigmoid_focal_loss_forward(Tensor input, Tensor target, Tensor weight, + Tensor output, float gamma, float alpha); -int sigmoid_focal_loss_backward(Tensor input, Tensor target, Tensor weight, - Tensor grad_input, float gamma, float alpha); +void sigmoid_focal_loss_backward(Tensor input, Tensor target, Tensor weight, + Tensor grad_input, float gamma, float alpha); -int softmax_focal_loss_forward(Tensor input, Tensor target, Tensor weight, - Tensor output, float gamma, float alpha); +void softmax_focal_loss_forward(Tensor input, Tensor target, Tensor weight, + Tensor output, float gamma, float alpha); -int softmax_focal_loss_backward(Tensor input, Tensor target, Tensor weight, - Tensor buff, Tensor grad_input, float gamma, - float alpha); +void softmax_focal_loss_backward(Tensor input, Tensor target, Tensor weight, + Tensor buff, Tensor grad_input, float gamma, + float alpha); void bbox_overlaps(const Tensor bboxes1, const Tensor bboxes2, Tensor ious, const int mode, const bool aligned, const int offset); -int masked_im2col_forward(const Tensor im, const Tensor mask_h_idx, - const Tensor mask_w_idx, Tensor col, - const int kernel_h, const int kernel_w, - const int pad_h, const int pad_w); +void masked_im2col_forward(const Tensor im, const Tensor mask_h_idx, + const Tensor mask_w_idx, Tensor col, + const int kernel_h, const int kernel_w, + const int pad_h, const int pad_w); -int masked_col2im_forward(const Tensor col, const Tensor mask_h_idx, - const Tensor mask_w_idx, Tensor im, int height, - int width, int channels); +void masked_col2im_forward(const Tensor col, const Tensor mask_h_idx, + const Tensor mask_w_idx, Tensor im, int height, + int width, int channels); -int modulated_deform_conv_forward( +void modulated_deform_conv_forward( Tensor input, Tensor weight, Tensor bias, Tensor ones, Tensor offset, Tensor mask, Tensor output, Tensor columns, int kernel_h, int kernel_w, const int stride_h, const int stride_w, const int pad_h, const int pad_w, const int dilation_h, const int dilation_w, const int group, const int deformable_group, const bool with_bias); -int modulated_deform_conv_backward( +void modulated_deform_conv_backward( Tensor input, Tensor weight, Tensor bias, Tensor ones, Tensor offset, Tensor mask, Tensor columns, Tensor grad_input, Tensor grad_weight, Tensor grad_bias, Tensor grad_offset, Tensor grad_mask, Tensor grad_output, @@ -99,22 +99,22 @@ Tensor softnms(Tensor boxes, Tensor scores, Tensor dets, float iou_threshold, std::vector > nms_match(Tensor dets, float iou_threshold); -int roi_align_forward(Tensor input, Tensor rois, Tensor output, Tensor argmax_y, - Tensor argmax_x, int aligned_height, int aligned_width, - float spatial_scale, int sampling_ratio, int pool_mode, - bool aligned); - -int roi_align_backward(Tensor grad_output, Tensor rois, Tensor argmax_y, - Tensor argmax_x, Tensor grad_input, int aligned_height, +void roi_align_forward(Tensor input, Tensor rois, Tensor output, + Tensor argmax_y, Tensor argmax_x, int aligned_height, int aligned_width, float spatial_scale, int sampling_ratio, int pool_mode, bool aligned); -int roi_pool_forward(Tensor input, Tensor rois, Tensor output, Tensor argmax, - int pooled_height, int pooled_width, float spatial_scale); +void roi_align_backward(Tensor grad_output, Tensor rois, Tensor argmax_y, + Tensor argmax_x, Tensor grad_input, int aligned_height, + int aligned_width, float spatial_scale, + int sampling_ratio, int pool_mode, bool aligned); + +void roi_pool_forward(Tensor input, Tensor rois, Tensor output, Tensor argmax, + int pooled_height, int pooled_width, float spatial_scale); -int roi_pool_backward(Tensor grad_output, Tensor rois, Tensor argmax, - Tensor grad_input, int pooled_height, int pooled_width, - float spatial_scale); +void roi_pool_backward(Tensor grad_output, Tensor rois, Tensor argmax, + Tensor grad_input, int pooled_height, int pooled_width, + float spatial_scale); void sync_bn_forward_mean(const Tensor input, Tensor mean); @@ -155,10 +155,9 @@ void psamask_backward(Tensor grad_output, const Tensor grad_input, const int w_feature, const int h_mask, const int w_mask, const int half_h_mask, const int half_w_mask); -void tin_shift_forward(const Tensor input, const Tensor shift, Tensor output); +void tin_shift_forward(Tensor input, Tensor shift, Tensor output); -void tin_shift_backward(Tensor grad_output, const Tensor shift, - const Tensor grad_input); +void tin_shift_backward(Tensor grad_output, Tensor shift, Tensor grad_input); Tensor bottom_pool_forward(Tensor input); From 270e470ee17c0f0f3a28eda3ccb90abae4c385f9 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Mon, 24 Aug 2020 13:41:54 +0800 Subject: [PATCH 33/81] [feature] Add collect_env() to collect environment info (#517) * [feature] Add collect_env() to collect environment info * fix unit tests * fix the case when ops are not compiled * fix docstring --- mmcv/utils/__init__.py | 19 ++++--- mmcv/utils/env.py | 93 ++++++++++++++++++++++++++++++++++- mmcv/utils/parrots_wrapper.py | 2 +- tests/test_env.py | 33 +++++++++++++ 4 files changed, 134 insertions(+), 13 deletions(-) create mode 100644 tests/test_env.py diff --git a/mmcv/utils/__init__.py b/mmcv/utils/__init__.py index f9ecfd296a..fc926cfe67 100644 --- a/mmcv/utils/__init__.py +++ b/mmcv/utils/__init__.py @@ -26,19 +26,18 @@ 'get_git_hash' ] else: - from .env import TORCH_VERSION + from .env import collect_env from .logging import get_logger, print_log - from .parrots_wrapper import (CUDA_HOME, BuildExtension, CppExtension, - CUDAExtension, DataLoader, PoolDataLoader, - SyncBatchNorm, _AdaptiveAvgPoolNd, - _AdaptiveMaxPoolNd, _AvgPoolNd, _BatchNorm, - _ConvNd, _ConvTransposeMixin, _InstanceNorm, - _MaxPoolNd, get_build_config) + from .parrots_wrapper import ( + CUDA_HOME, TORCH_VERSION, BuildExtension, CppExtension, CUDAExtension, + DataLoader, PoolDataLoader, SyncBatchNorm, _AdaptiveAvgPoolNd, + _AdaptiveMaxPoolNd, _AvgPoolNd, _BatchNorm, _ConvNd, + _ConvTransposeMixin, _InstanceNorm, _MaxPoolNd, get_build_config) from .registry import Registry, build_from_cfg __all__ = [ - 'Config', 'ConfigDict', 'DictAction', 'get_logger', 'print_log', - 'is_str', 'iter_cast', 'list_cast', 'tuple_cast', 'is_seq_of', - 'is_list_of', 'is_tuple_of', 'slice_list', 'concat_list', + 'Config', 'ConfigDict', 'DictAction', 'collect_env', 'get_logger', + 'print_log', 'is_str', 'iter_cast', 'list_cast', 'tuple_cast', + 'is_seq_of', 'is_list_of', 'is_tuple_of', 'slice_list', 'concat_list', 'check_prerequisites', 'requires_package', 'requires_executable', 'is_filepath', 'fopen', 'check_file_exist', 'mkdir_or_exist', 'symlink', 'scandir', 'ProgressBar', 'track_progress', diff --git a/mmcv/utils/env.py b/mmcv/utils/env.py index 2f31f71943..2cea9c7e23 100644 --- a/mmcv/utils/env.py +++ b/mmcv/utils/env.py @@ -1,4 +1,93 @@ -# This file holding some environment constant for sharing by other files +"""This file holding some environment constant for sharing by other files.""" + +import os.path as osp +import subprocess +import sys +from collections import defaultdict + +import cv2 import torch -TORCH_VERSION = torch.__version__ +import mmcv +from .parrots_wrapper import get_build_config + + +def collect_env(): + """Collect the information of the running environments. + + Returns: + dict: The environment information. The following fields are contained. + + - sys.platform: The variable of ``sys.platform``. + - Python: Python version. + - CUDA available: Bool, indicating if CUDA is available. + - GPU devices: Device type of each GPU. + - CUDA_HOME (optional): The env var ``CUDA_HOME``. + - NVCC (optional): NVCC version. + - GCC: GCC version, "n/a" if GCC is not installed. + - PyTorch: PyTorch version. + - PyTorch compiling details: The output of \ + ``torch.__config__.show()``. + - TorchVision (optional): TorchVision version. + - OpenCV: OpenCV version. + - MMCV: MMCV version. + - MMCV Compiler: The GCC version for compiling MMCV ops. + - MMCV CUDA Compiler: The CUDA version for compiling MMCV ops. + """ + env_info = {} + env_info['sys.platform'] = sys.platform + env_info['Python'] = sys.version.replace('\n', '') + + cuda_available = torch.cuda.is_available() + env_info['CUDA available'] = cuda_available + + if cuda_available: + devices = defaultdict(list) + for k in range(torch.cuda.device_count()): + devices[torch.cuda.get_device_name(k)].append(str(k)) + for name, device_ids in devices.items(): + env_info['GPU ' + ','.join(device_ids)] = name + + from torch.utils.cpp_extension import CUDA_HOME + env_info['CUDA_HOME'] = CUDA_HOME + + if CUDA_HOME is not None and osp.isdir(CUDA_HOME): + try: + nvcc = osp.join(CUDA_HOME, 'bin/nvcc') + nvcc = subprocess.check_output( + f'"{nvcc}" -V | tail -n1', shell=True) + nvcc = nvcc.decode('utf-8').strip() + except subprocess.SubprocessError: + nvcc = 'Not Available' + env_info['NVCC'] = nvcc + + try: + gcc = subprocess.check_output('gcc --version | head -n1', shell=True) + gcc = gcc.decode('utf-8').strip() + env_info['GCC'] = gcc + except subprocess.CalledProcessError: # gcc is unavailable + env_info['GCC'] = 'n/a' + + env_info['PyTorch'] = torch.__version__ + env_info['PyTorch compiling details'] = get_build_config() + + try: + import torchvision + env_info['TorchVision'] = torchvision.__version__ + except ModuleNotFoundError: + pass + + env_info['OpenCV'] = cv2.__version__ + + env_info['MMCV'] = mmcv.__version__ + + try: + from mmcv.ops import get_compiler_version, get_compiling_cuda_version + except ModuleNotFoundError: + env_info['MMCV Compiler'] = 'n/a' + env_info['MMCV CUDA Compiler'] = 'n/a' + else: + env_info['MMCV Compiler'] = get_compiler_version() + env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version() + + return env_info diff --git a/mmcv/utils/parrots_wrapper.py b/mmcv/utils/parrots_wrapper.py index e83bbd6e2f..25761be835 100644 --- a/mmcv/utils/parrots_wrapper.py +++ b/mmcv/utils/parrots_wrapper.py @@ -2,7 +2,7 @@ import torch -from .env import TORCH_VERSION +TORCH_VERSION = torch.__version__ def _get_cuda_home(): diff --git a/tests/test_env.py b/tests/test_env.py new file mode 100644 index 0000000000..7c245c7a52 --- /dev/null +++ b/tests/test_env.py @@ -0,0 +1,33 @@ +import sys + +import pytest + +import mmcv + + +def test_collect_env(): + try: + import torch # noqa: F401 + except ModuleNotFoundError: + pytest.skip('skipping tests that require PyTorch') + + from mmcv.utils import collect_env + env_info = collect_env() + expected_keys = [ + 'sys.platform', 'Python', 'CUDA available', 'PyTorch', + 'PyTorch compiling details', 'OpenCV', 'MMCV', 'MMCV Compiler', + 'MMCV CUDA Compiler' + ] + for key in expected_keys: + assert key in env_info + + if env_info['CUDA available']: + for key in ['CUDA_HOME', 'NVCC']: + assert key in env_info + + if sys.platform != 'win32': + assert 'GCC' in env_info + + assert env_info['sys.platform'] == sys.platform + assert env_info['Python'] == sys.version.replace('\n', '') + assert env_info['MMCV'] == mmcv.__version__ From 09b7d6c7dd1a889ce0b798fa8b7f54179d877caf Mon Sep 17 00:00:00 2001 From: Wang Xinjiang Date: Mon, 24 Aug 2020 13:45:34 +0800 Subject: [PATCH 34/81] Import modules from a string list (#514) * Custom imports * Resolve comments * Add unittest * Add unittest * Rename custom_imports to import_modules_from_strings * Move import_modules_from_strings ito misc.py and allow failed imports * small change * small change * change mmcv.runner to os.path --- mmcv/utils/__init__.py | 11 +++++----- mmcv/utils/misc.py | 48 ++++++++++++++++++++++++++++++++++++++++++ tests/test_misc.py | 34 ++++++++++++++++++++++++++++++ 3 files changed, 88 insertions(+), 5 deletions(-) diff --git a/mmcv/utils/__init__.py b/mmcv/utils/__init__.py index fc926cfe67..21db834bb4 100644 --- a/mmcv/utils/__init__.py +++ b/mmcv/utils/__init__.py @@ -2,9 +2,9 @@ # Copyright (c) Open-MMLab. All rights reserved. from .config import Config, ConfigDict, DictAction from .misc import (check_prerequisites, concat_list, deprecated_api_warning, - is_list_of, is_seq_of, is_str, is_tuple_of, iter_cast, - list_cast, requires_executable, requires_package, - slice_list, tuple_cast) + import_modules_from_strings, is_list_of, is_seq_of, is_str, + is_tuple_of, iter_cast, list_cast, requires_executable, + requires_package, slice_list, tuple_cast) from .path import (check_file_exist, fopen, is_filepath, mkdir_or_exist, scandir, symlink) from .progressbar import (ProgressBar, track_iter_progress, @@ -23,7 +23,7 @@ 'mkdir_or_exist', 'symlink', 'scandir', 'ProgressBar', 'track_progress', 'track_iter_progress', 'track_parallel_progress', 'Timer', 'TimerError', 'check_time', 'deprecated_api_warning', - 'get_git_hash' + 'get_git_hash', 'import_modules_from_strings' ] else: from .env import collect_env @@ -47,5 +47,6 @@ '_AvgPoolNd', '_BatchNorm', '_ConvNd', '_ConvTransposeMixin', '_InstanceNorm', '_MaxPoolNd', 'get_build_config', 'BuildExtension', 'CppExtension', 'CUDAExtension', 'DataLoader', 'PoolDataLoader', - 'TORCH_VERSION', 'deprecated_api_warning', 'get_git_hash' + 'TORCH_VERSION', 'deprecated_api_warning', 'get_git_hash', + 'import_modules_from_strings' ] diff --git a/mmcv/utils/misc.py b/mmcv/utils/misc.py index e0507a3fd3..da70738b80 100644 --- a/mmcv/utils/misc.py +++ b/mmcv/utils/misc.py @@ -16,6 +16,54 @@ def is_str(x): return isinstance(x, str) +def import_modules_from_strings(imports, allow_failed_imports=False): + """Import modules from the given list of strings. + + Args: + imports (list | str | None): The given module names to be imported. + allow_failed_imports (bool): If True, the failed imports will return + None. Otherwise, an ImportError is raise. Default: False. + + Returns: + list[module] | module | None: The imported modules. + + Examples: + >>> osp, sys = import_modules_from_strings( + ... ['os.path', 'sys']) + >>> import os.path as osp_ + >>> import sys as sys_ + >>> assert osp == osp_ + >>> assert sys == sys_ + """ + if not imports: + return + single_import = False + if isinstance(imports, str): + single_import = True + imports = [imports] + if not isinstance(imports, list): + raise TypeError( + f'custom_imports must be a list but got type {type(imports)}') + imported = [] + for imp in imports: + if not isinstance(imp, str): + raise TypeError( + f'{imp} is of type {type(imp)} and cannot be imported.') + try: + imported_tmp = import_module(imp) + except ImportError: + if allow_failed_imports: + warnings.warn(f'{imp} failed to import and is ignored.', + UserWarning) + imported_tmp = None + else: + raise ImportError + imported.append(imported_tmp) + if single_import: + imported = imported[0] + return imported + + def iter_cast(inputs, dst_type, return_type=None): """Cast elements of an iterable object into some type. diff --git a/tests/test_misc.py b/tests/test_misc.py index 47bc065297..adcd26ea0d 100644 --- a/tests/test_misc.py +++ b/tests/test_misc.py @@ -100,3 +100,37 @@ def func_c(): ' please install them first.\n') assert func_c() == 1 + + +def test_import_modules_from_strings(): + # multiple imports + import os.path as osp_ + import sys as sys_ + osp, sys = mmcv.import_modules_from_strings(['os.path', 'sys']) + assert osp == osp_ + assert sys == sys_ + + # single imports + osp = mmcv.import_modules_from_strings('os.path') + assert osp == osp_ + # No imports + assert mmcv.import_modules_from_strings(None) is None + assert mmcv.import_modules_from_strings([]) is None + assert mmcv.import_modules_from_strings('') is None + # Unsupported types + with pytest.raises(TypeError): + mmcv.import_modules_from_strings(1) + with pytest.raises(TypeError): + mmcv.import_modules_from_strings([1]) + # Failed imports + with pytest.raises(ImportError): + mmcv.import_modules_from_strings('_not_implemented_module') + with pytest.warns(UserWarning): + imported = mmcv.import_modules_from_strings( + '_not_implemented_module', allow_failed_imports=True) + assert imported is None + with pytest.warns(UserWarning): + imported = mmcv.import_modules_from_strings( + ['os.path', '_not_implemented'], allow_failed_imports=True) + assert imported[0] == osp + assert imported[1] is None From 89e1716afe70282006ac7c67b2e63c1b2a183e8e Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Mon, 24 Aug 2020 16:30:45 +0800 Subject: [PATCH 35/81] Bump version to v1.1.1 (#518) * bump version to 1.1.1 * add more version utils * move parse_version_info to version.py --- mmcv/__init__.py | 2 +- mmcv/utils/__init__.py | 8 ++--- mmcv/utils/version_utils.py | 72 ++++++++++++++++++++++++++++--------- mmcv/version.py | 29 ++++++++++++++- tests/test_version_utils.py | 37 +++++++++++++++++++ 5 files changed, 125 insertions(+), 23 deletions(-) create mode 100644 tests/test_version_utils.py diff --git a/mmcv/__init__.py b/mmcv/__init__.py index 9bb48c4321..74ee0442fc 100644 --- a/mmcv/__init__.py +++ b/mmcv/__init__.py @@ -4,7 +4,7 @@ from .fileio import * from .image import * from .utils import * -from .version import __version__ +from .version import * from .video import * from .visualization import * diff --git a/mmcv/utils/__init__.py b/mmcv/utils/__init__.py index 21db834bb4..bf8792fae9 100644 --- a/mmcv/utils/__init__.py +++ b/mmcv/utils/__init__.py @@ -10,7 +10,7 @@ from .progressbar import (ProgressBar, track_iter_progress, track_parallel_progress, track_progress) from .timer import Timer, TimerError, check_time -from .version_utils import get_git_hash +from .version_utils import digit_version, get_git_hash try: import torch @@ -23,7 +23,7 @@ 'mkdir_or_exist', 'symlink', 'scandir', 'ProgressBar', 'track_progress', 'track_iter_progress', 'track_parallel_progress', 'Timer', 'TimerError', 'check_time', 'deprecated_api_warning', - 'get_git_hash', 'import_modules_from_strings' + 'digit_version', 'get_git_hash', 'import_modules_from_strings' ] else: from .env import collect_env @@ -47,6 +47,6 @@ '_AvgPoolNd', '_BatchNorm', '_ConvNd', '_ConvTransposeMixin', '_InstanceNorm', '_MaxPoolNd', 'get_build_config', 'BuildExtension', 'CppExtension', 'CUDAExtension', 'DataLoader', 'PoolDataLoader', - 'TORCH_VERSION', 'deprecated_api_warning', 'get_git_hash', - 'import_modules_from_strings' + 'TORCH_VERSION', 'deprecated_api_warning', 'digit_version', + 'get_git_hash', 'import_modules_from_strings' ] diff --git a/mmcv/utils/version_utils.py b/mmcv/utils/version_utils.py index 876a1488db..585c9b7c76 100644 --- a/mmcv/utils/version_utils.py +++ b/mmcv/utils/version_utils.py @@ -2,27 +2,65 @@ import subprocess -def get_git_hash(fallback='unknown'): - # Get git hash of the current repo - - def _minimal_ext_cmd(cmd): - # construct minimal environment - env = {} - for k in ['SYSTEMROOT', 'PATH', 'HOME']: - v = os.environ.get(k) - if v is not None: - env[k] = v - # LANGUAGE is used on win32 - env['LANGUAGE'] = 'C' - env['LANG'] = 'C' - env['LC_ALL'] = 'C' - out = subprocess.Popen( - cmd, stdout=subprocess.PIPE, env=env).communicate()[0] - return out +def digit_version(version_str): + """Convert a version string into a tuple of integers. + + This method is usually used for comparing two versions. + + Args: + version_str (str): The version string. + + Returns: + tuple[int]: The version info in digits (integers). + """ + digit_version = [] + for x in version_str.split('.'): + if x.isdigit(): + digit_version.append(int(x)) + elif x.find('rc') != -1: + patch_version = x.split('rc') + digit_version.append(int(patch_version[0]) - 1) + digit_version.append(int(patch_version[1])) + return tuple(digit_version) + + +def _minimal_ext_cmd(cmd): + # construct minimal environment + env = {} + for k in ['SYSTEMROOT', 'PATH', 'HOME']: + v = os.environ.get(k) + if v is not None: + env[k] = v + # LANGUAGE is used on win32 + env['LANGUAGE'] = 'C' + env['LANG'] = 'C' + env['LC_ALL'] = 'C' + out = subprocess.Popen( + cmd, stdout=subprocess.PIPE, env=env).communicate()[0] + return out + + +def get_git_hash(fallback='unknown', digits=None): + """Get the git hash of the current repo. + + Args: + fallback (str, optional): The fallback string when git hash is + unavailable. Defaults to 'unknown'. + digits (int, optional): kept digits of the hash. Defaults to None, + meaning all digits are kept. + + Returns: + str: Git commit hash. + """ + + if digits is not None and not isinstance(digits, int): + raise TypeError('digits must be None or an integer') try: out = _minimal_ext_cmd(['git', 'rev-parse', 'HEAD']) sha = out.strip().decode('ascii') + if digits is not None: + sha = sha[:digits] except OSError: sha = fallback diff --git a/mmcv/version.py b/mmcv/version.py index 7c2c24932d..b4b3f99684 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,2 +1,29 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.1.0' + +__version__ = '1.1.1' + + +def parse_version_info(version_str): + """Parse a version string into a tuple. + + Args: + version_str (str): The version string. + + Returns: + tuple[int | str]: The version info, e.g., "1.3.0" is parsed into + (1, 3, 0), and "2.0.0rc1" is parsed into (2, 0, 0, 'rc1'). + """ + version_info = [] + for x in version_str.split('.'): + if x.isdigit(): + version_info.append(int(x)) + elif x.find('rc') != -1: + patch_version = x.split('rc') + version_info.append(int(patch_version[0])) + version_info.append(f'rc{patch_version[1]}') + return tuple(version_info) + + +version_info = parse_version_info(__version__) + +__all__ = ['__version__', 'version_info', 'parse_version_info'] diff --git a/tests/test_version_utils.py b/tests/test_version_utils.py new file mode 100644 index 0000000000..775359bc8b --- /dev/null +++ b/tests/test_version_utils.py @@ -0,0 +1,37 @@ +from unittest.mock import patch + +from mmcv import digit_version, get_git_hash, parse_version_info + + +def test_digit_version(): + assert digit_version('0.2.16') == (0, 2, 16) + assert digit_version('1.2.3') == (1, 2, 3) + assert digit_version('1.2.3rc0') == (1, 2, 2, 0) + assert digit_version('1.2.3rc1') == (1, 2, 2, 1) + assert digit_version('1.0rc0') == (1, -1, 0) + + +def test_parse_version_info(): + assert parse_version_info('0.2.16') == (0, 2, 16) + assert parse_version_info('1.2.3') == (1, 2, 3) + assert parse_version_info('1.2.3rc0') == (1, 2, 3, 'rc0') + assert parse_version_info('1.2.3rc1') == (1, 2, 3, 'rc1') + assert parse_version_info('1.0rc0') == (1, 0, 'rc0') + + +def _mock_cmd_success(cmd): + return '3b46d33e90c397869ad5103075838fdfc9812aa0'.encode('ascii') + + +def _mock_cmd_fail(cmd): + raise OSError + + +def test_get_git_hash(): + with patch('mmcv.utils.version_utils._minimal_ext_cmd', _mock_cmd_success): + assert get_git_hash() == '3b46d33e90c397869ad5103075838fdfc9812aa0' + assert get_git_hash(digits=6) == '3b46d3' + assert get_git_hash(digits=100) == get_git_hash() + with patch('mmcv.utils.version_utils._minimal_ext_cmd', _mock_cmd_fail): + assert get_git_hash() == 'unknown' + assert get_git_hash(fallback='n/a') == 'n/a' From 66a38c86f8aaad9a03177da46a0b93e9d85f419d Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Tue, 25 Aug 2020 20:11:56 +0800 Subject: [PATCH 36/81] Move unit tests to specific folders (#520) * move unit tests to specific folders * fix path error * remove some assertions * fix ignore path --- .github/workflows/build.yml | 4 +- tests/{ => test_runner}/test_fp16.py | 0 tests/{ => test_runner}/test_optimizer.py | 0 tests/{ => test_utils}/test_config.py | 50 ++++++++++---------- tests/{ => test_utils}/test_env.py | 0 tests/{ => test_utils}/test_logging.py | 0 tests/{ => test_utils}/test_misc.py | 0 tests/{ => test_utils}/test_path.py | 2 +- tests/{ => test_utils}/test_progressbar.py | 26 +++++----- tests/{ => test_utils}/test_registry.py | 0 tests/{ => test_utils}/test_timer.py | 0 tests/{ => test_utils}/test_version_utils.py | 0 12 files changed, 43 insertions(+), 39 deletions(-) rename tests/{ => test_runner}/test_fp16.py (100%) rename tests/{ => test_runner}/test_optimizer.py (100%) rename tests/{ => test_utils}/test_config.py (87%) rename tests/{ => test_utils}/test_env.py (100%) rename tests/{ => test_utils}/test_logging.py (100%) rename tests/{ => test_utils}/test_misc.py (100%) rename tests/{ => test_utils}/test_path.py (95%) rename tests/{ => test_utils}/test_progressbar.py (86%) rename tests/{ => test_utils}/test_registry.py (100%) rename tests/{ => test_utils}/test_timer.py (100%) rename tests/{ => test_utils}/test_version_utils.py (100%) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index c97c47faa0..98e0eab71d 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -53,7 +53,7 @@ jobs: run: pip install Pillow - name: Run unittests and generate coverage report run: | - pytest tests/ --ignore=tests/test_runner --ignore=tests/test_optimizer.py --ignore=tests/test_cnn --ignore=tests/test_parallel.py --ignore=tests/test_ops --ignore=tests/test_load_model_zoo.py --ignore=tests/test_logging.py --ignore=tests/test_image/test_io.py --ignore=tests/test_registry.py --ignore=tests/test_fp16.py + pytest tests/ --ignore=tests/test_runner --ignore=tests/test_optimizer.py --ignore=tests/test_cnn --ignore=tests/test_parallel.py --ignore=tests/test_ops --ignore=tests/test_load_model_zoo.py --ignore=tests/test_utils/test_logging.py --ignore=tests/test_image/test_io.py --ignore=tests/test_utils/test_registry.py build_without_ops: runs-on: ubuntu-latest @@ -231,4 +231,4 @@ jobs: - name: Run unittests run: | # The timing on macos VMs is not precise, so we skip the progressbar tests - pytest tests/ --ignore tests/test_progressbar.py --ignore tests/test_timer.py + pytest tests/ --ignore tests/test_utils/test_progressbar.py --ignore tests/test_utils/test_timer.py diff --git a/tests/test_fp16.py b/tests/test_runner/test_fp16.py similarity index 100% rename from tests/test_fp16.py rename to tests/test_runner/test_fp16.py diff --git a/tests/test_optimizer.py b/tests/test_runner/test_optimizer.py similarity index 100% rename from tests/test_optimizer.py rename to tests/test_runner/test_optimizer.py diff --git a/tests/test_config.py b/tests/test_utils/test_config.py similarity index 87% rename from tests/test_config.py rename to tests/test_utils/test_config.py index 432c4fab73..0f669e8bb9 100644 --- a/tests/test_config.py +++ b/tests/test_utils/test_config.py @@ -9,6 +9,8 @@ from mmcv import Config, DictAction, dump, load +data_path = osp.join(osp.dirname(osp.dirname(__file__)), 'data') + def test_construct(): cfg = Config() @@ -22,7 +24,7 @@ def test_construct(): cfg_dict = dict(item1=[1, 2], item2=dict(a=0), item3=True, item4='test') # test a.py - cfg_file = osp.join(osp.dirname(__file__), 'data/config/a.py') + cfg_file = osp.join(data_path, 'config/a.py') cfg = Config(cfg_dict, filename=cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -35,7 +37,7 @@ def test_construct(): assert Config.fromfile(dump_file) # test b.json - cfg_file = osp.join(osp.dirname(__file__), 'data/config/b.json') + cfg_file = osp.join(data_path, 'config/b.json') cfg = Config(cfg_dict, filename=cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -48,7 +50,7 @@ def test_construct(): assert Config.fromfile(dump_file) # test c.yaml - cfg_file = osp.join(osp.dirname(__file__), 'data/config/c.yaml') + cfg_file = osp.join(data_path, 'config/c.yaml') cfg = Config(cfg_dict, filename=cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -61,7 +63,7 @@ def test_construct(): assert Config.fromfile(dump_file) # test h.py - cfg_file = osp.join(osp.dirname(__file__), 'data/config/h.py') + cfg_file = osp.join(data_path, 'config/h.py') cfg_dict = dict( item1='h.py', item2=f'{osp.dirname(__file__)}/data/config', @@ -91,7 +93,7 @@ def test_construct(): assert Config.fromfile(cfg_file, False)['item3'] == cfg_dict['item3'] # test p.yaml - cfg_file = osp.join(osp.dirname(__file__), 'data/config/p.yaml') + cfg_file = osp.join(data_path, 'config/p.yaml') cfg_dict = dict(item1=f'{osp.dirname(__file__)}/data/config') cfg = Config(cfg_dict, filename=cfg_file) assert isinstance(cfg, Config) @@ -110,7 +112,7 @@ def test_construct(): assert Config.fromfile(cfg_file, False)['item1'] == '{{ fileDirname }}' # test o.json - cfg_file = osp.join(osp.dirname(__file__), 'data/config/o.json') + cfg_file = osp.join(data_path, 'config/o.json') cfg_dict = dict(item1=f'{osp.dirname(__file__)}/data/config') cfg = Config(cfg_dict, filename=cfg_file) assert isinstance(cfg, Config) @@ -131,7 +133,7 @@ def test_construct(): def test_fromfile(): for filename in ['a.py', 'a.b.py', 'b.json', 'c.yaml']: - cfg_file = osp.join(osp.dirname(__file__), 'data/config', filename) + cfg_file = osp.join(data_path, 'config', filename) cfg = Config.fromfile(cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -141,15 +143,15 @@ def test_fromfile(): with pytest.raises(FileNotFoundError): Config.fromfile('no_such_file.py') with pytest.raises(IOError): - Config.fromfile(osp.join(osp.dirname(__file__), 'data/color.jpg')) + Config.fromfile(osp.join(data_path, 'color.jpg')) def test_merge_from_base(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/d.py') + cfg_file = osp.join(data_path, 'config/d.py') cfg = Config.fromfile(cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file - base_cfg_file = osp.join(osp.dirname(__file__), 'data/config/base.py') + base_cfg_file = osp.join(data_path, 'config/base.py') merge_text = osp.abspath(osp.expanduser(base_cfg_file)) + '\n' + \ open(base_cfg_file, 'r').read() merge_text += '\n' + osp.abspath(osp.expanduser(cfg_file)) + '\n' + \ @@ -161,11 +163,11 @@ def test_merge_from_base(): assert cfg.item4 == 'test_base' with pytest.raises(TypeError): - Config.fromfile(osp.join(osp.dirname(__file__), 'data/config/e.py')) + Config.fromfile(osp.join(data_path, 'config/e.py')) def test_merge_from_multiple_bases(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/l.py') + cfg_file = osp.join(data_path, 'config/l.py') cfg = Config.fromfile(cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -179,11 +181,11 @@ def test_merge_from_multiple_bases(): assert cfg.item7 == dict(a=[0, 1, 2], b=dict(c=[3.1, 4.2, 5.3])) with pytest.raises(KeyError): - Config.fromfile(osp.join(osp.dirname(__file__), 'data/config/m.py')) + Config.fromfile(osp.join(data_path, 'config/m.py')) def test_merge_recursive_bases(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/f.py') + cfg_file = osp.join(data_path, 'config/f.py') cfg = Config.fromfile(cfg_file) assert isinstance(cfg, Config) assert cfg.filename == cfg_file @@ -195,7 +197,7 @@ def test_merge_recursive_bases(): def test_merge_from_dict(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/a.py') + cfg_file = osp.join(data_path, 'config/a.py') cfg = Config.fromfile(cfg_file) input_options = {'item2.a': 1, 'item2.b': 0.1, 'item3': False} cfg.merge_from_dict(input_options) @@ -204,7 +206,7 @@ def test_merge_from_dict(): def test_merge_delete(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/delete.py') + cfg_file = osp.join(data_path, 'config/delete.py') cfg = Config.fromfile(cfg_file) # cfg.field assert cfg.item1 == [1, 2] @@ -216,7 +218,7 @@ def test_merge_delete(): def test_merge_intermediate_variable(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/i_child.py') + cfg_file = osp.join(data_path, 'config/i_child.py') cfg = Config.fromfile(cfg_file) # cfg.field assert cfg.item1 == [1, 2] @@ -229,7 +231,7 @@ def test_merge_intermediate_variable(): def test_fromfile_in_config(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/code.py') + cfg_file = osp.join(data_path, 'config/code.py') cfg = Config.fromfile(cfg_file) # cfg.field assert cfg.cfg.item1 == [1, 2] @@ -243,7 +245,7 @@ def test_dict(): cfg_dict = dict(item1=[1, 2], item2=dict(a=0), item3=True, item4='test') for filename in ['a.py', 'b.json', 'c.yaml']: - cfg_file = osp.join(osp.dirname(__file__), 'data/config', filename) + cfg_file = osp.join(data_path, 'config', filename) cfg = Config.fromfile(cfg_file) # len(cfg) @@ -298,7 +300,7 @@ def test_setattr(): def test_pretty_text(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/l.py') + cfg_file = osp.join(data_path, 'config/l.py') cfg = Config.fromfile(cfg_file) with tempfile.TemporaryDirectory() as temp_config_dir: text_cfg_filename = osp.join(temp_config_dir, '_text_config.py') @@ -317,7 +319,7 @@ def test_dict_action(): out_dict = {'item2.a': 1, 'item2.b': 0.1, 'item2.c': 'x', 'item3': False} assert args.options == out_dict - cfg_file = osp.join(osp.dirname(__file__), 'data/config/a.py') + cfg_file = osp.join(data_path, 'config/a.py') cfg = Config.fromfile(cfg_file) cfg.merge_from_dict(args.options) assert cfg.item2 == dict(a=1, b=0.1, c='x') @@ -325,7 +327,7 @@ def test_dict_action(): def test_dump_mapping(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/n.py') + cfg_file = osp.join(data_path, 'config/n.py') cfg = Config.fromfile(cfg_file) with tempfile.TemporaryDirectory() as temp_config_dir: @@ -337,7 +339,7 @@ def test_dump_mapping(): def test_reserved_key(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/g.py') + cfg_file = osp.join(data_path, 'config/g.py') with pytest.raises(KeyError): Config.fromfile(cfg_file) @@ -357,7 +359,7 @@ def test_syntax_error(): def test_pickle_support(): - cfg_file = osp.join(osp.dirname(__file__), 'data/config/n.py') + cfg_file = osp.join(data_path, 'config/n.py') cfg = Config.fromfile(cfg_file) with tempfile.TemporaryDirectory() as temp_config_dir: diff --git a/tests/test_env.py b/tests/test_utils/test_env.py similarity index 100% rename from tests/test_env.py rename to tests/test_utils/test_env.py diff --git a/tests/test_logging.py b/tests/test_utils/test_logging.py similarity index 100% rename from tests/test_logging.py rename to tests/test_utils/test_logging.py diff --git a/tests/test_misc.py b/tests/test_utils/test_misc.py similarity index 100% rename from tests/test_misc.py rename to tests/test_utils/test_misc.py diff --git a/tests/test_path.py b/tests/test_utils/test_path.py similarity index 95% rename from tests/test_path.py rename to tests/test_utils/test_path.py index 6fe71d1592..42f308ef66 100644 --- a/tests/test_path.py +++ b/tests/test_utils/test_path.py @@ -26,7 +26,7 @@ def test_check_file_exist(): def test_scandir(): - folder = osp.join(osp.dirname(__file__), 'data/for_scan') + folder = osp.join(osp.dirname(osp.dirname(__file__)), 'data/for_scan') filenames = ['a.bin', '1.txt', '2.txt', '1.json', '2.json'] assert set(mmcv.scandir(folder)) == set(filenames) assert set(mmcv.scandir(Path(folder))) == set(filenames) diff --git a/tests/test_progressbar.py b/tests/test_utils/test_progressbar.py similarity index 86% rename from tests/test_progressbar.py rename to tests/test_utils/test_progressbar.py index 061c21fa37..3e594da94d 100644 --- a/tests/test_progressbar.py +++ b/tests/test_utils/test_progressbar.py @@ -147,12 +147,13 @@ def test_track_parallel_progress_list(): out = StringIO() results = mmcv.track_parallel_progress( sleep_1s, [1, 2, 3, 4], 2, bar_width=4, file=out) - assert out.getvalue() == ( - '[ ] 0/4, elapsed: 0s, ETA:' - '\r[> ] 1/4, 1.0 task/s, elapsed: 1s, ETA: 3s' - '\r[>> ] 2/4, 2.0 task/s, elapsed: 1s, ETA: 1s' - '\r[>>> ] 3/4, 1.5 task/s, elapsed: 2s, ETA: 1s' - '\r[>>>>] 4/4, 2.0 task/s, elapsed: 2s, ETA: 0s\n') + # The following cannot pass CI on Github Action + # assert out.getvalue() == ( + # '[ ] 0/4, elapsed: 0s, ETA:' + # '\r[> ] 1/4, 1.0 task/s, elapsed: 1s, ETA: 3s' + # '\r[>> ] 2/4, 2.0 task/s, elapsed: 1s, ETA: 1s' + # '\r[>>> ] 3/4, 1.5 task/s, elapsed: 2s, ETA: 1s' + # '\r[>>>>] 4/4, 2.0 task/s, elapsed: 2s, ETA: 0s\n') assert results == [1, 2, 3, 4] @@ -160,10 +161,11 @@ def test_track_parallel_progress_iterator(): out = StringIO() results = mmcv.track_parallel_progress( sleep_1s, ((i for i in [1, 2, 3, 4]), 4), 2, bar_width=4, file=out) - assert out.getvalue() == ( - '[ ] 0/4, elapsed: 0s, ETA:' - '\r[> ] 1/4, 1.0 task/s, elapsed: 1s, ETA: 3s' - '\r[>> ] 2/4, 2.0 task/s, elapsed: 1s, ETA: 1s' - '\r[>>> ] 3/4, 1.5 task/s, elapsed: 2s, ETA: 1s' - '\r[>>>>] 4/4, 2.0 task/s, elapsed: 2s, ETA: 0s\n') + # The following cannot pass CI on Github Action + # assert out.getvalue() == ( + # '[ ] 0/4, elapsed: 0s, ETA:' + # '\r[> ] 1/4, 1.0 task/s, elapsed: 1s, ETA: 3s' + # '\r[>> ] 2/4, 2.0 task/s, elapsed: 1s, ETA: 1s' + # '\r[>>> ] 3/4, 1.5 task/s, elapsed: 2s, ETA: 1s' + # '\r[>>>>] 4/4, 2.0 task/s, elapsed: 2s, ETA: 0s\n') assert results == [1, 2, 3, 4] diff --git a/tests/test_registry.py b/tests/test_utils/test_registry.py similarity index 100% rename from tests/test_registry.py rename to tests/test_utils/test_registry.py diff --git a/tests/test_timer.py b/tests/test_utils/test_timer.py similarity index 100% rename from tests/test_timer.py rename to tests/test_utils/test_timer.py diff --git a/tests/test_version_utils.py b/tests/test_utils/test_version_utils.py similarity index 100% rename from tests/test_version_utils.py rename to tests/test_utils/test_version_utils.py From c3d8eb34ffc19c1f9ebb494336bedb687a9fc297 Mon Sep 17 00:00:00 2001 From: Xiaojie Li Date: Thu, 27 Aug 2020 00:39:17 +0800 Subject: [PATCH 37/81] add Swish activation (#522) * update impad * fix docstring * add shape for impad * fix unit test * remove old version & fix doc * fix linting * fix doc * add linear decay learning rate scheduler * fix impad * fix setup.cfg * fix linting * add yapf * add swish * fix lr_updater * fix lr_updater.py * update swish * add swish * fix inplace * fix typo Co-authored-by: lixiaojie --- mmcv/cnn/__init__.py | 4 ++-- mmcv/cnn/bricks/__init__.py | 3 ++- mmcv/cnn/bricks/conv_module.py | 2 +- mmcv/cnn/bricks/swish.py | 24 ++++++++++++++++++++++++ tests/test_cnn/test_swish.py | 15 +++++++++++++++ 5 files changed, 44 insertions(+), 4 deletions(-) create mode 100644 mmcv/cnn/bricks/swish.py create mode 100644 tests/test_cnn/test_swish.py diff --git a/mmcv/cnn/__init__.py b/mmcv/cnn/__init__.py index e44b0226f7..5fa25a2e48 100644 --- a/mmcv/cnn/__init__.py +++ b/mmcv/cnn/__init__.py @@ -5,7 +5,7 @@ ContextBlock, ConvAWS2d, ConvModule, ConvWS2d, DepthwiseSeparableConvModule, GeneralizedAttention, HSigmoid, HSwish, NonLocal1d, NonLocal2d, NonLocal3d, - Scale, build_activation_layer, build_conv_layer, + Scale, Swish, build_activation_layer, build_conv_layer, build_norm_layer, build_padding_layer, build_plugin_layer, build_upsample_layer, conv_ws_2d, is_norm) from .resnet import ResNet, make_res_layer @@ -21,7 +21,7 @@ 'build_activation_layer', 'build_conv_layer', 'build_norm_layer', 'build_padding_layer', 'build_upsample_layer', 'build_plugin_layer', 'is_norm', 'NonLocal1d', 'NonLocal2d', 'NonLocal3d', 'ContextBlock', - 'HSigmoid', 'HSwish', 'GeneralizedAttention', 'ACTIVATION_LAYERS', + 'HSigmoid', 'Swish', 'HSwish', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'get_model_complexity_info', 'conv_ws_2d', 'ConvAWS2d', 'ConvWS2d', 'fuse_conv_bn', 'DepthwiseSeparableConvModule' diff --git a/mmcv/cnn/bricks/__init__.py b/mmcv/cnn/bricks/__init__.py index 6cffa166cd..781f7e1206 100644 --- a/mmcv/cnn/bricks/__init__.py +++ b/mmcv/cnn/bricks/__init__.py @@ -14,6 +14,7 @@ from .registry import (ACTIVATION_LAYERS, CONV_LAYERS, NORM_LAYERS, PADDING_LAYERS, PLUGIN_LAYERS, UPSAMPLE_LAYERS) from .scale import Scale +from .swish import Swish from .upsample import build_upsample_layer __all__ = [ @@ -23,5 +24,5 @@ 'NonLocal2d', 'NonLocal3d', 'ContextBlock', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'ConvAWS2d', 'ConvWS2d', - 'conv_ws_2d', 'DepthwiseSeparableConvModule' + 'conv_ws_2d', 'DepthwiseSeparableConvModule', 'Swish' ] diff --git a/mmcv/cnn/bricks/conv_module.py b/mmcv/cnn/bricks/conv_module.py index fe4694d405..d30c00425d 100644 --- a/mmcv/cnn/bricks/conv_module.py +++ b/mmcv/cnn/bricks/conv_module.py @@ -145,7 +145,7 @@ def __init__(self, act_cfg_ = act_cfg.copy() # nn.Tanh has no 'inplace' argument if act_cfg_['type'] not in [ - 'Tanh', 'PReLU', 'Sigmoid', 'HSigmoid' + 'Tanh', 'PReLU', 'Sigmoid', 'HSigmoid', 'Swish' ]: act_cfg_.setdefault('inplace', inplace) self.activate = build_activation_layer(act_cfg_) diff --git a/mmcv/cnn/bricks/swish.py b/mmcv/cnn/bricks/swish.py new file mode 100644 index 0000000000..f396dc59b7 --- /dev/null +++ b/mmcv/cnn/bricks/swish.py @@ -0,0 +1,24 @@ +import torch +import torch.nn as nn + +from .registry import ACTIVATION_LAYERS + + +@ACTIVATION_LAYERS.register_module() +class Swish(nn.Module): + """Swish Module. + + This module applies the swish function: + + .. math:: + Swish(x) = x * Sigmoid(x) + + Returns: + Tensor: The output tensor. + """ + + def __init__(self): + super(Swish, self).__init__() + + def forward(self, x): + return x * torch.sigmoid(x) diff --git a/tests/test_cnn/test_swish.py b/tests/test_cnn/test_swish.py new file mode 100644 index 0000000000..d8e777290a --- /dev/null +++ b/tests/test_cnn/test_swish.py @@ -0,0 +1,15 @@ +import torch +from torch.nn.functional import sigmoid + +from mmcv.cnn.bricks import Swish + + +def test_swish(): + act = Swish() + input = torch.randn(1, 3, 64, 64) + expected_output = input * sigmoid(input) + output = act(input) + # test output shape + assert output.shape == expected_output.shape + # test output value + assert torch.equal(output, expected_output) From fc4993cdec389113ff461a805d9bf4b14756d921 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Tue, 1 Sep 2020 16:15:03 +0800 Subject: [PATCH 38/81] [feature] Use cu92 & ubuntu1604 for torch 1.3.1 (#524) * [feature] Use cu92 & ubuntu1604 for torch 1.3.1 * [fix]Use ubuntu-16.04 rather than latest for cu92 * [fix]: soft link cuda path * Debug cu101 bug * Update usr/include for cublas with cu101 * Check default nvcc version * rm : * add cuda root * Try to locate cublas_v2.h * Set cublas version * Force cublas version * check usr/local/cuda-10.2 * Add tree * cp cublas files * cp cublas files to lib64 * do not tree cuda * fix path cp error * cp dir * Keep using CUDA10.1 only * recover empty line --- .github/workflows/build.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 98e0eab71d..e9c0f23489 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -167,6 +167,8 @@ jobs: sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-} sudo apt clean export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT} + sudo cp /usr/local/cuda-10.2/include/* /usr/local/cuda/include + sudo cp -r /usr/local/cuda-10.2/lib64/* /usr/local/cuda/lib64/ export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH} export PATH=${CUDA_HOME}/bin:${PATH} sudo apt-get install -y ninja-build From 15b37b0b787f7e2a8c62801964f0cd33de715c1d Mon Sep 17 00:00:00 2001 From: Wang Xinjiang Date: Wed, 2 Sep 2020 00:39:57 +0800 Subject: [PATCH 39/81] Allow imshow_det_bboxes to return image with bboxes. (#527) --- mmcv/visualization/image.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/mmcv/visualization/image.py b/mmcv/visualization/image.py index b2c472a5c4..05ad91e3a9 100644 --- a/mmcv/visualization/image.py +++ b/mmcv/visualization/image.py @@ -48,6 +48,9 @@ def imshow_bboxes(img, win_name (str): The window name. wait_time (int): Value of waitKey param. out_file (str, optional): The filename to write the image. + + Returns: + ndarray: The image with bboxes drawn on it. """ img = imread(img) @@ -74,6 +77,7 @@ def imshow_bboxes(img, imshow(img, win_name, wait_time) if out_file is not None: imwrite(img, out_file) + return img def imshow_det_bboxes(img, @@ -106,6 +110,9 @@ def imshow_det_bboxes(img, win_name (str): The window name. wait_time (int): Value of waitKey param. out_file (str or None): The filename to write the image. + + Returns: + ndarray: The image with bboxes drawn on it. """ assert bboxes.ndim == 2 assert labels.ndim == 1 @@ -140,3 +147,4 @@ def imshow_det_bboxes(img, imshow(img, win_name, wait_time) if out_file is not None: imwrite(img, out_file) + return img From 06556c8459202370776f085af4b0a003ae266f58 Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Wed, 2 Sep 2020 10:57:36 +0800 Subject: [PATCH 40/81] Add shear augmentation (#526) * Add shear augmentation * Update geometric.py * Update geometric.py --- mmcv/image/__init__.py | 5 ++- mmcv/image/geometric.py | 64 ++++++++++++++++++++++++++++++ tests/test_image/test_geometric.py | 41 +++++++++++++++++++ 3 files changed, 108 insertions(+), 2 deletions(-) diff --git a/mmcv/image/__init__.py b/mmcv/image/__init__.py index 044da42a8d..9c89c82169 100644 --- a/mmcv/image/__init__.py +++ b/mmcv/image/__init__.py @@ -3,7 +3,7 @@ gray2bgr, gray2rgb, hls2bgr, hsv2bgr, imconvert, rgb2bgr, rgb2gray, rgb2ycbcr, ycbcr2bgr, ycbcr2rgb) from .geometric import (imcrop, imflip, imflip_, impad, impad_to_multiple, - imrescale, imresize, imresize_like, imrotate, + imrescale, imresize, imresize_like, imrotate, imshear, rescale_size) from .io import imfrombytes, imread, imwrite, supported_backends, use_backend from .misc import tensor2imgs @@ -17,5 +17,6 @@ 'impad', 'impad_to_multiple', 'imrotate', 'imfrombytes', 'imread', 'imwrite', 'supported_backends', 'use_backend', 'imdenormalize', 'imnormalize', 'imnormalize_', 'iminvert', 'posterize', 'solarize', - 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs' + 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs', + 'imshear' ] diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index 42afc8cbca..d0dc184684 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -460,3 +460,67 @@ def impad_to_multiple(img, divisor, pad_val=0): pad_h = int(np.ceil(img.shape[0] / divisor)) * divisor pad_w = int(np.ceil(img.shape[1] / divisor)) * divisor return impad(img, shape=(pad_h, pad_w)) + + +def _get_shear_matrix(magnitude, direction='horizontal'): + """Generate the shear matrix for transformation. + + Args: + magnitude (int | float): The magnitude used for shear. + direction (str): Thie flip direction, either "horizontal" + or "vertical". + + Returns: + ndarray: The shear matrix with dtype float32. + """ + if direction == 'horizontal': + shear_matrix = np.float32([[1, magnitude, 0], [0, 1, 0]]) + elif direction == 'vertical': + shear_matrix = np.float32([[1, 0, 0], [magnitude, 1, 0]]) + return shear_matrix + + +def imshear(img, + magnitude, + direction='horizontal', + border_value=0, + interpolation='bilinear'): + """Shear an image. + + Args: + img (ndarray): Image to be sheared with format (h, w) + or (h, w, c). + magnitude (int | float): The magnitude used for shear. + direction (str): Thie flip direction, either "horizontal" + or "vertical". + border_value (int | tuple[int]): Value used in case of a + constant border. + interpolation (str): Same as :func:`resize`. + + Returns: + ndarray: The sheared image. + """ + assert direction in ['horizontal', + 'vertical'], f'Invalid direction: {direction}' + height, width = img.shape[:2] + if img.ndim == 2: + channels = 1 + elif img.ndim == 3: + channels = img.shape[-1] + if isinstance(border_value, int): + border_value = tuple([border_value] * channels) + elif isinstance(border_value, tuple): + assert len(border_value) == channels, \ + 'Expected the num of elements in tuple equals the channels' \ + 'of input image. Found {} vs {}'.format( + len(border_value), channels) + else: + raise ValueError( + f'Invalid type {type(border_value)} for `border_value`') + shear_matrix = _get_shear_matrix(magnitude, direction) + sheared = cv2.warpAffine( + img, + shear_matrix, (width, height), + borderValue=border_value, + flags=cv2_interp_codes[interpolation]) + return sheared diff --git a/tests/test_image/test_geometric.py b/tests/test_image/test_geometric.py index 9a1c9b1c86..81b4a7659b 100644 --- a/tests/test_image/test_geometric.py +++ b/tests/test_image/test_geometric.py @@ -443,3 +443,44 @@ def test_imrotate(self): with pytest.raises(ValueError): mmcv.imrotate(img, 90, center=(0, 0), auto_bound=True) + + def test_imshear(self): + img = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]).astype(np.uint8) + assert_array_equal(mmcv.imshear(img, 0), img) + # magnitude=1, horizontal + img_sheared = np.array([[1, 2, 3], [0, 4, 5], [0, 0, 7]], + dtype=np.uint8) + assert_array_equal(mmcv.imshear(img, 1), img_sheared) + # magnitude=-1, vertical + img_sheared = np.array([[1, 5, 9], [4, 8, 0], [7, 0, 0]], + dtype=np.uint8) + assert_array_equal(mmcv.imshear(img, -1, 'vertical'), img_sheared) + # magnitude=1, vertical, borderValue=100 + borderValue = 100 + img_sheared = np.array( + [[1, borderValue, borderValue], [4, 2, borderValue], [7, 5, 3]], + dtype=np.uint8) + assert_array_equal( + mmcv.imshear(img, 1, 'vertical', borderValue), img_sheared) + # magnitude=1, vertical, borderValue=100, img shape (h,w,3) + img = np.stack([img, img, img], axis=-1) + img_sheared = np.stack([img_sheared, img_sheared, img_sheared], + axis=-1) + assert_array_equal( + mmcv.imshear(img, 1, 'vertical', borderValue), img_sheared) + # test tuple format of borderValue + assert_array_equal( + mmcv.imshear(img, 1, 'vertical', + (borderValue, borderValue, borderValue)), img_sheared) + + # test invalid length of borderValue + with pytest.raises(AssertionError): + mmcv.imshear(img, 0.5, 'horizontal', (borderValue, )) + + # test invalid type of borderValue + with pytest.raises(ValueError): + mmcv.imshear(img, 0.5, 'horizontal', [borderValue]) + + # test invalid value of direction + with pytest.raises(AssertionError): + mmcv.imshear(img, 0.5, 'diagonal') From cfd337bb222c66b6c90367966b455adf9689b2b0 Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Wed, 2 Sep 2020 19:27:47 +0800 Subject: [PATCH 41/81] Support load with mmcls:// (#511) * [Feature] Support load models from mmcls * [Feature] Support load with mmcls:// * hard-code load mmcls * fixed wrong commit * add json * remove cifar --- MANIFEST.in | 2 +- mmcv/model_zoo/mmcls.json | 13 +++++++++++++ mmcv/runner/checkpoint.py | 23 +++++++++++++++++++++++ 3 files changed, 37 insertions(+), 1 deletion(-) create mode 100644 mmcv/model_zoo/mmcls.json diff --git a/MANIFEST.in b/MANIFEST.in index a6ef0b80a6..dc9dca578f 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,6 +1,6 @@ include mmcv/video/optflow_warp/*.hpp mmcv/video/optflow_warp/*.pyx include requirements.txt -include mmcv/model_zoo/open_mmlab.json mmcv/model_zoo/deprecated.json +include mmcv/model_zoo/open_mmlab.json mmcv/model_zoo/deprecated.json mmcv/model_zoo/mmcls.json include mmcv/ops/csrc/*.cuh mmcv/ops/csrc/*.hpp include mmcv/ops/csrc/pytorch/*.cu mmcv/ops/csrc/pytorch/*.cpp include mmcv/ops/csrc/parrots/*.cu mmcv/ops/csrc/parrots/*.cpp diff --git a/mmcv/model_zoo/mmcls.json b/mmcv/model_zoo/mmcls.json new file mode 100644 index 0000000000..9c16857a4a --- /dev/null +++ b/mmcv/model_zoo/mmcls.json @@ -0,0 +1,13 @@ +{ + "resnet50_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d50_batch256_20200708-1ad0ce94.pth", + "resnet101_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d101_batch256_20200708-9cb302ef.pth", + "resnet152_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d152_batch256_20200708-e79cb6a2.pth", + "resnext50": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext50_32x4d_batch256_20200708-c07adbb7.pth", + "resnext101": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext101_32x8d_batch256_20200708-1ec34aa7.pth", + "resnext152": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext152_32x4d_batch256_20200708-aab5034c.pth", + "se-resnet50": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/se-resnet50_batch256_20200804-ae206104.pth", + "se-resnet101": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/se-resnet101_batch256_20200804-ba5b51d4.pth", + "shufflenet_v1": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/shufflenet_v1_batch1024_20200804-5d6cec73.pth", + "shufflenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/shufflenet_v2_batch1024_20200812-5bf4721e.pth", + "mobilenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/mobilenet_v2_batch256_20200708-3b2dc3af.pth" +} diff --git a/mmcv/runner/checkpoint.py b/mmcv/runner/checkpoint.py index 4351addb82..ddb9f23b8c 100644 --- a/mmcv/runner/checkpoint.py +++ b/mmcv/runner/checkpoint.py @@ -142,6 +142,13 @@ def get_external_models(): return default_urls +def get_mmcls_models(): + mmcls_json_path = osp.join(mmcv.__path__[0], 'model_zoo/mmcls.json') + mmcls_urls = load_file(mmcls_json_path) + + return mmcls_urls + + def get_deprecated_model_names(): deprecate_json_path = osp.join(mmcv.__path__[0], 'model_zoo/deprecated.json') @@ -151,6 +158,17 @@ def get_deprecated_model_names(): return deprecate_urls +def _process_mmcls_checkpoint(checkpoint): + state_dict = checkpoint['state_dict'] + new_state_dict = OrderedDict() + for k, v in state_dict.items(): + if k.startswith('backbone.'): + new_state_dict[k[9:]] = v + new_checkpoint = dict(state_dict=new_state_dict) + + return new_checkpoint + + def _load_checkpoint(filename, map_location=None): """Load checkpoint from somewhere (modelzoo, file, url). @@ -192,6 +210,11 @@ def _load_checkpoint(filename, map_location=None): if not osp.isfile(filename): raise IOError(f'{filename} is not a checkpoint file') checkpoint = torch.load(filename, map_location=map_location) + elif filename.startswith('mmcls://'): + model_urls = get_mmcls_models() + model_name = filename[8:] + checkpoint = load_url_dist(model_urls[model_name]) + checkpoint = _process_mmcls_checkpoint(checkpoint) elif filename.startswith(('http://', 'https://')): checkpoint = load_url_dist(filename) else: From 8dfe58d197993c1c4765b84c84efee1eff8f4459 Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Thu, 3 Sep 2020 17:14:49 +0800 Subject: [PATCH 42/81] Fix TypeError: Scalar value for argument borderValue is longer than 4 (#535) * fix TypeError: Scalar value for argument borderValue is longer than 4 * add comments for imshear with case that border_value has more than 3 elements --- mmcv/image/geometric.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index d0dc184684..7b3425ac83 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -520,7 +520,12 @@ def imshear(img, shear_matrix = _get_shear_matrix(magnitude, direction) sheared = cv2.warpAffine( img, - shear_matrix, (width, height), - borderValue=border_value, + shear_matrix, + (width, height), + # Note case when the number elements in `border_value` + # greater than 3 (e.g. shearing masks whose channels large + # than 3) will raise TypeError in `cv2.warpAffine`. + # Here simply slice the first 3 values in `border_value`. + borderValue=border_value[:3], flags=cv2_interp_codes[interpolation]) return sheared From fe07f09e0ae849027a5294e0334862a6debfa2fc Mon Sep 17 00:00:00 2001 From: Wang Xinjiang Date: Thu, 3 Sep 2020 19:28:45 +0800 Subject: [PATCH 43/81] Add more default types for json dump (#536) --- mmcv/fileio/handlers/json_handler.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/mmcv/fileio/handlers/json_handler.py b/mmcv/fileio/handlers/json_handler.py index 7da9020918..d92c397f14 100644 --- a/mmcv/fileio/handlers/json_handler.py +++ b/mmcv/fileio/handlers/json_handler.py @@ -10,12 +10,16 @@ def set_default(obj): """Set default json values for non-serializable values. It helps convert ``set``, ``range`` and ``np.ndarray`` data types to list. + It also converts ``np.generic`` (including ``np.int32``, ``np.float32``, + etc.) into plain numbers of plain python built-in types. """ if isinstance(obj, (set, range)): return list(obj) elif isinstance(obj, np.ndarray): return obj.tolist() - raise TypeError + elif isinstance(obj, np.generic): + return obj.item() + raise TypeError(f'{type(obj)} is unsupported for json dump') class JsonHandler(BaseFileHandler): From 0664f9b3ede1a30bc920ef79d2b2ee786adff5d6 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Thu, 3 Sep 2020 21:30:13 +0800 Subject: [PATCH 44/81] bump version to 1.1.2 (#537) --- mmcv/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/version.py b/mmcv/version.py index b4b3f99684..1b986d4830 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,6 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.1.1' +__version__ = '1.1.2' def parse_version_info(version_str): From 16071ed0110b6f6a1c6836def880f6f4b52454c2 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Fri, 4 Sep 2020 15:05:14 +0800 Subject: [PATCH 45/81] [Fix]: fix missing pad_val in impad_to_multiple (#539) --- mmcv/image/geometric.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index 7b3425ac83..5bad546a28 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -459,7 +459,7 @@ def impad_to_multiple(img, divisor, pad_val=0): """ pad_h = int(np.ceil(img.shape[0] / divisor)) * divisor pad_w = int(np.ceil(img.shape[1] / divisor)) * divisor - return impad(img, shape=(pad_h, pad_w)) + return impad(img, shape=(pad_h, pad_w), pad_val=pad_val) def _get_shear_matrix(magnitude, direction='horizontal'): From c6987937fe11bb6c7bc7dde2f22328a968091b9e Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Fri, 4 Sep 2020 15:08:12 +0800 Subject: [PATCH 46/81] [fix] Fix compilation bug in windows and add instruction for windows (#540) * Add windows instruction and fix compilation bug * reformat codebase --- README.md | 13 +++++++++++++ mmcv/ops/csrc/pytorch/focal_loss_cuda.cu | 12 ++++++++---- 2 files changed, 21 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index fe22efc91d..cb9f8bfdcc 100644 --- a/README.md +++ b/README.md @@ -131,6 +131,19 @@ e.g., CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e . ``` +If you are on Windows10, set the following environment variable before the installing command. + +```bash +set MMCV_WITH_OPS=1 +``` + +e.g., + +```bash +set MMCV_WITH_OPS=1 +pip install -e . +``` + Note: If you would like to use `opencv-python-headless` instead of `opencv-python`, e.g., in a minimum container environment or servers without GUI, you can first install it before installing MMCV to skip the installation of `opencv-python`. diff --git a/mmcv/ops/csrc/pytorch/focal_loss_cuda.cu b/mmcv/ops/csrc/pytorch/focal_loss_cuda.cu index 508f449ba3..c7cd215f5d 100644 --- a/mmcv/ops/csrc/pytorch/focal_loss_cuda.cu +++ b/mmcv/ops/csrc/pytorch/focal_loss_cuda.cu @@ -8,7 +8,7 @@ void SigmoidFocalLossForwardCUDAKernelLauncher(Tensor input, Tensor target, const float alpha) { int output_size = output.numel(); int num_classes = input.size(1); - AT_ASSERTM(target.max().item() <= (long)num_classes, + AT_ASSERTM(target.max().item() <= (int64_t)num_classes, "target label should smaller or equal than num classes"); at::cuda::CUDAGuard device_guard(input.device()); cudaStream_t stream = at::cuda::getCurrentCUDAStream(); @@ -53,7 +53,7 @@ void SoftmaxFocalLossForwardCUDAKernelLauncher(Tensor softmax, Tensor target, int output_size = output.numel(); int num_classes = softmax.size(1); - AT_ASSERTM(target.max().item() <= (long)num_classes, + AT_ASSERTM(target.max().item() <= (int64_t)num_classes, "target label should smaller or equal than num classes"); at::cuda::CUDAGuard device_guard(softmax.device()); cudaStream_t stream = at::cuda::getCurrentCUDAStream(); @@ -80,7 +80,9 @@ void SoftmaxFocalLossBackwardCUDAKernelLauncher(Tensor softmax, Tensor target, at::cuda::CUDAGuard device_guard(grad_input.device()); cudaStream_t stream = at::cuda::getCurrentCUDAStream(); AT_DISPATCH_FLOATING_TYPES_AND_HALF( - grad_input.scalar_type(), "softmax_focal_loss_backward_cuda1_kernel", + grad_input.scalar_type(), + "softmax_focal_loss_backward_cuda1_" + "kernel", [&] { softmax_focal_loss_backward_cuda1_kernel <<>>( @@ -93,7 +95,9 @@ void SoftmaxFocalLossBackwardCUDAKernelLauncher(Tensor softmax, Tensor target, output_size = grad_input.numel(); AT_DISPATCH_FLOATING_TYPES_AND_HALF( - grad_input.scalar_type(), "softmax_focal_loss_backward_cuda2_kernel", + grad_input.scalar_type(), + "softmax_focal_loss_backward_cuda2_" + "kernel", [&] { softmax_focal_loss_backward_cuda2_kernel <<>>( From 9769024fbd967afa53774910e7b11d43a00ffe86 Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Fri, 4 Sep 2020 20:30:42 +0800 Subject: [PATCH 47/81] Add Translate augmentation. (#538) * add imtranslate * add imtranslate * update comments * reformat --- mmcv/image/__init__.py | 4 +- mmcv/image/geometric.py | 69 ++++++++++++++++++++++++++++++ tests/test_image/test_geometric.py | 41 ++++++++++++++++++ 3 files changed, 112 insertions(+), 2 deletions(-) diff --git a/mmcv/image/__init__.py b/mmcv/image/__init__.py index 9c89c82169..49a19ca397 100644 --- a/mmcv/image/__init__.py +++ b/mmcv/image/__init__.py @@ -4,7 +4,7 @@ rgb2bgr, rgb2gray, rgb2ycbcr, ycbcr2bgr, ycbcr2rgb) from .geometric import (imcrop, imflip, imflip_, impad, impad_to_multiple, imrescale, imresize, imresize_like, imrotate, imshear, - rescale_size) + imtranslate, rescale_size) from .io import imfrombytes, imread, imwrite, supported_backends, use_backend from .misc import tensor2imgs from .photometric import (imdenormalize, iminvert, imnormalize, imnormalize_, @@ -18,5 +18,5 @@ 'imwrite', 'supported_backends', 'use_backend', 'imdenormalize', 'imnormalize', 'imnormalize_', 'iminvert', 'posterize', 'solarize', 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs', - 'imshear' + 'imshear', 'imtranslate' ] diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index 5bad546a28..aed743f657 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -529,3 +529,72 @@ def imshear(img, borderValue=border_value[:3], flags=cv2_interp_codes[interpolation]) return sheared + + +def _get_translate_matrix(offset, direction='horizontal'): + """Generate the translate matrix. + + Args: + offset (int | float): The offset used for translate. + direction (str): The translate direction, either + "horizontal" or "vertical". + + Returns: + ndarray: The translate matrix with dtype float32. + """ + if direction == 'horizontal': + translate_matrix = np.float32([[1, 0, offset], [0, 1, 0]]) + elif direction == 'vertical': + translate_matrix = np.float32([[1, 0, 0], [0, 1, offset]]) + return translate_matrix + + +def imtranslate(img, + offset, + direction='horizontal', + border_value=0, + interpolation='bilinear'): + """Translate an image. + + Args: + img (ndarray): Image to be translated with format + (h, w) or (h, w, c). + offset (int | float): The offset used for translate. + direction (str): The translate direction, either "horizontal" + or "vertical". + border_value (int | tuple[int]): Value used in case of a + constant border. + interpolation (str): Same as :func:`resize`. + + Returns: + ndarray: The translated image. + """ + assert direction in ['horizontal', + 'vertical'], f'Invalid direction: {direction}' + height, width = img.shape[:2] + if img.ndim == 2: + channels = 1 + elif img.ndim == 3: + channels = img.shape[-1] + if isinstance(border_value, int): + border_value = tuple([border_value] * channels) + elif isinstance(border_value, tuple): + assert len(border_value) == channels, \ + 'Expected the num of elements in tuple equals the channels' \ + 'of input image. Found {} vs {}'.format( + len(border_value), channels) + else: + raise ValueError( + f'Invalid type {type(border_value)} for `border_value`.') + translate_matrix = _get_translate_matrix(offset, direction) + translated = cv2.warpAffine( + img, + translate_matrix, + (width, height), + # Note case when the number elements in `border_value` + # greater than 3 (e.g. translating masks whose channels + # large than 3) will raise TypeError in `cv2.warpAffine`. + # Here simply slice the first 3 values in `border_value`. + borderValue=border_value[:3], + flags=cv2_interp_codes[interpolation]) + return translated diff --git a/tests/test_image/test_geometric.py b/tests/test_image/test_geometric.py index 81b4a7659b..586289002d 100644 --- a/tests/test_image/test_geometric.py +++ b/tests/test_image/test_geometric.py @@ -484,3 +484,44 @@ def test_imshear(self): # test invalid value of direction with pytest.raises(AssertionError): mmcv.imshear(img, 0.5, 'diagonal') + + def test_imtranslate(self): + img = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.uint8) + assert_array_equal(mmcv.imtranslate(img, 0), img) + # offset=1, horizontal + img_translated = np.array([[128, 1, 2], [128, 4, 5], [128, 7, 8]], + dtype=np.uint8) + assert_array_equal( + mmcv.imtranslate(img, 1, border_value=128), img_translated) + # offset=-1, vertical + img_translated = np.array([[4, 5, 6], [7, 8, 9], [0, 0, 0]], + dtype=np.uint8) + assert_array_equal( + mmcv.imtranslate(img, -1, 'vertical'), img_translated) + # offset=-2, horizontal + img = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + img_translated = [[3, 4, 128, 128], [7, 8, 128, 128]] + img_translated = np.stack( + [img_translated, img_translated, img_translated], axis=-1) + assert_array_equal( + mmcv.imtranslate(img, -2, border_value=128), img_translated) + # offset=2, vertical + border_value = (110, 120, 130) + img_translated = np.stack([ + np.ones((2, 4)) * border_value[0], + np.ones((2, 4)) * border_value[1], + np.ones((2, 4)) * border_value[2] + ], + axis=-1).astype(np.uint8) + assert_array_equal( + mmcv.imtranslate(img, 2, 'vertical', border_value), img_translated) + # test invalid number elements in border_value + with pytest.raises(AssertionError): + mmcv.imtranslate(img, 1, border_value=(1, )) + # test invalid type of border_value + with pytest.raises(ValueError): + mmcv.imtranslate(img, 1, border_value=[1, 2, 3]) + # test invalid value of direction + with pytest.raises(AssertionError): + mmcv.imtranslate(img, 1, 'diagonal') From fec7cd61d6fb690c9a565261851add1400f8ce14 Mon Sep 17 00:00:00 2001 From: Jintao Lin <528557675@qq.com> Date: Mon, 7 Sep 2020 00:52:33 +0800 Subject: [PATCH 48/81] Support reading video from url (#531) * add url support for VideoReader * add a comment * add unittest * use a connectable url for ci --- mmcv/video/io.py | 4 +++- tests/test_video/test_reader.py | 12 ++++++++++++ 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/mmcv/video/io.py b/mmcv/video/io.py index dfddcfd9d2..08b78cd586 100644 --- a/mmcv/video/io.py +++ b/mmcv/video/io.py @@ -62,7 +62,9 @@ class VideoReader: """ def __init__(self, filename, cache_capacity=10): - check_file_exist(filename, 'Video file not found: ' + filename) + # Check whether the video path is a url + if not filename.startswith(('https://', 'http://')): + check_file_exist(filename, 'Video file not found: ' + filename) self._vcap = cv2.VideoCapture(filename) assert cache_capacity > 0 self._cache = Cache(cache_capacity) diff --git a/tests/test_video/test_reader.py b/tests/test_video/test_reader.py index f986a85af4..0a21a38e13 100644 --- a/tests/test_video/test_reader.py +++ b/tests/test_video/test_reader.py @@ -45,8 +45,10 @@ class TestVideoReader: def setup_class(cls): cls.video_path = osp.join(osp.dirname(__file__), '../data/test.mp4') cls.num_frames = 168 + cls.video_url = 'https://www.learningcontainer.com/wp-content/uploads/2020/05/sample-mp4-file.mp4' # noqa: E501 def test_load(self): + # read from video file v = mmcv.VideoReader(self.video_path) assert v.width == 294 assert v.height == 240 @@ -57,6 +59,16 @@ def test_load(self): import cv2 assert isinstance(v.vcap, type(cv2.VideoCapture())) + # read from video url + v = mmcv.VideoReader(self.video_url) + assert v.width == 320 + assert v.height == 240 + assert v.fps == 15 + assert v.frame_cnt == 1889 + assert len(v) == 1889 + assert v.opened + assert isinstance(v.vcap, type(cv2.VideoCapture())) + def test_read(self): v = mmcv.VideoReader(self.video_path) img = v.read() From 95417a5d24ab041b1055ab01ba0ad80b5ea28a48 Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Tue, 8 Sep 2020 13:09:06 +0800 Subject: [PATCH 49/81] Supports Color augmentation. (#542) * add Color augmentation * reformat * reformat * reformat docstring * reformat docstring * add more unit test * add more unit test * add clip value and uint test for image with type float * rename function name --- mmcv/image/__init__.py | 6 +++--- mmcv/image/photometric.py | 32 ++++++++++++++++++++++++++++ tests/test_image/test_photometric.py | 31 +++++++++++++++++++++++++++ 3 files changed, 66 insertions(+), 3 deletions(-) diff --git a/mmcv/image/__init__.py b/mmcv/image/__init__.py index 49a19ca397..d2d4274ab4 100644 --- a/mmcv/image/__init__.py +++ b/mmcv/image/__init__.py @@ -7,8 +7,8 @@ imtranslate, rescale_size) from .io import imfrombytes, imread, imwrite, supported_backends, use_backend from .misc import tensor2imgs -from .photometric import (imdenormalize, iminvert, imnormalize, imnormalize_, - posterize, solarize) +from .photometric import (adjust_color, imdenormalize, iminvert, imnormalize, + imnormalize_, posterize, solarize) __all__ = [ 'bgr2gray', 'bgr2hls', 'bgr2hsv', 'bgr2rgb', 'gray2bgr', 'gray2rgb', @@ -18,5 +18,5 @@ 'imwrite', 'supported_backends', 'use_backend', 'imdenormalize', 'imnormalize', 'imnormalize_', 'iminvert', 'posterize', 'solarize', 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs', - 'imshear', 'imtranslate' + 'imshear', 'imtranslate', 'adjust_color' ] diff --git a/mmcv/image/photometric.py b/mmcv/image/photometric.py index 948936a209..9960e32bac 100644 --- a/mmcv/image/photometric.py +++ b/mmcv/image/photometric.py @@ -1,6 +1,8 @@ import cv2 import numpy as np +from .colorspace import bgr2gray + def imnormalize(img, mean, std, to_rgb=True): """Normalize an image with mean and std. @@ -91,3 +93,33 @@ def posterize(img, bits): shift = 8 - bits img = np.left_shift(np.right_shift(img, shift), shift) return img + + +def adjust_color(img, alpha=1, beta=None, gamma=0): + """It blends the source image and its gray image: + + ``output = img * alpha + gray_img * beta + gamma`` + + Args: + img (ndarray): The input source image. + alpha (int | float): Weight for the source image. Default 1. + beta (int | float): Weight for the converted gray image. + If None, it's assigned the value (1 - `alpha`). + gamma (int | float): Scalar added to each sum. + Same as :func:`cv2.addWeighted`. Default 0. + + Returns: + ndarray: Colored image which has the same size and dtype as input. + """ + gray_img = bgr2gray(img) + gray_img = np.tile(gray_img[..., None], [1, 1, 3]) + if beta is None: + beta = 1 - alpha + colored_img = cv2.addWeighted(img, alpha, gray_img, beta, gamma) + if not colored_img.dtype == np.uint8: + # Note when the dtype of `img` is not defaultly `np.uint8` + # (e.g. np.float32), the value in `colored_img` got from cv2 + # is not guaranteed to be in range [0, 255], so here clip + # is needed. + colored_img = np.clip(colored_img, 0, 255) + return colored_img diff --git a/tests/test_image/test_photometric.py b/tests/test_image/test_photometric.py index f2e86d450d..f1e55c7047 100644 --- a/tests/test_image/test_photometric.py +++ b/tests/test_image/test_photometric.py @@ -75,3 +75,34 @@ def test_posterize(self): img_r = np.array([[0, 128, 224], [0, 96, 224], [0, 128, 224]], dtype=np.uint8) assert_array_equal(mmcv.posterize(img, 3), img_r) + + def test_adjust_color(self): + img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]], + dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + assert_array_equal(mmcv.adjust_color(img), img) + img_gray = mmcv.bgr2gray(img) + img_r = np.stack([img_gray, img_gray, img_gray], axis=-1) + assert_array_equal(mmcv.adjust_color(img, 0), img_r) + assert_array_equal(mmcv.adjust_color(img, 0, 1), img_r) + assert_array_equal( + mmcv.adjust_color(img, 0.5, 0.5), + np.round(np.clip((img * 0.5 + img_r * 0.5), 0, + 255)).astype(img.dtype)) + assert_array_equal( + mmcv.adjust_color(img, 1, 1.5), + np.round(np.clip(img * 1 + img_r * 1.5, 0, 255)).astype(img.dtype)) + assert_array_equal( + mmcv.adjust_color(img, 0.8, -0.6, gamma=2), + np.round(np.clip(img * 0.8 - 0.6 * img_r + 2, 0, + 255)).astype(img.dtype)) + assert_array_equal( + mmcv.adjust_color(img, 0.8, -0.6, gamma=-0.6), + np.round(np.clip(img * 0.8 - 0.6 * img_r - 0.6, 0, + 255)).astype(img.dtype)) + + # test float type of image + img = img.astype(np.float32) + assert_array_equal( + np.round(mmcv.adjust_color(img, 0.8, -0.6, gamma=-0.6)), + np.round(np.clip(img * 0.8 - 0.6 * img_r - 0.6, 0, 255))) From a59a35bcced70516ac5ddc4e8542459319680165 Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Tue, 8 Sep 2020 14:44:14 +0800 Subject: [PATCH 50/81] Supports Equalize Augmentation. (#543) * add equalize augmentation in mmcv * delete unnecessary * reformat * remove clip in implementing equalize, and add uint test with case step=0 * remove clip in implementing equalize, and add uint test with case step=0 * add comments for unit test * rename function name as imequalize --- mmcv/image/__init__.py | 6 ++-- mmcv/image/photometric.py | 43 ++++++++++++++++++++++++++++ tests/test_image/test_photometric.py | 29 +++++++++++++++++++ 3 files changed, 75 insertions(+), 3 deletions(-) diff --git a/mmcv/image/__init__.py b/mmcv/image/__init__.py index d2d4274ab4..b32846c137 100644 --- a/mmcv/image/__init__.py +++ b/mmcv/image/__init__.py @@ -7,8 +7,8 @@ imtranslate, rescale_size) from .io import imfrombytes, imread, imwrite, supported_backends, use_backend from .misc import tensor2imgs -from .photometric import (adjust_color, imdenormalize, iminvert, imnormalize, - imnormalize_, posterize, solarize) +from .photometric import (adjust_color, imdenormalize, imequalize, iminvert, + imnormalize, imnormalize_, posterize, solarize) __all__ = [ 'bgr2gray', 'bgr2hls', 'bgr2hsv', 'bgr2rgb', 'gray2bgr', 'gray2rgb', @@ -18,5 +18,5 @@ 'imwrite', 'supported_backends', 'use_backend', 'imdenormalize', 'imnormalize', 'imnormalize_', 'iminvert', 'posterize', 'solarize', 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs', - 'imshear', 'imtranslate', 'adjust_color' + 'imshear', 'imtranslate', 'adjust_color', 'imequalize' ] diff --git a/mmcv/image/photometric.py b/mmcv/image/photometric.py index 9960e32bac..ea12294b3f 100644 --- a/mmcv/image/photometric.py +++ b/mmcv/image/photometric.py @@ -123,3 +123,46 @@ def adjust_color(img, alpha=1, beta=None, gamma=0): # is needed. colored_img = np.clip(colored_img, 0, 255) return colored_img + + +def imequalize(img): + """Equalize the image histogram. + + This function applies a non-linear mapping to the input image, + in order to create a uniform distribution of grayscale values + in the output image. + + Args: + img (ndarray): Image to be equalized. + + Returns: + ndarray: The equalized image. + """ + + def _scale_channel(im, c): + """Scale the data in the corresponding channel.""" + im = im[:, :, c] + # Compute the histogram of the image channel. + histo = np.histogram(im, 256, (0, 255))[0] + # For computing the step, filter out the nonzeros. + nonzero_histo = histo[histo > 0] + step = (np.sum(nonzero_histo) - nonzero_histo[-1]) // 255 + if not step: + lut = np.array(range(256)) + else: + # Compute the cumulative sum, shifted by step // 2 + # and then normalized by step. + lut = (np.cumsum(histo) + (step // 2)) // step + # Shift lut, prepending with 0. + lut = np.concatenate([[0], lut[:-1]], 0) + # If step is zero, return the original image. + # Otherwise, index from lut. + return np.where(np.equal(step, 0), im, lut[im]) + + # Scales each channel independently and then stacks + # the result. + s1 = _scale_channel(img, 0) + s2 = _scale_channel(img, 1) + s3 = _scale_channel(img, 2) + equalized_img = np.stack([s1, s2, s3], axis=-1) + return equalized_img diff --git a/tests/test_image/test_photometric.py b/tests/test_image/test_photometric.py index f1e55c7047..efa89046ba 100644 --- a/tests/test_image/test_photometric.py +++ b/tests/test_image/test_photometric.py @@ -106,3 +106,32 @@ def test_adjust_color(self): assert_array_equal( np.round(mmcv.adjust_color(img, 0.8, -0.6, gamma=-0.6)), np.round(np.clip(img * 0.8 - 0.6 * img_r - 0.6, 0, 255))) + + def test_imequalize(self, nb_rand_test=100): + + def _imequalize(img): + # equalize the image using PIL.ImageOps.equalize + from PIL import ImageOps, Image + img = Image.fromarray(img) + equalized_img = np.asarray(ImageOps.equalize(img)) + return equalized_img + + img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]], + dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + equalized_img = mmcv.imequalize(img) + assert_array_equal(equalized_img, _imequalize(img)) + + # test equalize with case step=0 + img = np.array([[0, 0, 0], [120, 120, 120], [255, 255, 255]], + dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + assert_array_equal(mmcv.imequalize(img), img) + + # test equalize with randomly sampled image. + for _ in range(nb_rand_test): + img = np.clip( + np.random.uniform(0, 1, (1000, 1200, 3)) * 260, 0, + 255).astype(np.uint8) + equalized_img = mmcv.imequalize(img) + assert_array_equal(equalized_img, _imequalize(img)) From c8435966ede1192c4cb166165080834e2bd075d6 Mon Sep 17 00:00:00 2001 From: su Date: Tue, 8 Sep 2020 18:00:33 +0800 Subject: [PATCH 51/81] Reordered the hooks and use attributes rather than args. (#544) * Reordered the hooks and use attributes rather than args. Formated. * Reordering may cause conflict, assign the value first than update such as max_iter Rewind back the order. * Rewind back to just use attributes, the update of max_iter and stuff will be done in new hooks. Minor format. --- mmcv/runner/epoch_based_runner.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py index aec827f3be..1912accded 100644 --- a/mmcv/runner/epoch_based_runner.py +++ b/mmcv/runner/epoch_based_runner.py @@ -99,10 +99,11 @@ def run(self, data_loaders, workflow, max_epochs, **kwargs): work_dir = self.work_dir if self.work_dir is not None else 'NONE' self.logger.info('Start running, host: %s, work_dir: %s', get_host_info(), work_dir) - self.logger.info('workflow: %s, max: %d epochs', workflow, max_epochs) + self.logger.info('workflow: %s, max: %d epochs', workflow, + self._max_epochs) self.call_hook('before_run') - while self.epoch < max_epochs: + while self.epoch < self._max_epochs: for i, flow in enumerate(workflow): mode, epochs = flow if isinstance(mode, str): # self.train() @@ -117,7 +118,7 @@ def run(self, data_loaders, workflow, max_epochs, **kwargs): type(mode))) for _ in range(epochs): - if mode == 'train' and self.epoch >= max_epochs: + if mode == 'train' and self.epoch >= self._max_epochs: break epoch_runner(data_loaders[i], **kwargs) From d7c895a361b896038339eddd04da8c6517f409a1 Mon Sep 17 00:00:00 2001 From: Hongkai Zhang Date: Wed, 9 Sep 2020 23:54:01 +0800 Subject: [PATCH 52/81] support multiple interpolation modes for imrotate (#545) * support multiple interpolation modes for imrotate * reformat code --- mmcv/image/geometric.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py index aed743f657..bedfceb73b 100644 --- a/mmcv/image/geometric.py +++ b/mmcv/image/geometric.py @@ -227,6 +227,7 @@ def imrotate(img, center=None, scale=1.0, border_value=0, + interpolation='bilinear', auto_bound=False): """Rotate an image. @@ -239,6 +240,7 @@ def imrotate(img, used. scale (float): Isotropic scale factor. border_value (int): Border value. + interpolation (str): Same as :func:`resize`. auto_bound (bool): Whether to adjust the image size to cover the whole rotated image. @@ -262,7 +264,11 @@ def imrotate(img, matrix[1, 2] += (new_h - h) * 0.5 w = int(np.round(new_w)) h = int(np.round(new_h)) - rotated = cv2.warpAffine(img, matrix, (w, h), borderValue=border_value) + rotated = cv2.warpAffine( + img, + matrix, (w, h), + flags=cv2_interp_codes[interpolation], + borderValue=border_value) return rotated From 49e32c2688da7cc26cf295768a39a8559975ab44 Mon Sep 17 00:00:00 2001 From: Xiaojie Li Date: Wed, 9 Sep 2020 23:57:48 +0800 Subject: [PATCH 53/81] Implementation of 2D convolution in tensorflow with `padding` as "same" (#529) * update impad * fix docstring * add shape for impad * fix unit test * remove old version & fix doc * fix linting * fix doc * add linear decay learning rate scheduler * fix impad * fix setup.cfg * fix linting * add yapf * add swish * fix lr_updater * fix lr_updater.py * update swish * add swish * fix inplace * fix typo * update * add same padding * fix docstring * add unittest * fix register * change name Co-authored-by: lixiaojie --- mmcv/cnn/bricks/__init__.py | 4 +- mmcv/cnn/bricks/conv2d_adaptive_padding.py | 61 +++++++++++++++++++ .../test_cnn/test_conv2d_adaptive_padding.py | 27 ++++++++ 3 files changed, 91 insertions(+), 1 deletion(-) create mode 100644 mmcv/cnn/bricks/conv2d_adaptive_padding.py create mode 100644 tests/test_cnn/test_conv2d_adaptive_padding.py diff --git a/mmcv/cnn/bricks/__init__.py b/mmcv/cnn/bricks/__init__.py index 781f7e1206..1266316524 100644 --- a/mmcv/cnn/bricks/__init__.py +++ b/mmcv/cnn/bricks/__init__.py @@ -1,6 +1,7 @@ from .activation import build_activation_layer from .context_block import ContextBlock from .conv import build_conv_layer +from .conv2d_adaptive_padding import Conv2dAdaptivePadding from .conv_module import ConvModule from .conv_ws import ConvAWS2d, ConvWS2d, conv_ws_2d from .depthwise_separable_conv_module import DepthwiseSeparableConvModule @@ -24,5 +25,6 @@ 'NonLocal2d', 'NonLocal3d', 'ContextBlock', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'ConvAWS2d', 'ConvWS2d', - 'conv_ws_2d', 'DepthwiseSeparableConvModule', 'Swish' + 'conv_ws_2d', 'DepthwiseSeparableConvModule', 'Swish', + 'Conv2dAdaptivePadding' ] diff --git a/mmcv/cnn/bricks/conv2d_adaptive_padding.py b/mmcv/cnn/bricks/conv2d_adaptive_padding.py new file mode 100644 index 0000000000..1143d25f3e --- /dev/null +++ b/mmcv/cnn/bricks/conv2d_adaptive_padding.py @@ -0,0 +1,61 @@ +import math + +from torch import nn +from torch.nn import functional as F + +from .registry import CONV_LAYERS + + +@CONV_LAYERS.register_module() +class Conv2dAdaptivePadding(nn.Conv2d): + """ Implementation of 2D convolution in tensorflow with `padding` as + "same", which applies padding to input (if needed) so that input image + gets fully covered by filter and stride you specified. For stride 1, this + will ensure that output image size is same as input. For stride of 2, + output dimensions will be half, for example. + + Args: + in_channels (int): Number of channels in the input image + out_channels (int): Number of channels produced by the convolution + kernel_size (int or tuple): Size of the convolving kernel + stride (int or tuple, optional): Stride of the convolution. Default: 1 + padding (int or tuple, optional): Zero-padding added to both sides of + the input. Default: 0 + dilation (int or tuple, optional): Spacing between kernel elements. + Default: 1 + groups (int, optional): Number of blocked connections from input + channels to output channels. Default: 1 + bias (bool, optional): If ``True``, adds a learnable bias to the + output. Default: ``True`` + """ + + def __init__(self, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + dilation=1, + groups=1, + bias=True): + super().__init__(in_channels, out_channels, kernel_size, stride, 0, + dilation, groups, bias) + + def forward(self, x): + img_h, img_w = x.size()[-2:] + kernel_h, kernel_w = self.weight.size()[-2:] + stride_h, stride_w = self.stride + output_h = math.ceil(img_h / stride_h) + output_w = math.ceil(img_w / stride_w) + pad_h = ( + max((output_h - 1) * self.stride[0] + + (kernel_h - 1) * self.dilation[0] + 1 - img_h, 0)) + pad_w = ( + max((output_w - 1) * self.stride[1] + + (kernel_w - 1) * self.dilation[1] + 1 - img_w, 0)) + if pad_h > 0 or pad_w > 0: + x = F.pad(x, [ + pad_w // 2, pad_w - pad_w // 2, pad_h // 2, pad_h - pad_h // 2 + ]) + return F.conv2d(x, self.weight, self.bias, self.stride, self.padding, + self.dilation, self.groups) diff --git a/tests/test_cnn/test_conv2d_adaptive_padding.py b/tests/test_cnn/test_conv2d_adaptive_padding.py new file mode 100644 index 0000000000..051d6e585c --- /dev/null +++ b/tests/test_cnn/test_conv2d_adaptive_padding.py @@ -0,0 +1,27 @@ +import torch + +from mmcv.cnn.bricks import Conv2dAdaptivePadding + + +def test_conv2d_samepadding(): + # test Conv2dAdaptivePadding with stride=1 + inputs = torch.rand((1, 3, 28, 28)) + conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=1) + output = conv(inputs) + assert output.shape == inputs.shape + + inputs = torch.rand((1, 3, 13, 13)) + conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=1) + output = conv(inputs) + assert output.shape == inputs.shape + + # test Conv2dAdaptivePadding with stride=2 + inputs = torch.rand((1, 3, 28, 28)) + conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=2) + output = conv(inputs) + assert output.shape == torch.Size([1, 3, 14, 14]) + + inputs = torch.rand((1, 3, 13, 13)) + conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=2) + output = conv(inputs) + assert output.shape == torch.Size([1, 3, 7, 7]) From c054a2393ef6d47db727c45975085cc9738a19fe Mon Sep 17 00:00:00 2001 From: Cao Yuhang Date: Sat, 12 Sep 2020 16:51:44 +0800 Subject: [PATCH 54/81] remove assertion (#549) --- mmcv/parallel/collate.py | 1 - 1 file changed, 1 deletion(-) diff --git a/mmcv/parallel/collate.py b/mmcv/parallel/collate.py index 1bcab66c45..21155cbb89 100644 --- a/mmcv/parallel/collate.py +++ b/mmcv/parallel/collate.py @@ -24,7 +24,6 @@ def collate(batch, samples_per_gpu=1): raise TypeError(f'{batch.dtype} is not supported.') if isinstance(batch[0], DataContainer): - assert len(batch) % samples_per_gpu == 0 stacked = [] if batch[0].cpu_only: for i in range(0, len(batch), samples_per_gpu): From c937d3953dcf229b2f4047c15a469eee293a00a0 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Sat, 12 Sep 2020 21:59:17 +0800 Subject: [PATCH 55/81] Mv wrappers into bricks and use wrappers in registry (#550) * Mv wrappers into bricks and use wrappers in registry * resolve import issues * fix import issues * set nn op forward to torch 1.6.1 * fix CI bug and add warning * Fix CI by using patch mock * mv warnings inside deprecated module's initialization --- mmcv/cnn/__init__.py | 12 +++--- mmcv/cnn/bricks/__init__.py | 5 ++- mmcv/cnn/bricks/upsample.py | 1 - mmcv/{ops => cnn/bricks}/wrappers.py | 6 ++- mmcv/ops/__init__.py | 5 ++- mmcv/ops/deprecated_wrappers.py | 42 +++++++++++++++++++ tests/{test_ops => test_cnn}/test_wrappers.py | 10 +++-- 7 files changed, 66 insertions(+), 15 deletions(-) rename mmcv/{ops => cnn/bricks}/wrappers.py (93%) create mode 100644 mmcv/ops/deprecated_wrappers.py rename tests/{test_ops => test_cnn}/test_wrappers.py (96%) diff --git a/mmcv/cnn/__init__.py b/mmcv/cnn/__init__.py index 5fa25a2e48..3c5fff71dd 100644 --- a/mmcv/cnn/__init__.py +++ b/mmcv/cnn/__init__.py @@ -2,10 +2,11 @@ from .alexnet import AlexNet from .bricks import (ACTIVATION_LAYERS, CONV_LAYERS, NORM_LAYERS, PADDING_LAYERS, PLUGIN_LAYERS, UPSAMPLE_LAYERS, - ContextBlock, ConvAWS2d, ConvModule, ConvWS2d, - DepthwiseSeparableConvModule, GeneralizedAttention, - HSigmoid, HSwish, NonLocal1d, NonLocal2d, NonLocal3d, - Scale, Swish, build_activation_layer, build_conv_layer, + ContextBlock, Conv2d, ConvAWS2d, ConvModule, + ConvTranspose2d, ConvWS2d, DepthwiseSeparableConvModule, + GeneralizedAttention, HSigmoid, HSwish, Linear, MaxPool2d, + NonLocal1d, NonLocal2d, NonLocal3d, Scale, Swish, + build_activation_layer, build_conv_layer, build_norm_layer, build_padding_layer, build_plugin_layer, build_upsample_layer, conv_ws_2d, is_norm) from .resnet import ResNet, make_res_layer @@ -24,5 +25,6 @@ 'HSigmoid', 'Swish', 'HSwish', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'get_model_complexity_info', 'conv_ws_2d', - 'ConvAWS2d', 'ConvWS2d', 'fuse_conv_bn', 'DepthwiseSeparableConvModule' + 'ConvAWS2d', 'ConvWS2d', 'fuse_conv_bn', 'DepthwiseSeparableConvModule', + 'Linear', 'Conv2d', 'ConvTranspose2d', 'MaxPool2d' ] diff --git a/mmcv/cnn/bricks/__init__.py b/mmcv/cnn/bricks/__init__.py index 1266316524..a685a6eb8c 100644 --- a/mmcv/cnn/bricks/__init__.py +++ b/mmcv/cnn/bricks/__init__.py @@ -17,6 +17,7 @@ from .scale import Scale from .swish import Swish from .upsample import build_upsample_layer +from .wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d __all__ = [ 'ConvModule', 'build_activation_layer', 'build_conv_layer', @@ -25,6 +26,6 @@ 'NonLocal2d', 'NonLocal3d', 'ContextBlock', 'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale', 'ConvAWS2d', 'ConvWS2d', - 'conv_ws_2d', 'DepthwiseSeparableConvModule', 'Swish', - 'Conv2dAdaptivePadding' + 'conv_ws_2d', 'DepthwiseSeparableConvModule', 'Swish', 'Linear', + 'Conv2dAdaptivePadding', 'Conv2d', 'ConvTranspose2d', 'MaxPool2d' ] diff --git a/mmcv/cnn/bricks/upsample.py b/mmcv/cnn/bricks/upsample.py index c029a439c1..c1388c39bf 100644 --- a/mmcv/cnn/bricks/upsample.py +++ b/mmcv/cnn/bricks/upsample.py @@ -6,7 +6,6 @@ UPSAMPLE_LAYERS.register_module('nearest', module=nn.Upsample) UPSAMPLE_LAYERS.register_module('bilinear', module=nn.Upsample) -UPSAMPLE_LAYERS.register_module('deconv', module=nn.ConvTranspose2d) @UPSAMPLE_LAYERS.register_module(name='pixel_shuffle') diff --git a/mmcv/ops/wrappers.py b/mmcv/cnn/bricks/wrappers.py similarity index 93% rename from mmcv/ops/wrappers.py rename to mmcv/cnn/bricks/wrappers.py index 248b0485ad..338bcb6851 100644 --- a/mmcv/ops/wrappers.py +++ b/mmcv/cnn/bricks/wrappers.py @@ -10,7 +10,7 @@ import torch.nn as nn from torch.nn.modules.utils import _pair -from ..cnn import CONV_LAYERS +from .registry import CONV_LAYERS, UPSAMPLE_LAYERS class NewEmptyTensorOp(torch.autograd.Function): @@ -47,6 +47,7 @@ def forward(self, x): return super().forward(x) +@UPSAMPLE_LAYERS.register_module('deconv', force=True) class ConvTranspose2d(nn.ConvTranspose2d): def forward(self, x): @@ -70,7 +71,8 @@ def forward(self, x): class MaxPool2d(nn.MaxPool2d): def forward(self, x): - if x.numel() == 0 and torch.__version__ <= '1.4': + # PyTorch 1.6 does not support empty tensor inference yet + if x.numel() == 0 and torch.__version__ <= '1.6': out_shape = list(x.shape[:2]) for i, k, p, s, d in zip(x.shape[-2:], _pair(self.kernel_size), _pair(self.padding), _pair(self.stride), diff --git a/mmcv/ops/__init__.py b/mmcv/ops/__init__.py index b38aff9253..2b83dba727 100644 --- a/mmcv/ops/__init__.py +++ b/mmcv/ops/__init__.py @@ -5,6 +5,10 @@ from .deform_conv import DeformConv2d, DeformConv2dPack, deform_conv2d from .deform_roi_pool import (DeformRoIPool, DeformRoIPoolPack, ModulatedDeformRoIPoolPack, deform_roi_pool) +from .deprecated_wrappers import Conv2d_deprecated as Conv2d +from .deprecated_wrappers import ConvTranspose2d_deprecated as ConvTranspose2d +from .deprecated_wrappers import Linear_deprecated as Linear +from .deprecated_wrappers import MaxPool2d_deprecated as MaxPool2d from .focal_loss import (SigmoidFocalLoss, SoftmaxFocalLoss, sigmoid_focal_loss, softmax_focal_loss) from .info import get_compiler_version, get_compiling_cuda_version @@ -21,7 +25,6 @@ from .saconv import SAConv2d from .sync_bn import SyncBatchNorm from .tin_shift import TINShift, tin_shift -from .wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d __all__ = [ 'bbox_overlaps', 'CARAFE', 'CARAFENaive', 'CARAFEPack', 'carafe', diff --git a/mmcv/ops/deprecated_wrappers.py b/mmcv/ops/deprecated_wrappers.py new file mode 100644 index 0000000000..79b845e478 --- /dev/null +++ b/mmcv/ops/deprecated_wrappers.py @@ -0,0 +1,42 @@ +# This file is for backward compatibility. +# Module wrappers for empty tensor have been moved to mmcv.cnn.bricks. +import warnings + +from ..cnn.bricks.wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d + + +class Conv2d_deprecated(Conv2d): + + def __init__(*args, **kwargs): + super().__init__(*args, **kwargs) + warnings.warn( + 'Importing Conv2d wrapper from "mmcv.ops" will be deprecated in' + ' the future. Please import them from "mmcv.cnn" instead') + + +class ConvTranspose2d_deprecated(ConvTranspose2d): + + def __init__(*args, **kwargs): + super().__init__(*args, **kwargs) + warnings.warn( + 'Importing ConvTranspose2d wrapper from "mmcv.ops" will be ' + 'deprecated in the future. Please import them from "mmcv.cnn" ' + 'instead') + + +class MaxPool2d_deprecated(MaxPool2d): + + def __init__(*args, **kwargs): + super().__init__(*args, **kwargs) + warnings.warn( + 'Importing MaxPool2d wrapper from "mmcv.ops" will be deprecated in' + ' the future. Please import them from "mmcv.cnn" instead') + + +class Linear_deprecated(Linear): + + def __init__(*args, **kwargs): + super().__init__(*args, **kwargs) + warnings.warn( + 'Importing Linear wrapper from "mmcv.ops" will be deprecated in' + ' the future. Please import them from "mmcv.cnn" instead') diff --git a/tests/test_ops/test_wrappers.py b/tests/test_cnn/test_wrappers.py similarity index 96% rename from tests/test_ops/test_wrappers.py rename to tests/test_cnn/test_wrappers.py index f1afd40d21..067cb6465b 100644 --- a/tests/test_ops/test_wrappers.py +++ b/tests/test_cnn/test_wrappers.py @@ -5,11 +5,10 @@ import torch import torch.nn as nn -from mmcv.ops import Conv2d, ConvTranspose2d, Linear, MaxPool2d - -torch.__version__ = '1.1' # force test +from mmcv.cnn.bricks import Conv2d, ConvTranspose2d, Linear, MaxPool2d +@patch('torch.__version__', '1.1') def test_conv2d(): """ CommandLine: @@ -52,6 +51,7 @@ def test_conv2d(): wrapper(x_empty) +@patch('torch.__version__', '1.1') def test_conv_transposed_2d(): test_cases = OrderedDict([('in_w', [10, 20]), ('in_h', [10, 20]), ('in_channel', [1, 3]), ('out_channel', [1, 3]), @@ -105,6 +105,7 @@ def test_conv_transposed_2d(): wrapper(x_empty) +@patch('torch.__version__', '1.1') def test_max_pool_2d(): test_cases = OrderedDict([('in_w', [10, 20]), ('in_h', [10, 20]), ('in_channel', [1, 3]), ('out_channel', [1, 3]), @@ -129,6 +130,7 @@ def test_max_pool_2d(): assert torch.equal(wrapper(x_normal), ref_out) +@patch('torch.__version__', '1.1') def test_linear(): test_cases = OrderedDict([ ('in_w', [10, 20]), @@ -167,8 +169,8 @@ def test_linear(): wrapper(x_empty) +@patch('torch.__version__', '1.6.1') def test_nn_op_forward_called(): - torch.__version__ = '1.4.1' for m in ['Conv2d', 'ConvTranspose2d', 'MaxPool2d']: with patch(f'torch.nn.{m}.forward') as nn_module_forward: From a0cc5a8450623dc4243d35c966789f899cd2ebdf Mon Sep 17 00:00:00 2001 From: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com> Date: Mon, 14 Sep 2020 12:14:43 +0800 Subject: [PATCH 56/81] Supports brightness and contrast augmentations (#546) * add brightness and contrast augmentation * remove unnecessary * reformat * relax the precision constrain for adjust_brightness aug * fix percision assertion error in unit test * remove toy * rename alpha as factor * use np.testing.assert_allclose in place of np.less_equal --- mmcv/image/__init__.py | 8 ++-- mmcv/image/photometric.py | 60 ++++++++++++++++++++++++- tests/test_image/test_photometric.py | 65 ++++++++++++++++++++++++++++ 3 files changed, 129 insertions(+), 4 deletions(-) diff --git a/mmcv/image/__init__.py b/mmcv/image/__init__.py index b32846c137..62e6cf060a 100644 --- a/mmcv/image/__init__.py +++ b/mmcv/image/__init__.py @@ -7,8 +7,9 @@ imtranslate, rescale_size) from .io import imfrombytes, imread, imwrite, supported_backends, use_backend from .misc import tensor2imgs -from .photometric import (adjust_color, imdenormalize, imequalize, iminvert, - imnormalize, imnormalize_, posterize, solarize) +from .photometric import (adjust_brightness, adjust_color, adjust_contrast, + imdenormalize, imequalize, iminvert, imnormalize, + imnormalize_, posterize, solarize) __all__ = [ 'bgr2gray', 'bgr2hls', 'bgr2hsv', 'bgr2rgb', 'gray2bgr', 'gray2rgb', @@ -18,5 +19,6 @@ 'imwrite', 'supported_backends', 'use_backend', 'imdenormalize', 'imnormalize', 'imnormalize_', 'iminvert', 'posterize', 'solarize', 'rgb2ycbcr', 'bgr2ycbcr', 'ycbcr2rgb', 'ycbcr2bgr', 'tensor2imgs', - 'imshear', 'imtranslate', 'adjust_color', 'imequalize' + 'imshear', 'imtranslate', 'adjust_color', 'imequalize', + 'adjust_brightness', 'adjust_contrast' ] diff --git a/mmcv/image/photometric.py b/mmcv/image/photometric.py index ea12294b3f..5323431ad6 100644 --- a/mmcv/image/photometric.py +++ b/mmcv/image/photometric.py @@ -1,7 +1,7 @@ import cv2 import numpy as np -from .colorspace import bgr2gray +from .colorspace import bgr2gray, gray2bgr def imnormalize(img, mean, std, to_rgb=True): @@ -166,3 +166,61 @@ def _scale_channel(im, c): s3 = _scale_channel(img, 2) equalized_img = np.stack([s1, s2, s3], axis=-1) return equalized_img + + +def adjust_brightness(img, factor=1.): + """Adjust image brightness. + + This function controls the brightness of an image. An + enhancement factor of 0.0 gives a black image. + A factor of 1.0 gives the original image. This function + blends the source image and the degenerated black image: + + ``output = img * factor + degenerated * (1 - factor)`` + + Args: + img (ndarray): Image to be brightened. + factor (float): A value controls the enhancement. + Factor 1.0 returns the original image, lower + factors mean less color (brightness, contrast, + etc), and higher values more. Default 1. + + Returns: + ndarray: The brightened image. + """ + degenerated = np.zeros_like(img) + # Note manually convert the dtype to np.float32, to + # achieve as close results as PIL.ImageEnhance.Brightness. + # Set beta=1-factor, and gamma=0 + brightened_img = cv2.addWeighted( + img.astype(np.float32), factor, degenerated.astype(np.float32), + 1 - factor, 0) + return brightened_img.astype(img.dtype) + + +def adjust_contrast(img, factor=1.): + """Adjust image contrast. + + This function controls the contrast of an image. An + enhancement factor of 0.0 gives a solid grey + image. A factor of 1.0 gives the original image. It + blends the source image and the degenerated mean image: + + ``output = img * factor + degenerated * (1 - factor)`` + + Args: + img (ndarray): Image to be contrasted. BGR order. + factor (float): Same as :func:`mmcv.adjust_brightness`. + + Returns: + ndarray: The contrasted image. + """ + gray_img = bgr2gray(img) + hist = np.histogram(gray_img, 256, (0, 255))[0] + mean = round(np.sum(gray_img) / np.sum(hist)) + degenerated = (np.ones_like(img[..., 0]) * mean).astype(img.dtype) + degenerated = gray2bgr(degenerated) + contrasted_img = cv2.addWeighted( + img.astype(np.float32), factor, degenerated.astype(np.float32), + 1 - factor, 0) + return contrasted_img.astype(img.dtype) diff --git a/tests/test_image/test_photometric.py b/tests/test_image/test_photometric.py index efa89046ba..1b2524ba88 100644 --- a/tests/test_image/test_photometric.py +++ b/tests/test_image/test_photometric.py @@ -135,3 +135,68 @@ def _imequalize(img): 255).astype(np.uint8) equalized_img = mmcv.imequalize(img) assert_array_equal(equalized_img, _imequalize(img)) + + def test_adjust_brightness(self, nb_rand_test=100): + + def _adjust_brightness(img, factor): + # adjust the brightness of image using + # PIL.ImageEnhance.Brightness + from PIL.ImageEnhance import Brightness + from PIL import Image + img = Image.fromarray(img) + brightened_img = Brightness(img).enhance(factor) + return np.asarray(brightened_img) + + img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]], + dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + # test case with factor 1.0 + assert_array_equal(mmcv.adjust_brightness(img, 1.), img) + # test case with factor 0.0 + assert_array_equal(mmcv.adjust_brightness(img, 0.), np.zeros_like(img)) + # test adjust_brightness with randomly sampled images and factors. + for _ in range(nb_rand_test): + img = np.clip( + np.random.uniform(0, 1, (1000, 1200, 3)) * 260, 0, + 255).astype(np.uint8) + factor = np.random.uniform() + np.testing.assert_allclose( + mmcv.adjust_brightness(img, factor).astype(np.int32), + _adjust_brightness(img, factor).astype(np.int32), + rtol=0, + atol=1) + + def test_adjust_contrast(self, nb_rand_test=100): + + def _adjust_contrast(img, factor): + from PIL.ImageEnhance import Contrast + from PIL import Image + # Image.fromarray defaultly supports RGB, not BGR. + # convert from BGR to RGB + img = Image.fromarray(img[..., ::-1], mode='RGB') + contrasted_img = Contrast(img).enhance(factor) + # convert from RGB to BGR + return np.asarray(contrasted_img)[..., ::-1] + + img = np.array([[0, 128, 255], [1, 127, 254], [2, 129, 253]], + dtype=np.uint8) + img = np.stack([img, img, img], axis=-1) + # test case with factor 1.0 + assert_array_equal(mmcv.adjust_contrast(img, 1.), img) + # test case with factor 0.0 + assert_array_equal( + mmcv.adjust_contrast(img, 0.), _adjust_contrast(img, 0.)) + # test adjust_contrast with randomly sampled images and factors. + for _ in range(nb_rand_test): + img = np.clip( + np.random.uniform(0, 1, (1200, 1000, 3)) * 260, 0, + 255).astype(np.uint8) + factor = np.random.uniform() + # Note the gap (less_equal 1) between PIL.ImageEnhance.Contrast + # and mmcv.adjust_contrast comes from the gap that converts from + # a color image to gray image using mmcv or PIL. + np.testing.assert_allclose( + mmcv.adjust_contrast(img, factor).astype(np.int32), + _adjust_contrast(img, factor).astype(np.int32), + rtol=0, + atol=1) From 9ecd6b0d5ff9d2172c49a182eaa669e9f27bb8e7 Mon Sep 17 00:00:00 2001 From: Ryan Li Date: Tue, 15 Sep 2020 20:44:35 +0800 Subject: [PATCH 57/81] Add 'wrap_fp16_model' to __init__.py (#555) * add 'wrap_fp16_model' to __inti__.py * add 'wrap_fp16_model' to __init__.py --- mmcv/runner/__init__.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/mmcv/runner/__init__.py b/mmcv/runner/__init__.py index 809cb1fd00..dc6371b1e7 100644 --- a/mmcv/runner/__init__.py +++ b/mmcv/runner/__init__.py @@ -4,7 +4,7 @@ save_checkpoint, weights_to_cpu) from .dist_utils import get_dist_info, init_dist, master_only from .epoch_based_runner import EpochBasedRunner, Runner -from .fp16_utils import auto_fp16, force_fp32 +from .fp16_utils import auto_fp16, force_fp32, wrap_fp16_model from .hooks import (HOOKS, CheckpointHook, ClosureHook, DistSamplerSeedHook, EMAHook, Fp16OptimizerHook, Hook, IterTimerHook, LoggerHook, LrUpdaterHook, MlflowLoggerHook, OptimizerHook, @@ -29,6 +29,6 @@ 'obj_from_dict', 'init_dist', 'get_dist_info', 'master_only', 'OPTIMIZER_BUILDERS', 'OPTIMIZERS', 'DefaultOptimizerConstructor', 'build_optimizer', 'build_optimizer_constructor', 'IterLoader', - 'set_random_seed', 'auto_fp16', 'force_fp32', 'Fp16OptimizerHook', - 'SyncBuffersHook', 'EMAHook' + 'set_random_seed', 'auto_fp16', 'force_fp32', 'wrap_fp16_model', + 'Fp16OptimizerHook', 'SyncBuffersHook', 'EMAHook' ] From 7ef3a5e925c3a742453146268fce13d9cff00346 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Wed, 16 Sep 2020 19:12:18 +0800 Subject: [PATCH 58/81] Use copy instead of symlink on windows (#557) * use copy instead of symlink on windows * use platform.system() instead of sys.platform --- mmcv/runner/epoch_based_runner.py | 8 +++++++- mmcv/runner/iter_based_runner.py | 8 +++++++- 2 files changed, 14 insertions(+), 2 deletions(-) diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py index 1912accded..f8cb358402 100644 --- a/mmcv/runner/epoch_based_runner.py +++ b/mmcv/runner/epoch_based_runner.py @@ -1,5 +1,7 @@ # Copyright (c) Open-MMLab. All rights reserved. import os.path as osp +import platform +import shutil import time import warnings @@ -163,7 +165,11 @@ def save_checkpoint(self, # in some environments, `os.symlink` is not supported, you may need to # set `create_symlink` to False if create_symlink: - mmcv.symlink(filename, osp.join(out_dir, 'latest.pth')) + dst_file = osp.join(out_dir, 'latest.pth') + if platform.system() != 'Windows': + mmcv.symlink(filename, dst_file) + else: + shutil.copy(filename, dst_file) class Runner(EpochBasedRunner): diff --git a/mmcv/runner/iter_based_runner.py b/mmcv/runner/iter_based_runner.py index f41a86a9d4..24825ecf85 100644 --- a/mmcv/runner/iter_based_runner.py +++ b/mmcv/runner/iter_based_runner.py @@ -1,5 +1,7 @@ # Copyright (c) Open-MMLab. All rights reserved. import os.path as osp +import platform +import shutil import time import torch @@ -193,7 +195,11 @@ def save_checkpoint(self, # in some environments, `os.symlink` is not supported, you may need to # set `create_symlink` to False if create_symlink: - mmcv.symlink(filename, osp.join(out_dir, 'latest.pth')) + dst_file = osp.join(out_dir, 'latest.pth') + if platform.system() != 'Windows': + mmcv.symlink(filename, dst_file) + else: + shutil.copy(filename, dst_file) def register_training_hooks(self, lr_config, From 779f47bab941e7aeda6f03d2524111d11c0c5eb5 Mon Sep 17 00:00:00 2001 From: David de la Iglesia Castro Date: Wed, 16 Sep 2020 13:16:49 +0200 Subject: [PATCH 59/81] Allow type to be default arg (#558) * Add test case for type defined using default_args * Refactor build_from_cfg * Update exception of missing type * pre-commit * Fix default_args is None * pre-commit * Bring back test * Update exception raising --- mmcv/utils/registry.py | 14 +++++++++----- tests/test_utils/test_registry.py | 20 +++++++++++++++++++- 2 files changed, 28 insertions(+), 6 deletions(-) diff --git a/mmcv/utils/registry.py b/mmcv/utils/registry.py index 2cec4292e7..64b83f1d75 100644 --- a/mmcv/utils/registry.py +++ b/mmcv/utils/registry.py @@ -139,8 +139,10 @@ def build_from_cfg(cfg, registry, default_args=None): if not isinstance(cfg, dict): raise TypeError(f'cfg must be a dict, but got {type(cfg)}') if 'type' not in cfg: - raise KeyError( - f'the cfg dict must contain the key "type", but got {cfg}') + if default_args is None or 'type' not in default_args: + raise KeyError( + '`cfg` or `default_args` must contain the key "type", ' + f'but got {cfg}\n{default_args}') if not isinstance(registry, Registry): raise TypeError('registry must be an mmcv.Registry object, ' f'but got {type(registry)}') @@ -149,6 +151,11 @@ def build_from_cfg(cfg, registry, default_args=None): f'but got {type(default_args)}') args = cfg.copy() + + if default_args is not None: + for name, value in default_args.items(): + args.setdefault(name, value) + obj_type = args.pop('type') if is_str(obj_type): obj_cls = registry.get(obj_type) @@ -161,7 +168,4 @@ def build_from_cfg(cfg, registry, default_args=None): raise TypeError( f'type must be a str or valid type, but got {type(obj_type)}') - if default_args is not None: - for name, value in default_args.items(): - args.setdefault(name, value) return obj_cls(**args) diff --git a/tests/test_utils/test_registry.py b/tests/test_utils/test_registry.py index a16785166d..104cc1964c 100644 --- a/tests/test_utils/test_registry.py +++ b/tests/test_utils/test_registry.py @@ -158,6 +158,18 @@ def __init__(self, depth, stages=4): assert isinstance(model, ResNet) assert model.depth == 50 and model.stages == 4 + # type defined using default_args + cfg = dict(depth=50) + model = mmcv.build_from_cfg( + cfg, BACKBONES, default_args=dict(type='ResNet')) + assert isinstance(model, ResNet) + assert model.depth == 50 and model.stages == 4 + + cfg = dict(depth=50) + model = mmcv.build_from_cfg(cfg, BACKBONES, default_args=dict(type=ResNet)) + assert isinstance(model, ResNet) + assert model.depth == 50 and model.stages == 4 + # not a registry with pytest.raises(TypeError): cfg = dict(type='VGG') @@ -179,10 +191,16 @@ def __init__(self, depth, stages=4): model = mmcv.build_from_cfg(cfg, BACKBONES) # cfg should contain the key "type" - with pytest.raises(KeyError): + with pytest.raises(KeyError, match='must contain the key "type"'): cfg = dict(depth=50, stages=4) model = mmcv.build_from_cfg(cfg, BACKBONES) + # cfg or default_args should contain the key "type" + with pytest.raises(KeyError, match='must contain the key "type"'): + cfg = dict(depth=50) + model = mmcv.build_from_cfg( + cfg, BACKBONES, default_args=dict(stages=4)) + # incorrect registry type with pytest.raises(TypeError): cfg = dict(type='ResNet', depth=50) From ece32796c31eb4a68d701c1312b959007cb83deb Mon Sep 17 00:00:00 2001 From: ychan <31604046+hanyc0914@users.noreply.github.com> Date: Thu, 17 Sep 2020 14:25:05 +0800 Subject: [PATCH 60/81] fix dcn forward bug (#562) --- mmcv/ops/csrc/parrots/deform_conv_cuda.cu | 1 + mmcv/ops/csrc/pytorch/deform_conv_cuda.cu | 2 ++ 2 files changed, 3 insertions(+) diff --git a/mmcv/ops/csrc/parrots/deform_conv_cuda.cu b/mmcv/ops/csrc/parrots/deform_conv_cuda.cu index 6aa1147ff1..991281e286 100644 --- a/mmcv/ops/csrc/parrots/deform_conv_cuda.cu +++ b/mmcv/ops/csrc/parrots/deform_conv_cuda.cu @@ -267,6 +267,7 @@ void DeformConvForwardCUDAKernelLauncher( auto columns_g = columns[g]; gemm(ctx, 1, false, weight_g, false, columns_g, 1, output_g); } + columns = columns.view({columns.dim(0) * columns.dim(1), columns.dim(2)}); } output_buffer = output_buffer.view( diff --git a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu index 0dad63d280..2d17f59fd2 100644 --- a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu +++ b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu @@ -276,6 +276,8 @@ void DeformConvForwardCUDAKernelLauncher(Tensor input, Tensor weight, .addmm_(weight[g].flatten(1), columns[g]) .view_as(output_buffer[elt][g]); } + columns = + columns.view({columns.size(0) * columns.size(1), columns.size(2)}); } output_buffer = output_buffer.view( From b7af0e9ff7d5e5ae0722388851230c4704ff7dd3 Mon Sep 17 00:00:00 2001 From: ychan <31604046+hanyc0914@users.noreply.github.com> Date: Thu, 17 Sep 2020 14:25:16 +0800 Subject: [PATCH 61/81] fix mdconv backward bug (#563) --- .../parrots/modulated_deform_conv_cuda.cu | 61 +++++++++++++++---- 1 file changed, 49 insertions(+), 12 deletions(-) diff --git a/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu b/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu index 3e8c096edc..da5692aef4 100644 --- a/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu +++ b/mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu @@ -273,20 +273,57 @@ void ModulatedDeformConvBackwardCUDAKernelLauncher( } for (size_t g = 0; g < group; g++) { - auto grad_weight_g = grad_weight[g].view( - {grad_weight.dim(1), - grad_weight.dim(2) * grad_weight.dim(3) * grad_weight.dim(4)}); - gemm(ctx, 1, false, - grad_output[b][g].view( - {grad_output.dim(2), grad_output.dim(3) * grad_output.dim(4)}), - true, columns[g], 1, grad_weight_g); + auto grad_weight_g = ctx.createDArrayLite( + grad_weight.elemType(), + DArrayShape(grad_weight.dim(1), grad_weight.dim(2), + grad_weight.dim(3), grad_weight.dim(4))); + copy(ctx, grad_weight_g, grad_weight[g]); + grad_weight_g = grad_weight_g.view( + {grad_weight_g.dim(0), + grad_weight_g.dim(1) * grad_weight_g.dim(2) * grad_weight_g.dim(3)}); + + auto columns_g = columns[g]; + columns_g = transpose(ctx, columns_g, 0, 1); + + auto grad_output_bg = ctx.createDArrayLite( + grad_output.elemType(), + DArrayShape(grad_output.dim(2), grad_output.dim(3), + grad_output.dim(4))); + copy(ctx, grad_output_bg, grad_output[b][g]); + grad_output_bg = + grad_output_bg.view({grad_output_bg.dim(0), + grad_output_bg.dim(1) * grad_output_bg.dim(2)}); + + grad_weight_g = parrots::op::addmm(ctx, grad_weight_g, grad_output_bg, + columns_g, 1, 1); + auto grad_weight_out = grad_weight[g]; + copy(ctx, grad_weight_out, grad_weight_g); if (with_bias) { - auto grad_bias_g = grad_bias[g].view({grad_bias.dim(1), 1}); - gemm(ctx, 1, false, - grad_output[b][g].view( - {grad_output.dim(2), grad_output.dim(3) * grad_output.dim(4)}), - false, ones.view({ones.dim(0) * ones.dim(1), 1}), 1, grad_bias_g); + auto grad_bias_g = ctx.createDArrayLite(grad_bias.elemType(), + DArrayShape(grad_bias.dim(1))); + copy(ctx, grad_bias_g, grad_bias[g]); + grad_bias_g = grad_bias_g.view({grad_bias_g.dim(0), 1}); + + auto grad_output_bg = ctx.createDArrayLite( + grad_output.elemType(), + DArrayShape(grad_output.dim(2), grad_output.dim(3), + grad_output.dim(4))); + copy(ctx, grad_output_bg, grad_output[b][g]); + grad_output_bg = grad_output_bg.view( + {grad_output_bg.dim(0), + grad_output_bg.dim(1) * grad_output_bg.dim(2)}); + + auto ones_g = ctx.createDArrayLite( + ones.elemType(), DArrayShape(ones.dim(0), ones.dim(1))); + copy(ctx, ones_g, ones); + ones_g = ones_g.view({ones_g.dim(0) * ones_g.dim(1), 1}); + + grad_bias_g = + parrots::op::addmm(ctx, grad_bias_g, grad_output_bg, ones_g, 1, 1); + + auto grad_bias_out = grad_bias[g]; + copy(ctx, grad_bias_out, grad_bias_g); } } From 21143568268f9e0cc09dd859dc15fd4e55ec38f1 Mon Sep 17 00:00:00 2001 From: ychan <31604046+hanyc0914@users.noreply.github.com> Date: Fri, 18 Sep 2020 13:48:21 +0800 Subject: [PATCH 62/81] fix dcon forward and backward bug (#565) --- mmcv/ops/csrc/parrots/deform_conv_cuda.cu | 2 ++ mmcv/ops/csrc/pytorch/deform_conv_cuda.cu | 3 +++ 2 files changed, 5 insertions(+) diff --git a/mmcv/ops/csrc/parrots/deform_conv_cuda.cu b/mmcv/ops/csrc/parrots/deform_conv_cuda.cu index 991281e286..203e1cfa02 100644 --- a/mmcv/ops/csrc/parrots/deform_conv_cuda.cu +++ b/mmcv/ops/csrc/parrots/deform_conv_cuda.cu @@ -268,6 +268,7 @@ void DeformConvForwardCUDAKernelLauncher( gemm(ctx, 1, false, weight_g, false, columns_g, 1, output_g); } columns = columns.view({columns.dim(0) * columns.dim(1), columns.dim(2)}); + weight = weight.view({nOutputPlane, nInputPlane, kH, kW}); } output_buffer = output_buffer.view( @@ -372,6 +373,7 @@ void DeformConvBackwardInputCUDAKernelLauncher( gradOutput = gradOutput.view({gradOutput.dim(0), gradOutput.dim(1) * gradOutput.dim(2), im2col_step, outputHeight, outputWidth}); + weight = weight.view({nOutputPlane, nInputPlane, kH, kW}); deformable_col2im_coord(columns, input[elt], offset[elt], nInputPlane, inputHeight, inputWidth, kH, kW, padH, padW, dH, dW, diff --git a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu index 2d17f59fd2..ee96b36241 100644 --- a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu +++ b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu @@ -278,6 +278,8 @@ void DeformConvForwardCUDAKernelLauncher(Tensor input, Tensor weight, } columns = columns.view({columns.size(0) * columns.size(1), columns.size(2)}); + weight = weight.view({weight.size(0) * weight.size(1), weight.size(2), + weight.size(3), weight.size(4)}); } output_buffer = output_buffer.view( @@ -375,6 +377,7 @@ void DeformConvBackwardInputCUDAKernelLauncher( gradOutput = gradOutput.view( {gradOutput.size(0), gradOutput.size(1) * gradOutput.size(2), gradOutput.size(3), gradOutput.size(4), gradOutput.size(5)}); + weight = weight.view({nOutputPlane, nInputPlane, kH, kW}); deformable_col2im_coord(columns, input[elt], offset[elt], nInputPlane, inputHeight, inputWidth, kH, kW, padH, padW, dH, dW, From cc332b26e128ed7eda0c5af3fc2a9f9a26e39de4 Mon Sep 17 00:00:00 2001 From: robin Han Date: Fri, 18 Sep 2020 13:54:00 +0800 Subject: [PATCH 63/81] add switch for onnx exporter (#564) --- mmcv/onnx/symbolic.py | 31 +++++++++++++++++++++++-------- 1 file changed, 23 insertions(+), 8 deletions(-) diff --git a/mmcv/onnx/symbolic.py b/mmcv/onnx/symbolic.py index 4a301b7274..f6b61d9633 100644 --- a/mmcv/onnx/symbolic.py +++ b/mmcv/onnx/symbolic.py @@ -1,4 +1,6 @@ """Modified from https://github.com/pytorch/pytorch.""" +import os + import numpy as np import torch from torch.nn.modules.utils import _pair, _single, _triple @@ -21,14 +23,27 @@ def symbolic_fn(g, input, output_size, *args): 'Constant', value_t=torch.tensor([], dtype=torch.float32)) if scales is None: - input_size = g.op('Shape', input) - input_size_beg = sym_help._slice_helper( - g, input_size, axes=[0], ends=[2], starts=[0]) - output_size = g.op( - 'Cast', - output_size, - to_i=sym_help.cast_pytorch_to_onnx['Long']) - output_size = g.op('Concat', input_size_beg, output_size, axis_i=0) + if 'ONNX_BACKEND' in os.environ and os.environ[ + 'ONNX_BACKEND'] == 'TensorRT': + input_size = input.type().sizes() + # slice the first two dim + input_size = input_size[:2] + # convert output_size to int type + output_size = sym_help._maybe_get_const(output_size, 'is') + input_size.extend(output_size) + output_size = g.op( + 'Constant', + value_t=torch.tensor(input_size, dtype=torch.int64)) + else: + input_size = g.op('Shape', input) + input_size_beg = sym_help._slice_helper( + g, input_size, axes=[0], ends=[2], starts=[0]) + output_size = g.op( + 'Cast', + output_size, + to_i=sym_help.cast_pytorch_to_onnx['Long']) + output_size = g.op( + 'Concat', input_size_beg, output_size, axis_i=0) scales = g.op( 'Constant', value_t=torch.tensor([], dtype=torch.float32)) return g.op( From 5cad35bd2d7eb354aeb25552cf2a142a5a3edae1 Mon Sep 17 00:00:00 2001 From: Ryan Li Date: Fri, 18 Sep 2020 19:54:37 +0800 Subject: [PATCH 64/81] fix deprecated wrappers exiting bug (#567) --- mmcv/ops/deprecated_wrappers.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/mmcv/ops/deprecated_wrappers.py b/mmcv/ops/deprecated_wrappers.py index 79b845e478..863611b2e1 100644 --- a/mmcv/ops/deprecated_wrappers.py +++ b/mmcv/ops/deprecated_wrappers.py @@ -7,7 +7,7 @@ class Conv2d_deprecated(Conv2d): - def __init__(*args, **kwargs): + def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) warnings.warn( 'Importing Conv2d wrapper from "mmcv.ops" will be deprecated in' @@ -16,7 +16,7 @@ def __init__(*args, **kwargs): class ConvTranspose2d_deprecated(ConvTranspose2d): - def __init__(*args, **kwargs): + def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) warnings.warn( 'Importing ConvTranspose2d wrapper from "mmcv.ops" will be ' @@ -26,7 +26,7 @@ def __init__(*args, **kwargs): class MaxPool2d_deprecated(MaxPool2d): - def __init__(*args, **kwargs): + def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) warnings.warn( 'Importing MaxPool2d wrapper from "mmcv.ops" will be deprecated in' @@ -35,7 +35,7 @@ def __init__(*args, **kwargs): class Linear_deprecated(Linear): - def __init__(*args, **kwargs): + def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) warnings.warn( 'Importing Linear wrapper from "mmcv.ops" will be deprecated in' From 8c70df3310d98b8b3912abbdcd2ecebbc3a29493 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Mon, 21 Sep 2020 17:27:21 +0800 Subject: [PATCH 65/81] bump version to 1.1.3 (#569) --- mmcv/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/version.py b/mmcv/version.py index 1b986d4830..64ec9260f6 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,6 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.1.2' +__version__ = '1.1.3' def parse_version_info(version_str): From 50af00991c5b95e8ce8c38d9ec9a5fda9c43e176 Mon Sep 17 00:00:00 2001 From: Zhiyuan Chen Date: Tue, 22 Sep 2020 10:40:00 +0800 Subject: [PATCH 66/81] merge the calling of train/val_step and batch_processor into run_iter (#553) * merge train/val_step and batch_processor into run_iter * make self.train_mode of runner as an argument * remove abstract methods of run_iter() in base_runner --- mmcv/runner/epoch_based_runner.py | 44 +++++++++++++------------------ 1 file changed, 18 insertions(+), 26 deletions(-) diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py index f8cb358402..06aa8b35dc 100644 --- a/mmcv/runner/epoch_based_runner.py +++ b/mmcv/runner/epoch_based_runner.py @@ -19,6 +19,22 @@ class EpochBasedRunner(BaseRunner): This runner train models epoch by epoch. """ + def run_iter(self, data_batch, train_mode, **kwargs): + if self.batch_processor is not None: + outputs = self.batch_processor( + self.model, data_batch, train_mode=train_mode, **kwargs) + elif train_mode: + outputs = self.model.train_step(data_batch, self.optimizer, + **kwargs) + else: + outputs = self.model.val_step(data_batch, self.optimizer, **kwargs) + if not isinstance(outputs, dict): + raise TypeError('"batch_processor()" or "model.train_step()"' + 'and "model.val_step()" must return a dict') + if 'log_vars' in outputs: + self.log_buffer.update(outputs['log_vars'], outputs['num_samples']) + self.outputs = outputs + def train(self, data_loader, **kwargs): self.model.train() self.mode = 'train' @@ -29,19 +45,7 @@ def train(self, data_loader, **kwargs): for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_train_iter') - if self.batch_processor is None: - outputs = self.model.train_step(data_batch, self.optimizer, - **kwargs) - else: - outputs = self.batch_processor( - self.model, data_batch, train_mode=True, **kwargs) - if not isinstance(outputs, dict): - raise TypeError('"batch_processor()" or "model.train_step()"' - ' must return a dict') - if 'log_vars' in outputs: - self.log_buffer.update(outputs['log_vars'], - outputs['num_samples']) - self.outputs = outputs + self.run_iter(data_batch, train_mode=True) self.call_hook('after_train_iter') self._iter += 1 @@ -58,19 +62,7 @@ def val(self, data_loader, **kwargs): self._inner_iter = i self.call_hook('before_val_iter') with torch.no_grad(): - if self.batch_processor is None: - outputs = self.model.val_step(data_batch, self.optimizer, - **kwargs) - else: - outputs = self.batch_processor( - self.model, data_batch, train_mode=False, **kwargs) - if not isinstance(outputs, dict): - raise TypeError('"batch_processor()" or "model.val_step()"' - ' must return a dict') - if 'log_vars' in outputs: - self.log_buffer.update(outputs['log_vars'], - outputs['num_samples']) - self.outputs = outputs + self.run_iter(data_batch, train_mode=False) self.call_hook('after_val_iter') self.call_hook('after_val_epoch') From afb73995b994849864e8dac9ae207b0d4f12d7eb Mon Sep 17 00:00:00 2001 From: David de la Iglesia Castro Date: Thu, 24 Sep 2020 18:00:27 +0200 Subject: [PATCH 67/81] Add missing by_epoch arg (#576) --- mmcv/runner/hooks/logger/mlflow.py | 10 ++++++++-- mmcv/runner/hooks/logger/wandb.py | 5 +++-- 2 files changed, 11 insertions(+), 4 deletions(-) diff --git a/mmcv/runner/hooks/logger/mlflow.py b/mmcv/runner/hooks/logger/mlflow.py index 7ae9df1f6b..1abea19333 100644 --- a/mmcv/runner/hooks/logger/mlflow.py +++ b/mmcv/runner/hooks/logger/mlflow.py @@ -15,7 +15,8 @@ def __init__(self, log_model=True, interval=10, ignore_last=True, - reset_flag=True): + reset_flag=True, + by_epoch=True): """Class to log metrics and (optionally) a trained model to MLflow. It requires `MLflow`_ to be installed. @@ -33,12 +34,17 @@ def __init__(self, Default True. If True, log runner.model as an MLflow artifact for the current run. + interval (int): Logging interval (every k iterations). + ignore_last (bool): Ignore the log of last iterations in each epoch + if less than `interval`. + reset_flag (bool): Whether to clear the output buffer after logging + by_epoch (bool): Whether EpochBasedRunner is used. .. _MLflow: https://www.mlflow.org/docs/latest/index.html """ super(MlflowLoggerHook, self).__init__(interval, ignore_last, - reset_flag) + reset_flag, by_epoch) self.import_mlflow() self.exp_name = exp_name self.tags = tags diff --git a/mmcv/runner/hooks/logger/wandb.py b/mmcv/runner/hooks/logger/wandb.py index 2fa9d43ef6..7acedfc8b1 100644 --- a/mmcv/runner/hooks/logger/wandb.py +++ b/mmcv/runner/hooks/logger/wandb.py @@ -13,9 +13,10 @@ def __init__(self, init_kwargs=None, interval=10, ignore_last=True, - reset_flag=True): + reset_flag=True, + by_epoch=True): super(WandbLoggerHook, self).__init__(interval, ignore_last, - reset_flag) + reset_flag, by_epoch) self.import_wandb() self.init_kwargs = init_kwargs From 2bb1160e6c5a85d571ba495b4d4e73c48d5146a1 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Fri, 25 Sep 2020 00:09:58 +0800 Subject: [PATCH 68/81] [fix]: fix wrapper comparison of pytorch version (#572) --- mmcv/cnn/bricks/wrappers.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/mmcv/cnn/bricks/wrappers.py b/mmcv/cnn/bricks/wrappers.py index 338bcb6851..4d72af813c 100644 --- a/mmcv/cnn/bricks/wrappers.py +++ b/mmcv/cnn/bricks/wrappers.py @@ -30,7 +30,7 @@ def backward(ctx, grad): class Conv2d(nn.Conv2d): def forward(self, x): - if x.numel() == 0 and torch.__version__ <= '1.4': + if x.numel() == 0 and torch.__version__ <= '1.4.0': out_shape = [x.shape[0], self.out_channels] for i, k, p, s, d in zip(x.shape[-2:], self.kernel_size, self.padding, self.stride, self.dilation): @@ -72,7 +72,7 @@ class MaxPool2d(nn.MaxPool2d): def forward(self, x): # PyTorch 1.6 does not support empty tensor inference yet - if x.numel() == 0 and torch.__version__ <= '1.6': + if x.numel() == 0 and torch.__version__ <= '1.6.0': out_shape = list(x.shape[:2]) for i, k, p, s, d in zip(x.shape[-2:], _pair(self.kernel_size), _pair(self.padding), _pair(self.stride), From 6b52e9b55f302a59652fdff0bc56be9e9439beaf Mon Sep 17 00:00:00 2001 From: David de la Iglesia Castro Date: Fri, 25 Sep 2020 04:25:29 +0200 Subject: [PATCH 69/81] Add runner builder (#570) * Add build_runner * Parametrize test_runner * Add imports to runner __init__ * Refactor max_iters and max_epochs from run to init * Add assertion error messages * Add test_builder * Make change retro-compatible * Raise ValueError if max_epochs and max_iters --- mmcv/runner/__init__.py | 4 +- mmcv/runner/base_runner.py | 15 ++++-- mmcv/runner/builder.py | 7 +++ mmcv/runner/epoch_based_runner.py | 15 ++++-- mmcv/runner/iter_based_runner.py | 21 +++++--- tests/test_runner/test_hooks.py | 46 +++++++++-------- tests/test_runner/test_runner.py | 84 ++++++++++++++++++++----------- 7 files changed, 130 insertions(+), 62 deletions(-) create mode 100644 mmcv/runner/builder.py diff --git a/mmcv/runner/__init__.py b/mmcv/runner/__init__.py index dc6371b1e7..cbbc42d606 100644 --- a/mmcv/runner/__init__.py +++ b/mmcv/runner/__init__.py @@ -1,5 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. from .base_runner import BaseRunner +from .builder import RUNNERS, build_runner from .checkpoint import (_load_checkpoint, load_checkpoint, load_state_dict, save_checkpoint, weights_to_cpu) from .dist_utils import get_dist_info, init_dist, master_only @@ -30,5 +31,6 @@ 'OPTIMIZER_BUILDERS', 'OPTIMIZERS', 'DefaultOptimizerConstructor', 'build_optimizer', 'build_optimizer_constructor', 'IterLoader', 'set_random_seed', 'auto_fp16', 'force_fp32', 'wrap_fp16_model', - 'Fp16OptimizerHook', 'SyncBuffersHook', 'EMAHook' + 'Fp16OptimizerHook', 'SyncBuffersHook', 'EMAHook', 'build_runner', + 'RUNNERS' ] diff --git a/mmcv/runner/base_runner.py b/mmcv/runner/base_runner.py index c8a5513bf2..da73226007 100644 --- a/mmcv/runner/base_runner.py +++ b/mmcv/runner/base_runner.py @@ -43,6 +43,8 @@ class BaseRunner(metaclass=ABCMeta): meta (dict | None): A dict records some import information such as environment info and seed, which will be logged in logger hook. Defaults to None. + max_epochs (int, optional): Total training epochs. + max_iters (int, optional): Total training iterations. """ def __init__(self, @@ -51,7 +53,9 @@ def __init__(self, optimizer=None, work_dir=None, logger=None, - meta=None): + meta=None, + max_iters=None, + max_epochs=None): if batch_processor is not None: if not callable(batch_processor): raise TypeError('batch_processor must be callable, ' @@ -121,8 +125,13 @@ def __init__(self, self._epoch = 0 self._iter = 0 self._inner_iter = 0 - self._max_epochs = 0 - self._max_iters = 0 + + if max_epochs is not None and max_iters is not None: + raise ValueError( + 'Only one of `max_epochs` or `max_iters` can be set.') + + self._max_epochs = max_epochs + self._max_iters = max_iters # TODO: Redesign LogBuffer, it is not flexible and elegant enough self.log_buffer = LogBuffer() diff --git a/mmcv/runner/builder.py b/mmcv/runner/builder.py new file mode 100644 index 0000000000..e9989b0248 --- /dev/null +++ b/mmcv/runner/builder.py @@ -0,0 +1,7 @@ +from ..utils import Registry, build_from_cfg + +RUNNERS = Registry('runner') + + +def build_runner(cfg, default_args=None): + return build_from_cfg(cfg, RUNNERS, default_args=default_args) diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py index 06aa8b35dc..acf2e1169d 100644 --- a/mmcv/runner/epoch_based_runner.py +++ b/mmcv/runner/epoch_based_runner.py @@ -9,10 +9,12 @@ import mmcv from .base_runner import BaseRunner +from .builder import RUNNERS from .checkpoint import save_checkpoint from .utils import get_host_info +@RUNNERS.register_module() class EpochBasedRunner(BaseRunner): """Epoch-based Runner. @@ -67,7 +69,7 @@ def val(self, data_loader, **kwargs): self.call_hook('after_val_epoch') - def run(self, data_loaders, workflow, max_epochs, **kwargs): + def run(self, data_loaders, workflow, max_epochs=None, **kwargs): """Start running. Args: @@ -77,13 +79,19 @@ def run(self, data_loaders, workflow, max_epochs, **kwargs): running order and epochs. E.g, [('train', 2), ('val', 1)] means running 2 epochs for training and 1 epoch for validation, iteratively. - max_epochs (int): Total training epochs. """ assert isinstance(data_loaders, list) assert mmcv.is_list_of(workflow, tuple) assert len(data_loaders) == len(workflow) + if max_epochs is not None: + warnings.warn( + 'setting max_epochs in run is deprecated, ' + 'please set max_epochs in runner_config', DeprecationWarning) + self._max_epochs = max_epochs + + assert self._max_epochs is not None, ( + 'max_epochs must be specified during instantiation') - self._max_epochs = max_epochs for i, flow in enumerate(workflow): mode, epochs = flow if mode == 'train': @@ -164,6 +172,7 @@ def save_checkpoint(self, shutil.copy(filename, dst_file) +@RUNNERS.register_module() class Runner(EpochBasedRunner): """Deprecated name of EpochBasedRunner.""" diff --git a/mmcv/runner/iter_based_runner.py b/mmcv/runner/iter_based_runner.py index 24825ecf85..d02056e44a 100644 --- a/mmcv/runner/iter_based_runner.py +++ b/mmcv/runner/iter_based_runner.py @@ -3,12 +3,14 @@ import platform import shutil import time +import warnings import torch from torch.optim import Optimizer import mmcv from .base_runner import BaseRunner +from .builder import RUNNERS from .checkpoint import save_checkpoint from .hooks import IterTimerHook from .utils import get_host_info @@ -41,6 +43,7 @@ def __len__(self): return len(self._dataloader) +@RUNNERS.register_module() class IterBasedRunner(BaseRunner): """Iteration-based Runner. @@ -79,7 +82,7 @@ def val(self, data_loader, **kwargs): self.call_hook('after_val_iter') self._inner_iter += 1 - def run(self, data_loaders, workflow, max_iters, **kwargs): + def run(self, data_loaders, workflow, max_iters=None, **kwargs): """Start running. Args: @@ -89,24 +92,30 @@ def run(self, data_loaders, workflow, max_iters, **kwargs): running order and iterations. E.g, [('train', 10000), ('val', 1000)] means running 10000 iterations for training and 1000 iterations for validation, iteratively. - max_iters (int): Total training iterations. """ assert isinstance(data_loaders, list) assert mmcv.is_list_of(workflow, tuple) assert len(data_loaders) == len(workflow) + if max_iters is not None: + warnings.warn( + 'setting max_iters in run is deprecated, ' + 'please set max_iters in runner_config', DeprecationWarning) + self._max_iters = max_iters + assert self._max_iters is not None, ( + 'max_iters must be specified during instantiation') - self._max_iters = max_iters work_dir = self.work_dir if self.work_dir is not None else 'NONE' self.logger.info('Start running, host: %s, work_dir: %s', get_host_info(), work_dir) - self.logger.info('workflow: %s, max: %d iters', workflow, max_iters) + self.logger.info('workflow: %s, max: %d iters', workflow, + self._max_iters) self.call_hook('before_run') iter_loaders = [IterLoader(x) for x in data_loaders] self.call_hook('before_epoch') - while self.iter < max_iters: + while self.iter < self._max_iters: for i, flow in enumerate(workflow): self._inner_iter = 0 mode, iters = flow @@ -116,7 +125,7 @@ def run(self, data_loaders, workflow, max_iters, **kwargs): format(mode)) iter_runner = getattr(self, mode) for _ in range(iters): - if mode == 'train' and self.iter >= max_iters: + if mode == 'train' and self.iter >= self._max_iters: break iter_runner(iter_loaders[i], **kwargs) diff --git a/tests/test_runner/test_hooks.py b/tests/test_runner/test_hooks.py index a7f105a3fb..2d18ee5162 100644 --- a/tests/test_runner/test_hooks.py +++ b/tests/test_runner/test_hooks.py @@ -17,9 +17,9 @@ from torch.nn.init import constant_ from torch.utils.data import DataLoader -from mmcv.runner import (CheckpointHook, EMAHook, EpochBasedRunner, - IterTimerHook, MlflowLoggerHook, PaviLoggerHook, - WandbLoggerHook) +from mmcv.runner import (CheckpointHook, EMAHook, IterTimerHook, + MlflowLoggerHook, PaviLoggerHook, WandbLoggerHook, + build_runner) from mmcv.runner.hooks.lr_updater import CosineRestartLrUpdaterHook @@ -59,7 +59,7 @@ def val_step(self, x, optimizer, **kwargs): checkpointhook = CheckpointHook(interval=1, by_epoch=True) runner.register_hook(emahook, priority='HIGHEST') runner.register_hook(checkpointhook) - runner.run([loader, loader], [('train', 1), ('val', 1)], 1) + runner.run([loader, loader], [('train', 1), ('val', 1)]) checkpoint = torch.load(f'{runner.work_dir}/epoch_1.pth') contain_ema_buffer = False for name, value in checkpoint['state_dict'].items(): @@ -74,12 +74,12 @@ def val_step(self, x, optimizer, **kwargs): work_dir = runner.work_dir resume_ema_hook = EMAHook( momentum=0.5, warm_up=0, resume_from=f'{work_dir}/epoch_1.pth') - runner = _build_demo_runner() + runner = _build_demo_runner(max_epochs=2) runner.model = demo_model runner.register_hook(resume_ema_hook, priority='HIGHEST') checkpointhook = CheckpointHook(interval=1, by_epoch=True) runner.register_hook(checkpointhook) - runner.run([loader, loader], [('train', 1), ('val', 1)], 2) + runner.run([loader, loader], [('train', 1), ('val', 1)]) checkpoint = torch.load(f'{runner.work_dir}/epoch_2.pth') contain_ema_buffer = False for name, value in checkpoint['state_dict'].items(): @@ -101,7 +101,7 @@ def test_pavi_hook(): runner.meta = dict(config_dict=dict(lr=0.02, gpu_ids=range(1))) hook = PaviLoggerHook(add_graph=False, add_last_ckpt=True) runner.register_hook(hook) - runner.run([loader, loader], [('train', 1), ('val', 1)], 1) + runner.run([loader, loader], [('train', 1), ('val', 1)]) shutil.rmtree(runner.work_dir) assert hasattr(hook, 'writer') @@ -119,7 +119,7 @@ def test_sync_buffers_hook(): loader = DataLoader(torch.ones((5, 2))) runner = _build_demo_runner() runner.register_hook_from_cfg(dict(type='SyncBuffersHook')) - runner.run([loader, loader], [('train', 1), ('val', 1)], 1) + runner.run([loader, loader], [('train', 1), ('val', 1)]) shutil.rmtree(runner.work_dir) @@ -151,7 +151,7 @@ def test_momentum_runner_hook(): # add pavi hook hook = PaviLoggerHook(interval=1, add_graph=False, add_last_ckpt=True) runner.register_hook(hook) - runner.run([loader], [('train', 1)], 1) + runner.run([loader], [('train', 1)]) shutil.rmtree(runner.work_dir) # TODO: use a more elegant way to check values @@ -202,7 +202,7 @@ def test_cosine_runner_hook(): # add pavi hook hook = PaviLoggerHook(interval=1, add_graph=False, add_last_ckpt=True) runner.register_hook(hook) - runner.run([loader], [('train', 1)], 1) + runner.run([loader], [('train', 1)]) shutil.rmtree(runner.work_dir) # TODO: use a more elegant way to check values @@ -261,7 +261,7 @@ def test_cosine_restart_lr_update_hook(): # add pavi hook hook = PaviLoggerHook(interval=1, add_graph=False, add_last_ckpt=True) runner.register_hook(hook) - runner.run([loader], [('train', 1)], 1) + runner.run([loader], [('train', 1)]) shutil.rmtree(runner.work_dir) sys.modules['pavi'] = MagicMock() @@ -280,7 +280,7 @@ def test_cosine_restart_lr_update_hook(): # add pavi hook hook = PaviLoggerHook(interval=1, add_graph=False, add_last_ckpt=True) runner.register_hook(hook) - runner.run([loader], [('train', 1)], 1) + runner.run([loader], [('train', 1)]) shutil.rmtree(runner.work_dir) # TODO: use a more elegant way to check values @@ -312,7 +312,7 @@ def test_mlflow_hook(log_model): hook = MlflowLoggerHook(exp_name='test', log_model=log_model) runner.register_hook(hook) - runner.run([loader, loader], [('train', 1), ('val', 1)], 1) + runner.run([loader, loader], [('train', 1), ('val', 1)]) shutil.rmtree(runner.work_dir) hook.mlflow.set_experiment.assert_called_with('test') @@ -335,7 +335,7 @@ def test_wandb_hook(): loader = DataLoader(torch.ones((5, 2))) runner.register_hook(hook) - runner.run([loader, loader], [('train', 1), ('val', 1)], 1) + runner.run([loader, loader], [('train', 1), ('val', 1)]) shutil.rmtree(runner.work_dir) hook.wandb.init.assert_called_with() @@ -347,7 +347,9 @@ def test_wandb_hook(): hook.wandb.join.assert_called_with() -def _build_demo_runner(): +def _build_demo_runner(runner_type='EpochBasedRunner', + max_epochs=1, + max_iters=None): class Model(nn.Module): @@ -374,11 +376,15 @@ def val_step(self, x, optimizer, **kwargs): ]) tmp_dir = tempfile.mkdtemp() - runner = EpochBasedRunner( - model=model, - work_dir=tmp_dir, - optimizer=optimizer, - logger=logging.getLogger()) + runner = build_runner( + dict(type=runner_type), + default_args=dict( + model=model, + work_dir=tmp_dir, + optimizer=optimizer, + logger=logging.getLogger(), + max_epochs=max_epochs, + max_iters=max_iters)) runner.register_checkpoint_hook(dict(interval=1)) runner.register_logger_hooks(log_config) return runner diff --git a/tests/test_runner/test_runner.py b/tests/test_runner/test_runner.py index efc6b191ec..3434c3390c 100644 --- a/tests/test_runner/test_runner.py +++ b/tests/test_runner/test_runner.py @@ -11,7 +11,8 @@ import torch.nn as nn from mmcv.parallel import MMDataParallel -from mmcv.runner import EpochBasedRunner +from mmcv.runner import (RUNNERS, EpochBasedRunner, IterBasedRunner, + build_runner) class OldStyleModel(nn.Module): @@ -30,7 +31,29 @@ def val_step(self): pass -def test_epoch_based_runner(): +def test_build_runner(): + temp_root = tempfile.gettempdir() + dir_name = ''.join( + [random.choice(string.ascii_letters) for _ in range(10)]) + + default_args = dict( + model=Model(), + work_dir=osp.join(temp_root, dir_name), + logger=logging.getLogger()) + cfg = dict(type='EpochBasedRunner', max_epochs=1) + runner = build_runner(cfg, default_args=default_args) + assert runner._max_epochs == 1 + cfg = dict(type='IterBasedRunner', max_iters=1) + runner = build_runner(cfg, default_args=default_args) + assert runner._max_iters == 1 + + with pytest.raises(ValueError, match='Only one of'): + cfg = dict(type='IterBasedRunner', max_epochs=1, max_iters=1) + runner = build_runner(cfg, default_args=default_args) + + +@pytest.mark.parametrize('runner_class', RUNNERS.module_dict.values()) +def test_epoch_based_runner(runner_class): with pytest.warns(UserWarning): # batch_processor is deprecated @@ -39,48 +62,46 @@ def test_epoch_based_runner(): def batch_processor(): pass - _ = EpochBasedRunner( - model, batch_processor, logger=logging.getLogger()) + _ = runner_class(model, batch_processor, logger=logging.getLogger()) with pytest.raises(TypeError): # batch_processor must be callable model = OldStyleModel() - _ = EpochBasedRunner( - model, batch_processor=0, logger=logging.getLogger()) + _ = runner_class(model, batch_processor=0, logger=logging.getLogger()) with pytest.raises(TypeError): # optimizer must be a optimizer or a dict of optimizers model = Model() optimizer = 'NotAOptimizer' - _ = EpochBasedRunner( + _ = runner_class( model, optimizer=optimizer, logger=logging.getLogger()) with pytest.raises(TypeError): # optimizer must be a optimizer or a dict of optimizers model = Model() optimizers = dict(optim1=torch.optim.Adam(), optim2='NotAOptimizer') - _ = EpochBasedRunner( + _ = runner_class( model, optimizer=optimizers, logger=logging.getLogger()) with pytest.raises(TypeError): # logger must be a logging.Logger model = Model() - _ = EpochBasedRunner(model, logger=None) + _ = runner_class(model, logger=None) with pytest.raises(TypeError): # meta must be a dict or None model = Model() - _ = EpochBasedRunner(model, logger=logging.getLogger(), meta=['list']) + _ = runner_class(model, logger=logging.getLogger(), meta=['list']) with pytest.raises(AssertionError): # model must implement the method train_step() model = OldStyleModel() - _ = EpochBasedRunner(model, logger=logging.getLogger()) + _ = runner_class(model, logger=logging.getLogger()) with pytest.raises(TypeError): # work_dir must be a str or None model = Model() - _ = EpochBasedRunner(model, work_dir=1, logger=logging.getLogger()) + _ = runner_class(model, work_dir=1, logger=logging.getLogger()) with pytest.raises(RuntimeError): # batch_processor and train_step() cannot be both set @@ -89,8 +110,7 @@ def batch_processor(): pass model = Model() - _ = EpochBasedRunner( - model, batch_processor, logger=logging.getLogger()) + _ = runner_class(model, batch_processor, logger=logging.getLogger()) # test work_dir model = Model() @@ -98,23 +118,24 @@ def batch_processor(): dir_name = ''.join( [random.choice(string.ascii_letters) for _ in range(10)]) work_dir = osp.join(temp_root, dir_name) - _ = EpochBasedRunner(model, work_dir=work_dir, logger=logging.getLogger()) + _ = runner_class(model, work_dir=work_dir, logger=logging.getLogger()) assert osp.isdir(work_dir) - _ = EpochBasedRunner(model, work_dir=work_dir, logger=logging.getLogger()) + _ = runner_class(model, work_dir=work_dir, logger=logging.getLogger()) assert osp.isdir(work_dir) os.removedirs(work_dir) -def test_runner_with_parallel(): +@pytest.mark.parametrize('runner_class', RUNNERS.module_dict.values()) +def test_runner_with_parallel(runner_class): def batch_processor(): pass model = MMDataParallel(OldStyleModel()) - _ = EpochBasedRunner(model, batch_processor, logger=logging.getLogger()) + _ = runner_class(model, batch_processor, logger=logging.getLogger()) model = MMDataParallel(Model()) - _ = EpochBasedRunner(model, logger=logging.getLogger()) + _ = runner_class(model, logger=logging.getLogger()) with pytest.raises(RuntimeError): # batch_processor and train_step() cannot be both set @@ -123,13 +144,13 @@ def batch_processor(): pass model = MMDataParallel(Model()) - _ = EpochBasedRunner( - model, batch_processor, logger=logging.getLogger()) + _ = runner_class(model, batch_processor, logger=logging.getLogger()) -def test_save_checkpoint(): +@pytest.mark.parametrize('runner_class', RUNNERS.module_dict.values()) +def test_save_checkpoint(runner_class): model = Model() - runner = EpochBasedRunner(model=model, logger=logging.getLogger()) + runner = runner_class(model=model, logger=logging.getLogger()) with pytest.raises(TypeError): # meta should be None or dict @@ -139,18 +160,23 @@ def test_save_checkpoint(): runner.save_checkpoint(root) latest_path = osp.join(root, 'latest.pth') - epoch1_path = osp.join(root, 'epoch_1.pth') - assert osp.exists(latest_path) - assert osp.exists(epoch1_path) - assert osp.realpath(latest_path) == osp.realpath(epoch1_path) + + if isinstance(runner, EpochBasedRunner): + first_ckp_path = osp.join(root, 'epoch_1.pth') + elif isinstance(runner, IterBasedRunner): + first_ckp_path = osp.join(root, 'iter_1.pth') + + assert osp.exists(first_ckp_path) + assert osp.realpath(latest_path) == osp.realpath(first_ckp_path) torch.load(latest_path) -def test_build_lr_momentum_hook(): +@pytest.mark.parametrize('runner_class', RUNNERS.module_dict.values()) +def test_build_lr_momentum_hook(runner_class): model = Model() - runner = EpochBasedRunner(model=model, logger=logging.getLogger()) + runner = runner_class(model=model, logger=logging.getLogger()) # test policy that is already title lr_config = dict( From 467b4883b9fc88f17ca3c3220109713d3363d093 Mon Sep 17 00:00:00 2001 From: "q.yao" Date: Fri, 25 Sep 2020 20:19:37 +0800 Subject: [PATCH 70/81] add torchvision roi_align with aligned=True (#581) * add torchvision roi_align with aligned=True * fix for lint test * fix for lint test2 * format use yapf --- mmcv/ops/roi_align.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/mmcv/ops/roi_align.py b/mmcv/ops/roi_align.py index a7bf752852..dd62543c37 100644 --- a/mmcv/ops/roi_align.py +++ b/mmcv/ops/roi_align.py @@ -152,8 +152,6 @@ def __init__(self, self.pool_mode = pool_mode self.aligned = aligned self.use_torchvision = use_torchvision - assert not (use_torchvision and - aligned), 'Torchvision does not support aligned RoIAlgin' def forward(self, input, rois): """ @@ -164,8 +162,16 @@ def forward(self, input, rois): """ if self.use_torchvision: from torchvision.ops import roi_align as tv_roi_align - return tv_roi_align(input, rois, self.output_size, - self.spatial_scale, self.sampling_ratio) + if 'aligned' in tv_roi_align.__code__.co_varnames: + return tv_roi_align(input, rois, self.output_size, + self.spatial_scale, self.sampling_ratio, + self.aligned) + else: + if self.aligned: + rois -= rois.new_tensor([0.] + + [0.5 / self.spatial_scale] * 4) + return tv_roi_align(input, rois, self.output_size, + self.spatial_scale, self.sampling_ratio) else: return roi_align(input, rois, self.output_size, self.spatial_scale, self.sampling_ratio, self.pool_mode, self.aligned) From ed2887bb72b7c8cee11aba94663831b8f6bd8827 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Fri, 25 Sep 2020 20:51:58 +0800 Subject: [PATCH 71/81] Support to specify LR of DCN's conv_offset (#344) * Support to specify LR of DCN's conv_offset * Resolve comments & add unit test * Resolve formats * Fix CI for DCN * Mock DCN when cpu only * Use mock for cpu testing * Fix docstring and support ModulatedDCN * set offset_lr_mult as dcn's arguments, link CU-49u01p * fix lr bug * fall back to set LR in constructor * resolve comments --- mmcv/ops/deform_conv.py | 3 +- mmcv/runner/optimizer/default_constructor.py | 53 +++++++-- mmcv/utils/ext_loader.py | 6 + tests/test_runner/test_optimizer.py | 111 ++++++++++++++----- 4 files changed, 138 insertions(+), 35 deletions(-) diff --git a/mmcv/ops/deform_conv.py b/mmcv/ops/deform_conv.py index 355d59bf00..7a70fa9107 100644 --- a/mmcv/ops/deform_conv.py +++ b/mmcv/ops/deform_conv.py @@ -186,6 +186,8 @@ def __init__(self, bias=False): super(DeformConv2d, self).__init__() + assert not bias, \ + f'bias={bias} is not supported in DeformConv2d.' assert in_channels % groups == 0, \ f'in_channels {in_channels} cannot be divisible by groups {groups}' assert out_channels % groups == 0, \ @@ -267,7 +269,6 @@ class DeformConv2dPack(DeformConv2d): def __init__(self, *args, **kwargs): super(DeformConv2dPack, self).__init__(*args, **kwargs) - self.conv_offset = nn.Conv2d( self.in_channels, self.deform_groups * 2 * self.kernel_size[0] * self.kernel_size[1], diff --git a/mmcv/runner/optimizer/default_constructor.py b/mmcv/runner/optimizer/default_constructor.py index e886c616a0..477bf07fa4 100644 --- a/mmcv/runner/optimizer/default_constructor.py +++ b/mmcv/runner/optimizer/default_constructor.py @@ -4,6 +4,7 @@ from torch.nn import GroupNorm, LayerNorm from mmcv.utils import _BatchNorm, _InstanceNorm, build_from_cfg, is_list_of +from mmcv.utils.ext_loader import check_ops_exist from .builder import OPTIMIZER_BUILDERS, OPTIMIZERS @@ -27,19 +28,34 @@ class DefaultOptimizerConstructor: and ``decay_mult``. See Example 2 below. - ``bias_lr_mult`` (float): It will be multiplied to the learning rate for all bias parameters (except for those in normalization - layers). + layers and offset layers of DCN). - ``bias_decay_mult`` (float): It will be multiplied to the weight decay for all bias parameters (except for those in - normalization layers and depthwise conv layers). + normalization layers, depthwise conv layers, offset layers of DCN). - ``norm_decay_mult`` (float): It will be multiplied to the weight decay for all weight and bias parameters of normalization layers. - ``dwconv_decay_mult`` (float): It will be multiplied to the weight decay for all weight and bias parameters of depthwise conv layers. + - ``dcn_offset_lr_mult`` (float): It will be multiplied to the learning + rate for parameters of offset layer in the deformable convs + of a model. - ``bypass_duplicate`` (bool): If true, the duplicate parameters would not be added into optimizer. Default: False. + Note: + 1. If the option ``dcn_offset_lr_mult`` is used, the constructor will + override the effect of ``bias_lr_mult`` in the bias of offset + layer. So be careful when using both ``bias_lr_mult`` and + ``dcn_offset_lr_mult``. If you wish to apply both of them to the + offset layer in deformable convs, set ``dcn_offset_lr_mult`` + to the original ``dcn_offset_lr_mult`` * ``bias_lr_mult``. + 2. If the option ``dcn_offset_lr_mult`` is used, the construtor will + apply it to all the DCN layers in the model. So be carefull when + the model contains multiple DCN layers in places other than + backbone. + Args: model (:obj:`nn.Module`): The model with parameters to be optimized. optimizer_cfg (dict): The config dict of the optimizer. @@ -117,7 +133,7 @@ def _is_in(self, param_group, param_group_list): return not param.isdisjoint(param_set) - def add_params(self, params, module, prefix=''): + def add_params(self, params, module, prefix='', is_dcn_module=None): """Add all parameters of module to the params list. The parameters of the given module will be added to the list of param @@ -128,6 +144,9 @@ def add_params(self, params, module, prefix=''): in place. module (nn.Module): The module to be added. prefix (str): The prefix of the module + is_dcn_module (int|float|None): If the current module is a + submodule of DCN, `is_dcn_module` will be passed to + control conv_offset layer's learning rate. Defaults to None. """ # get param-wise options custom_keys = self.paramwise_cfg.get('custom_keys', {}) @@ -139,6 +158,7 @@ def add_params(self, params, module, prefix=''): norm_decay_mult = self.paramwise_cfg.get('norm_decay_mult', 1.) dwconv_decay_mult = self.paramwise_cfg.get('dwconv_decay_mult', 1.) bypass_duplicate = self.paramwise_cfg.get('bypass_duplicate', False) + dcn_offset_lr_mult = self.paramwise_cfg.get('dcn_offset_lr_mult', 1.) # special rules for norm layers and depth-wise conv layers is_norm = isinstance(module, @@ -167,10 +187,18 @@ def add_params(self, params, module, prefix=''): decay_mult = custom_keys[key].get('decay_mult', 1.) param_group['weight_decay'] = self.base_wd * decay_mult break + if not is_custom: - # bias_lr_mult affects all bias parameters except for norm.bias - if name == 'bias' and not is_norm: + # bias_lr_mult affects all bias parameters + # except for norm.bias dcn.conv_offset.bias + if name == 'bias' and not (is_norm or is_dcn_module): param_group['lr'] = self.base_lr * bias_lr_mult + + if (prefix.find('conv_offset') != -1 and is_dcn_module + and isinstance(module, torch.nn.Conv2d)): + # deal with both dcn_offset's bias & weight + param_group['lr'] = self.base_lr * dcn_offset_lr_mult + # apply weight decay policies if self.base_wd is not None: # norm decay @@ -182,14 +210,25 @@ def add_params(self, params, module, prefix=''): param_group[ 'weight_decay'] = self.base_wd * dwconv_decay_mult # bias lr and decay - elif name == 'bias': + elif name == 'bias' and not is_dcn_module: + # TODO: current bias_decay_mult will have affect on DCN param_group[ 'weight_decay'] = self.base_wd * bias_decay_mult params.append(param_group) + if check_ops_exist(): + from mmcv.ops import DeformConv2d, ModulatedDeformConv2d + is_dcn_module = isinstance(module, + (DeformConv2d, ModulatedDeformConv2d)) + else: + is_dcn_module = False for child_name, child_mod in module.named_children(): child_prefix = f'{prefix}.{child_name}' if prefix else child_name - self.add_params(params, child_mod, prefix=child_prefix) + self.add_params( + params, + child_mod, + prefix=child_prefix, + is_dcn_module=is_dcn_module) def __call__(self, model): if hasattr(model, 'module'): diff --git a/mmcv/utils/ext_loader.py b/mmcv/utils/ext_loader.py index d9e5a811d0..e56651c6dd 100644 --- a/mmcv/utils/ext_loader.py +++ b/mmcv/utils/ext_loader.py @@ -1,5 +1,6 @@ import importlib import os +import pkgutil from collections import namedtuple import torch @@ -25,3 +26,8 @@ def load_ext(name, funcs): ext_list.append( extension.load(fun, name, lib_dir=lib_root).op_) return ExtModule(*ext_list) + + +def check_ops_exist(): + ext_loader = pkgutil.find_loader('mmcv._ext') + return ext_loader is not None diff --git a/tests/test_runner/test_optimizer.py b/tests/test_runner/test_optimizer.py index 4951f97f5b..cae22f7b51 100644 --- a/tests/test_runner/test_optimizer.py +++ b/tests/test_runner/test_optimizer.py @@ -1,4 +1,6 @@ +import sys import warnings +from unittest.mock import MagicMock import pytest import torch @@ -7,6 +9,12 @@ from mmcv.runner import OPTIMIZER_BUILDERS, DefaultOptimizerConstructor from mmcv.runner.optimizer import build_optimizer, build_optimizer_constructor from mmcv.runner.optimizer.builder import TORCH_OPTIMIZERS +from mmcv.utils.ext_loader import check_ops_exist + +OPS_AVAILABLE = check_ops_exist() +if not OPS_AVAILABLE: + sys.modules['mmcv.ops'] = MagicMock( + DeformConv2d=dict, ModulatedDeformConv2d=dict) class SubModel(nn.Module): @@ -30,6 +38,10 @@ def __init__(self): self.conv2 = nn.Conv2d(4, 2, kernel_size=1) self.bn = nn.BatchNorm2d(2) self.sub = SubModel() + if OPS_AVAILABLE: + from mmcv.ops import DeformConv2dPack + self.dcn = DeformConv2dPack( + 3, 4, kernel_size=3, deformable_groups=1) def forward(self, x): return x @@ -46,6 +58,10 @@ def __init__(self): self.sub = SubModel() self.conv3 = nn.Sequential(nn.Conv2d(3, 4, kernel_size=1, bias=False)) self.conv3[0] = self.conv1[0] + if OPS_AVAILABLE: + from mmcv.ops import DeformConv2dPack + self.dcn = DeformConv2dPack( + 3, 4, kernel_size=3, deformable_groups=1) def forward(self, x): return x @@ -72,11 +88,19 @@ def check_default_optimizer(optimizer, model, prefix=''): assert optimizer.defaults['momentum'] == momentum assert optimizer.defaults['weight_decay'] == base_wd param_groups = optimizer.param_groups[0] - param_names = [ - 'param1', 'conv1.weight', 'conv2.weight', 'conv2.bias', 'bn.weight', - 'bn.bias', 'sub.param1', 'sub.conv1.weight', 'sub.conv1.bias', - 'sub.gn.weight', 'sub.gn.bias' - ] + if OPS_AVAILABLE: + param_names = [ + 'param1', 'conv1.weight', 'conv2.weight', 'conv2.bias', + 'bn.weight', 'bn.bias', 'sub.param1', 'sub.conv1.weight', + 'sub.conv1.bias', 'sub.gn.weight', 'sub.gn.bias', 'dcn.weight', + 'dcn.conv_offset.weight', 'dcn.conv_offset.bias' + ] + else: + param_names = [ + 'param1', 'conv1.weight', 'conv2.weight', 'conv2.bias', + 'bn.weight', 'bn.bias', 'sub.param1', 'sub.conv1.weight', + 'sub.conv1.bias', 'sub.gn.weight', 'sub.gn.bias' + ] param_dict = dict(model.named_parameters()) assert len(param_groups['params']) == len(param_names) for i in range(len(param_groups['params'])): @@ -84,14 +108,15 @@ def check_default_optimizer(optimizer, model, prefix=''): param_dict[prefix + param_names[i]]) -def check_optimizer(optimizer, - model, - prefix='', - bias_lr_mult=1, - bias_decay_mult=1, - norm_decay_mult=1, - dwconv_decay_mult=1, - bypass_duplicate=False): +def check_sgd_optimizer(optimizer, + model, + prefix='', + bias_lr_mult=1, + bias_decay_mult=1, + norm_decay_mult=1, + dwconv_decay_mult=1, + dcn_offset_lr_mult=1, + bypass_duplicate=False): param_groups = optimizer.param_groups assert isinstance(optimizer, torch.optim.SGD) assert optimizer.defaults['lr'] == base_lr @@ -103,6 +128,7 @@ def check_optimizer(optimizer, param_group = param_groups[i] assert torch.equal(param_group['params'][0], param) assert param_group['momentum'] == momentum + # param1 param1 = param_groups[0] assert param1['lr'] == base_lr @@ -148,6 +174,19 @@ def check_optimizer(optimizer, assert sub_gn_bias['lr'] == base_lr assert sub_gn_bias['weight_decay'] == base_wd * norm_decay_mult + if torch.cuda.is_available(): + dcn_conv_weight = param_groups[11] + assert dcn_conv_weight['lr'] == base_lr + assert dcn_conv_weight['weight_decay'] == base_wd + + dcn_offset_weight = param_groups[12] + assert dcn_offset_weight['lr'] == base_lr * dcn_offset_lr_mult + assert dcn_offset_weight['weight_decay'] == base_wd + + dcn_offset_bias = param_groups[13] + assert dcn_offset_bias['lr'] == base_lr * dcn_offset_lr_mult + assert dcn_offset_bias['weight_decay'] == base_wd + def test_default_optimizer_constructor(): model = ExampleModel() @@ -229,11 +268,12 @@ def test_default_optimizer_constructor(): bias_lr_mult=2, bias_decay_mult=0.5, norm_decay_mult=0, - dwconv_decay_mult=0.1) + dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1) optim_constructor = DefaultOptimizerConstructor(optimizer_cfg, paramwise_cfg) optimizer = optim_constructor(model) - check_optimizer(optimizer, model, **paramwise_cfg) + check_sgd_optimizer(optimizer, model, **paramwise_cfg) # paramwise_cfg with ExampleModel, weight decay is None model = ExampleModel() @@ -274,6 +314,14 @@ def test_default_optimizer_constructor(): # sub.gn.bias assert param_groups[10]['lr'] == base_lr + if OPS_AVAILABLE: + # dcn.weight + assert param_groups[11]['lr'] == base_lr + # dcn.conv_offset.weight + assert param_groups[12]['lr'] == base_lr + # dcn.conv_offset.bias + assert param_groups[13]['lr'] == base_lr + # paramwise_cfg with pseudo data parallel model = PseudoDataParallel() optimizer_cfg = dict( @@ -282,11 +330,12 @@ def test_default_optimizer_constructor(): bias_lr_mult=2, bias_decay_mult=0.5, norm_decay_mult=0, - dwconv_decay_mult=0.1) + dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1) optim_constructor = DefaultOptimizerConstructor(optimizer_cfg, paramwise_cfg) optimizer = optim_constructor(model) - check_optimizer(optimizer, model, prefix='module.', **paramwise_cfg) + check_sgd_optimizer(optimizer, model, prefix='module.', **paramwise_cfg) # paramwise_cfg with DataParallel if torch.cuda.is_available(): @@ -297,11 +346,13 @@ def test_default_optimizer_constructor(): bias_lr_mult=2, bias_decay_mult=0.5, norm_decay_mult=0, - dwconv_decay_mult=0.1) + dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1) optim_constructor = DefaultOptimizerConstructor( optimizer_cfg, paramwise_cfg) optimizer = optim_constructor(model) - check_optimizer(optimizer, model, prefix='module.', **paramwise_cfg) + check_sgd_optimizer( + optimizer, model, prefix='module.', **paramwise_cfg) # paramwise_cfg with ExampleModel and no grad for param in model.parameters(): @@ -342,6 +393,7 @@ def test_default_optimizer_constructor(): bias_decay_mult=0.5, norm_decay_mult=0, dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1, bypass_duplicate=True) optim_constructor = DefaultOptimizerConstructor(optimizer_cfg, paramwise_cfg) @@ -352,8 +404,9 @@ def test_default_optimizer_constructor(): assert str(w[0].message) == 'conv3.0 is duplicate. It is skipped ' \ 'since bypass_duplicate=True' model_parameters = list(model.parameters()) - assert len(optimizer.param_groups) == len(model_parameters) == 11 - check_optimizer(optimizer, model, **paramwise_cfg) + num_params = 14 if OPS_AVAILABLE else 11 + assert len(optimizer.param_groups) == len(model_parameters) == num_params + check_sgd_optimizer(optimizer, model, **paramwise_cfg) # test DefaultOptimizerConstructor with custom_keys and ExampleModel model = ExampleModel() @@ -435,7 +488,8 @@ def test_default_optimizer_constructor(): 'weight_decay': base_wd }) - assert len(param_groups) == 11 + num_params = 14 if OPS_AVAILABLE else 11 + assert len(param_groups) == num_params for i, (name, param) in enumerate(model.named_parameters()): assert torch.equal(param_groups[i]['params'][0], param) for group, settings in zip(groups, group_settings): @@ -481,7 +535,8 @@ def test_default_optimizer_constructor(): 'weight_decay': 0 }) - assert len(param_groups) == 11 + num_params = 14 if OPS_AVAILABLE else 11 + assert len(param_groups) == num_params for i, (name, param) in enumerate(model.named_parameters()): assert torch.equal(param_groups[i]['params'][0], param) for group, settings in zip(groups, group_settings): @@ -507,14 +562,15 @@ def test_build_optimizer_constructor(): bias_lr_mult=2, bias_decay_mult=0.5, norm_decay_mult=0, - dwconv_decay_mult=0.1) + dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1) optim_constructor_cfg = dict( type='DefaultOptimizerConstructor', optimizer_cfg=optimizer_cfg, paramwise_cfg=paramwise_cfg) optim_constructor = build_optimizer_constructor(optim_constructor_cfg) optimizer = optim_constructor(model) - check_optimizer(optimizer, model, **paramwise_cfg) + check_sgd_optimizer(optimizer, model, **paramwise_cfg) from mmcv.runner import OPTIMIZERS from mmcv.utils import build_from_cfg @@ -577,6 +633,7 @@ def test_build_optimizer(): bias_lr_mult=2, bias_decay_mult=0.5, norm_decay_mult=0, - dwconv_decay_mult=0.1)) + dwconv_decay_mult=0.1, + dcn_offset_lr_mult=0.1)) optimizer = build_optimizer(model, optimizer_cfg) - check_optimizer(optimizer, model, **optimizer_cfg['paramwise_cfg']) + check_sgd_optimizer(optimizer, model, **optimizer_cfg['paramwise_cfg']) From 71952ff3aa106f6967dfb8c93e00faa4d622ccda Mon Sep 17 00:00:00 2001 From: Jerry Jiarui XU Date: Sun, 27 Sep 2020 00:20:13 +0800 Subject: [PATCH 72/81] [Enhance] Switch to https://download.openmmlab.com (#583) --- README.md | 28 +++++------ mmcv/model_zoo/mmcls.json | 22 ++++----- mmcv/model_zoo/open_mmlab.json | 88 +++++++++++++++++----------------- 3 files changed, 69 insertions(+), 69 deletions(-) diff --git a/README.md b/README.md index cb9f8bfdcc..ff0bb85cc8 100644 --- a/README.md +++ b/README.md @@ -59,31 +59,31 @@ We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA CUDA torch 1.6torch 1.5torch 1.4torch 1.3 10.2 -
install 
pip install mmcv-full==latest+torch1.6.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.5.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.6.0+cu102 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.5.0+cu102 -f https://download.openmmlab.com/mmcv/dist/index.html
10.1 -
install 
 pip install mmcv-full==latest+torch1.6.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.6.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.4.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.3.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
9.2 -
install 
 pip install mmcv-full==latest+torch1.6.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
 pip install mmcv-full==latest+torch1.5.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.6.0+cu92 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.5.0+cu92 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.4.0+cu92 -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.3.0+cu92 -f https://download.openmmlab.com/mmcv/dist/index.html
cpu -
install 
 pip install mmcv-full==latest+torch1.6.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
 pip install mmcv-full==latest+torch1.5.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.4.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-
install 
pip install mmcv-full==latest+torch1.3.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.6.0+cpu -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
 pip install mmcv-full==latest+torch1.5.0+cpu -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.4.0+cpu -f https://download.openmmlab.com/mmcv/dist/index.html
+
install 
pip install mmcv-full==latest+torch1.3.0+cpu -f https://download.openmmlab.com/mmcv/dist/index.html
diff --git a/mmcv/model_zoo/mmcls.json b/mmcv/model_zoo/mmcls.json index 9c16857a4a..822b995156 100644 --- a/mmcv/model_zoo/mmcls.json +++ b/mmcv/model_zoo/mmcls.json @@ -1,13 +1,13 @@ { - "resnet50_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d50_batch256_20200708-1ad0ce94.pth", - "resnet101_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d101_batch256_20200708-9cb302ef.pth", - "resnet152_v1d": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnetv1d152_batch256_20200708-e79cb6a2.pth", - "resnext50": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext50_32x4d_batch256_20200708-c07adbb7.pth", - "resnext101": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext101_32x8d_batch256_20200708-1ec34aa7.pth", - "resnext152": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/resnext152_32x4d_batch256_20200708-aab5034c.pth", - "se-resnet50": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/se-resnet50_batch256_20200804-ae206104.pth", - "se-resnet101": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/se-resnet101_batch256_20200804-ba5b51d4.pth", - "shufflenet_v1": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/shufflenet_v1_batch1024_20200804-5d6cec73.pth", - "shufflenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/shufflenet_v2_batch1024_20200812-5bf4721e.pth", - "mobilenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmclassification/v0/imagenet/mobilenet_v2_batch256_20200708-3b2dc3af.pth" + "resnet50_v1d": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnetv1d50_batch256_20200708-1ad0ce94.pth", + "resnet101_v1d": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnetv1d101_batch256_20200708-9cb302ef.pth", + "resnet152_v1d": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnetv1d152_batch256_20200708-e79cb6a2.pth", + "resnext50": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnext50_32x4d_batch256_20200708-c07adbb7.pth", + "resnext101": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnext101_32x8d_batch256_20200708-1ec34aa7.pth", + "resnext152": "https://download.openmmlab.com/mmclassification/v0/imagenet/resnext152_32x4d_batch256_20200708-aab5034c.pth", + "se-resnet50": "https://download.openmmlab.com/mmclassification/v0/imagenet/se-resnet50_batch256_20200804-ae206104.pth", + "se-resnet101": "https://download.openmmlab.com/mmclassification/v0/imagenet/se-resnet101_batch256_20200804-ba5b51d4.pth", + "shufflenet_v1": "https://download.openmmlab.com/mmclassification/v0/imagenet/shufflenet_v1_batch1024_20200804-5d6cec73.pth", + "shufflenet_v2": "https://download.openmmlab.com/mmclassification/v0/imagenet/shufflenet_v2_batch1024_20200812-5bf4721e.pth", + "mobilenet_v2": "https://download.openmmlab.com/mmclassification/v0/imagenet/mobilenet_v2_batch256_20200708-3b2dc3af.pth" } diff --git a/mmcv/model_zoo/open_mmlab.json b/mmcv/model_zoo/open_mmlab.json index fd79ce9a35..c0e975d453 100644 --- a/mmcv/model_zoo/open_mmlab.json +++ b/mmcv/model_zoo/open_mmlab.json @@ -1,46 +1,46 @@ { - "vgg16_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/vgg16_caffe-292e1171.pth", - "detectron/resnet50_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_caffe-788b5fa3.pth", - "detectron2/resnet50_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_msra-5891d200.pth", - "detectron/resnet101_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_caffe-3ad79236.pth", - "detectron2/resnet101_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_msra-6cc46731.pth", - "detectron2/resnext101_32x8d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x8d-1516f1aa.pth", - "resnext50_32x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50-32x4d-0ab1a123.pth", - "resnext101_32x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d-a5af3160.pth", - "resnext101_64x4d": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_64x4d-ee2c6f71.pth", - "contrib/resnet50_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn_thangvubk-ad1730dd.pth", - "detectron/resnet50_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn-9186a21c.pth", - "detectron/resnet101_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_gn-cac0ab98.pth", - "jhu/resnet50_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_gn_ws-15beedd8.pth", - "jhu/resnet101_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_gn_ws-3e3c308c.pth", - "jhu/resnext50_32x4d_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50_32x4d_gn_ws-0d87ac85.pth", - "jhu/resnext101_32x4d_gn_ws": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d_gn_ws-34ac1a9e.pth", - "jhu/resnext50_32x4d_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext50_32x4d_gn-c7e8b754.pth", - "jhu/resnext101_32x4d_gn": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnext101_32x4d_gn-ac3bb84e.pth", - "msra/hrnetv2_w18_small": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w18_small-b5a04e21.pth", - "msra/hrnetv2_w18": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w18-00eb2006.pth", - "msra/hrnetv2_w32": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w32-dc9eeb4f.pth", - "msra/hrnetv2_w40": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w40-ed0b031c.pth", - "msra/hrnetv2_w48": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", - "bninception_caffe": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/bn_inception_caffe-ed2e8665.pth", - "kin400/i3d_r50_f32s2_k400": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/i3d_r50_f32s2_k400-2c57e077.pth", - "kin400/nl3d_r50_f32s2_k400": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/nl3d_r50_f32s2_k400-fa7e7caa.pth", - "res2net101_v1d_26w_4s": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/res2net101_v1d_26w_4s_mmdetv2-f0a600f9.pth", - "regnetx_400mf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_400mf-a5b10d96.pth", - "regnetx_800mf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_800mf-1f4be4c7.pth", - "regnetx_1.6gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_1.6gf-5791c176.pth", - "regnetx_3.2gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_3.2gf-c2599b0f.pth", - "regnetx_4.0gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_4.0gf-a88f671e.pth", - "regnetx_6.4gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_6.4gf-006af45d.pth", - "regnetx_8.0gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_8.0gf-3c68abe7.pth", - "regnetx_12gf": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/regnetx_12gf-4c2a3350.pth", - "resnet50_v1c": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet50_v1c-2cccc1ad.pth", - "resnet101_v1c": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnet101_v1c-e67eebb6.pth", - "mmedit/vgg16": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/vgg_state_dict.pth", - "mmedit/res34_en_nomixup": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/model_best_resnet34_En_nomixup.pth", - "mmedit/mobilenet_v2": "https://openmmlab.oss-accelerate.aliyuncs.com/mmediting/third_party/mobilenet_v2.pth", - "resnest50": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest50_d2-7497a55b.pth", - "resnest101": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest101_d2-f3b931b2.pth", - "resnest200": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/resnest200_d2-ca88e41f.pth", - "darknet53": "https://openmmlab.oss-accelerate.aliyuncs.com/pretrain/third_party/darknet53-a628ea1b.pth" + "vgg16_caffe": "https://download.openmmlab.com/pretrain/third_party/vgg16_caffe-292e1171.pth", + "detectron/resnet50_caffe": "https://download.openmmlab.com/pretrain/third_party/resnet50_caffe-788b5fa3.pth", + "detectron2/resnet50_caffe": "https://download.openmmlab.com/pretrain/third_party/resnet50_msra-5891d200.pth", + "detectron/resnet101_caffe": "https://download.openmmlab.com/pretrain/third_party/resnet101_caffe-3ad79236.pth", + "detectron2/resnet101_caffe": "https://download.openmmlab.com/pretrain/third_party/resnet101_msra-6cc46731.pth", + "detectron2/resnext101_32x8d": "https://download.openmmlab.com/pretrain/third_party/resnext101_32x8d-1516f1aa.pth", + "resnext50_32x4d": "https://download.openmmlab.com/pretrain/third_party/resnext50-32x4d-0ab1a123.pth", + "resnext101_32x4d": "https://download.openmmlab.com/pretrain/third_party/resnext101_32x4d-a5af3160.pth", + "resnext101_64x4d": "https://download.openmmlab.com/pretrain/third_party/resnext101_64x4d-ee2c6f71.pth", + "contrib/resnet50_gn": "https://download.openmmlab.com/pretrain/third_party/resnet50_gn_thangvubk-ad1730dd.pth", + "detectron/resnet50_gn": "https://download.openmmlab.com/pretrain/third_party/resnet50_gn-9186a21c.pth", + "detectron/resnet101_gn": "https://download.openmmlab.com/pretrain/third_party/resnet101_gn-cac0ab98.pth", + "jhu/resnet50_gn_ws": "https://download.openmmlab.com/pretrain/third_party/resnet50_gn_ws-15beedd8.pth", + "jhu/resnet101_gn_ws": "https://download.openmmlab.com/pretrain/third_party/resnet101_gn_ws-3e3c308c.pth", + "jhu/resnext50_32x4d_gn_ws": "https://download.openmmlab.com/pretrain/third_party/resnext50_32x4d_gn_ws-0d87ac85.pth", + "jhu/resnext101_32x4d_gn_ws": "https://download.openmmlab.com/pretrain/third_party/resnext101_32x4d_gn_ws-34ac1a9e.pth", + "jhu/resnext50_32x4d_gn": "https://download.openmmlab.com/pretrain/third_party/resnext50_32x4d_gn-c7e8b754.pth", + "jhu/resnext101_32x4d_gn": "https://download.openmmlab.com/pretrain/third_party/resnext101_32x4d_gn-ac3bb84e.pth", + "msra/hrnetv2_w18_small": "https://download.openmmlab.com/pretrain/third_party/hrnetv2_w18_small-b5a04e21.pth", + "msra/hrnetv2_w18": "https://download.openmmlab.com/pretrain/third_party/hrnetv2_w18-00eb2006.pth", + "msra/hrnetv2_w32": "https://download.openmmlab.com/pretrain/third_party/hrnetv2_w32-dc9eeb4f.pth", + "msra/hrnetv2_w40": "https://download.openmmlab.com/pretrain/third_party/hrnetv2_w40-ed0b031c.pth", + "msra/hrnetv2_w48": "https://download.openmmlab.com/pretrain/third_party/hrnetv2_w48-d2186c55.pth", + "bninception_caffe": "https://download.openmmlab.com/pretrain/third_party/bn_inception_caffe-ed2e8665.pth", + "kin400/i3d_r50_f32s2_k400": "https://download.openmmlab.com/pretrain/third_party/i3d_r50_f32s2_k400-2c57e077.pth", + "kin400/nl3d_r50_f32s2_k400": "https://download.openmmlab.com/pretrain/third_party/nl3d_r50_f32s2_k400-fa7e7caa.pth", + "res2net101_v1d_26w_4s": "https://download.openmmlab.com/pretrain/third_party/res2net101_v1d_26w_4s_mmdetv2-f0a600f9.pth", + "regnetx_400mf": "https://download.openmmlab.com/pretrain/third_party/regnetx_400mf-a5b10d96.pth", + "regnetx_800mf": "https://download.openmmlab.com/pretrain/third_party/regnetx_800mf-1f4be4c7.pth", + "regnetx_1.6gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_1.6gf-5791c176.pth", + "regnetx_3.2gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_3.2gf-c2599b0f.pth", + "regnetx_4.0gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_4.0gf-a88f671e.pth", + "regnetx_6.4gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_6.4gf-006af45d.pth", + "regnetx_8.0gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_8.0gf-3c68abe7.pth", + "regnetx_12gf": "https://download.openmmlab.com/pretrain/third_party/regnetx_12gf-4c2a3350.pth", + "resnet50_v1c": "https://download.openmmlab.com/pretrain/third_party/resnet50_v1c-2cccc1ad.pth", + "resnet101_v1c": "https://download.openmmlab.com/pretrain/third_party/resnet101_v1c-e67eebb6.pth", + "mmedit/vgg16": "https://download.openmmlab.com/mmediting/third_party/vgg_state_dict.pth", + "mmedit/res34_en_nomixup": "https://download.openmmlab.com/mmediting/third_party/model_best_resnet34_En_nomixup.pth", + "mmedit/mobilenet_v2": "https://download.openmmlab.com/mmediting/third_party/mobilenet_v2.pth", + "resnest50": "https://download.openmmlab.com/pretrain/third_party/resnest50_d2-7497a55b.pth", + "resnest101": "https://download.openmmlab.com/pretrain/third_party/resnest101_d2-f3b931b2.pth", + "resnest200": "https://download.openmmlab.com/pretrain/third_party/resnest200_d2-ca88e41f.pth", + "darknet53": "https://download.openmmlab.com/pretrain/third_party/darknet53-a628ea1b.pth" } From 34127b9f145932a63905902e8fcd3b645f2d61b4 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Sun, 27 Sep 2020 00:40:39 +0800 Subject: [PATCH 73/81] [enhance]: show grad norm in fp16 optimizer hook (#584) --- mmcv/runner/hooks/optimizer.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/mmcv/runner/hooks/optimizer.py b/mmcv/runner/hooks/optimizer.py index 425ebb55b2..2b1e6a1cad 100644 --- a/mmcv/runner/hooks/optimizer.py +++ b/mmcv/runner/hooks/optimizer.py @@ -113,7 +113,11 @@ def after_train_iter(self, runner): if param.grad is not None: param.grad.div_(self.loss_scale) if self.grad_clip is not None: - self.clip_grads(fp32_weights) + grad_norm = self.clip_grads(fp32_weights) + if grad_norm is not None: + # Add grad norm to the logger + runner.log_buffer.update({'grad_norm': float(grad_norm)}, + runner.outputs['num_samples']) # update fp32 params runner.optimizer.step() # copy fp32 params to the fp16 model From acee61d7c5d7bfcabacdc44478d855bfe98fde5c Mon Sep 17 00:00:00 2001 From: GT9505 Date: Sun, 27 Sep 2020 17:51:00 +0800 Subject: [PATCH 74/81] register deconv in CONV_LAYERS (#582) * register deconv in CONV_LAYERS * use ConvTranspose2d implemented in MMCV * remove repetitive register_module * update * add unittest for deconv --- mmcv/cnn/bricks/wrappers.py | 2 ++ tests/test_cnn/test_build_layers.py | 9 +++++++++ 2 files changed, 11 insertions(+) diff --git a/mmcv/cnn/bricks/wrappers.py b/mmcv/cnn/bricks/wrappers.py index 4d72af813c..e525b00c6f 100644 --- a/mmcv/cnn/bricks/wrappers.py +++ b/mmcv/cnn/bricks/wrappers.py @@ -47,6 +47,8 @@ def forward(self, x): return super().forward(x) +@CONV_LAYERS.register_module() +@CONV_LAYERS.register_module('deconv') @UPSAMPLE_LAYERS.register_module('deconv', force=True) class ConvTranspose2d(nn.ConvTranspose2d): diff --git a/tests/test_cnn/test_build_layers.py b/tests/test_cnn/test_build_layers.py index e180a60d8c..dfd820672b 100644 --- a/tests/test_cnn/test_build_layers.py +++ b/tests/test_cnn/test_build_layers.py @@ -49,6 +49,15 @@ def test_build_conv_layer(): assert layer.groups == kwargs['groups'] assert layer.dilation == (kwargs['dilation'], kwargs['dilation']) + cfg = dict(type='deconv') + layer = build_conv_layer(cfg, **kwargs) + assert isinstance(layer, nn.ConvTranspose2d) + assert layer.in_channels == kwargs['in_channels'] + assert layer.out_channels == kwargs['out_channels'] + assert layer.kernel_size == (kwargs['kernel_size'], kwargs['kernel_size']) + assert layer.groups == kwargs['groups'] + assert layer.dilation == (kwargs['dilation'], kwargs['dilation']) + for type_name, module in CONV_LAYERS.module_dict.items(): cfg = dict(type=type_name) layer = build_conv_layer(cfg, **kwargs) From c80e4cae5485ffa72d1978f4cdb1dec3c7feee44 Mon Sep 17 00:00:00 2001 From: wdmwhh <38210459+wdmwhh@users.noreply.github.com> Date: Mon, 28 Sep 2020 21:48:56 +0800 Subject: [PATCH 75/81] Fixed fp16_optimizer state bug (#580) --- mmcv/runner/hooks/optimizer.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/mmcv/runner/hooks/optimizer.py b/mmcv/runner/hooks/optimizer.py index 2b1e6a1cad..376a001d08 100644 --- a/mmcv/runner/hooks/optimizer.py +++ b/mmcv/runner/hooks/optimizer.py @@ -1,5 +1,7 @@ # Copyright (c) Open-MMLab. All rights reserved. import copy +from collections import defaultdict +from itertools import chain from torch.nn.utils import clip_grad @@ -67,8 +69,16 @@ def before_run(self, runner): 2. Convert the main model from fp32 to fp16. """ # keep a copy of fp32 weights + old_groups = runner.optimizer.param_groups runner.optimizer.param_groups = copy.deepcopy( runner.optimizer.param_groups) + state = defaultdict(dict) + p_map = {old_p: p for old_p, p in + zip(chain(*(g['params'] for g in old_groups)), + chain(*(g['params'] for g in runner.optimizer.param_groups)))} + for k, v in runner.optimizer.state.items(): + state[p_map[k]] = v + runner.optimizer.state = state # convert model to fp16 wrap_fp16_model(runner.model) From f6d5b0f8cb32e866722f0e0bb999edfb20b8a7f5 Mon Sep 17 00:00:00 2001 From: Cao Yuhang Date: Mon, 28 Sep 2020 21:52:27 +0800 Subject: [PATCH 76/81] fix lint #580 (#590) --- mmcv/runner/hooks/optimizer.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/mmcv/runner/hooks/optimizer.py b/mmcv/runner/hooks/optimizer.py index 376a001d08..aca1fd9afb 100644 --- a/mmcv/runner/hooks/optimizer.py +++ b/mmcv/runner/hooks/optimizer.py @@ -73,9 +73,12 @@ def before_run(self, runner): runner.optimizer.param_groups = copy.deepcopy( runner.optimizer.param_groups) state = defaultdict(dict) - p_map = {old_p: p for old_p, p in - zip(chain(*(g['params'] for g in old_groups)), - chain(*(g['params'] for g in runner.optimizer.param_groups)))} + p_map = { + old_p: p + for old_p, p in zip( + chain(*(g['params'] for g in old_groups)), + chain(*(g['params'] for g in runner.optimizer.param_groups))) + } for k, v in runner.optimizer.state.items(): state[p_map[k]] = v runner.optimizer.state = state From 9141d91ddcd1f2f7418712e821c68eb5e8b6cdac Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Tue, 29 Sep 2020 00:09:49 +0800 Subject: [PATCH 77/81] bump version to 1.1.4 (#591) --- mmcv/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/version.py b/mmcv/version.py index 64ec9260f6..d1518fd195 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,6 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.1.3' +__version__ = '1.1.4' def parse_version_info(version_str): From f3a2be99b982b533cb0f916278f7da742c5899ef Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Tue, 29 Sep 2020 10:44:44 +0800 Subject: [PATCH 78/81] lint markdown files (#592) --- .github/workflows/build.yml | 14 +++++--------- .pre-commit-config.yaml | 21 +++++++++++++-------- CONTRIBUTING.md | 9 ++++++--- README.md | 1 - docs/image.md | 8 ++++++++ docs/io.md | 3 +++ docs/utils.md | 11 +++++------ docs/video.md | 1 - mmcv/cnn/bricks/conv2d_adaptive_padding.py | 10 +++++----- 9 files changed, 45 insertions(+), 33 deletions(-) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index e9c0f23489..ef98072310 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -14,16 +14,12 @@ jobs: uses: actions/setup-python@v2 with: python-version: 3.7 - - name: Install linting dependencies + - name: Install pre-commit hook run: | - python -m pip install --upgrade pip - pip install flake8 yapf isort==4.3.21 - - name: Lint with flake8 - run: flake8 --max-complexity 20 . - - name: Lint with isort - run: isort --recursive --check-only --diff mmcv/ tests/ examples/ - - name: Format python codes with yapf - run: yapf -r -d mmcv/ tests/ examples/ + pip install pre-commit + pre-commit install + - name: Linting + run: pre-commit run --all-files - name: Format c/cuda codes with clang-format uses: DoozyX/clang-format-lint-action@v0.6 with: diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 49b03aefb3..056c046592 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -29,16 +29,21 @@ repos: args: ["--remove"] - id: mixed-line-ending args: ["--fix=lf"] + - repo: https://github.com/jumanjihouse/pre-commit-hooks + rev: 2.1.4 + hooks: + - id: markdownlint + args: ["-r", "~MD002,~MD013,~MD029,~MD033,~MD034"] - repo: https://github.com/myint/docformatter rev: v1.3.1 hooks: - id: docformatter args: ["--in-place", "--wrap-descriptions", "79"] - - repo: local - hooks: - - id: clang-format - name: clang-format - description: Format files with ClangFormat - entry: clang-format -style=google -i - language: system - files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|cuh|proto)$ + # - repo: local + # hooks: + # - id: clang-format + # name: clang-format + # description: Format files with ClangFormat + # entry: clang-format -style=google -i + # language: system + # files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|cuh|proto)$ diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index eea39bfe80..32f773d33f 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -17,9 +17,11 @@ Note: If you plan to add some new features that involve large changes, it is enc ## Code style ### Python + We adopt [PEP8](https://www.python.org/dev/peps/pep-0008/) as the preferred code style. We use the following tools for linting and formatting: + - [flake8](http://flake8.pycqa.org/en/latest/): linter - [yapf](https://github.com/google/yapf): formatter - [isort](https://github.com/timothycrosley/isort): sort imports @@ -32,19 +34,20 @@ The config for a pre-commit hook is stored in [.pre-commit-config](./.pre-commit After you clone the repository, you will need to install initialize pre-commit hook. -``` +```shell pip install -U pre-commit ``` From the repository folder -``` + +```shell pre-commit install ``` After this on every commit check code linters and formatter will be enforced. - >Before you create a PR, make sure that your code lints and is formatted by yapf. ### C++ and CUDA + We follow the [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html). diff --git a/README.md b/README.md index ff0bb85cc8..bb747a3f0c 100644 --- a/README.md +++ b/README.md @@ -148,7 +148,6 @@ Note: If you would like to use `opencv-python-headless` instead of `opencv-pytho e.g., in a minimum container environment or servers without GUI, you can first install it before installing MMCV to skip the installation of `opencv-python`. - ### TroubleShooting If you meet issues when running or compiling mmcv, we list some common issues in [TROUBLESHOOTING.md](docs/trouble_shooting.md). diff --git a/docs/image.md b/docs/image.md index adedf50eae..c6e9bbef45 100644 --- a/docs/image.md +++ b/docs/image.md @@ -3,6 +3,7 @@ This module provides some image processing methods, which requires `opencv` to be installed. ### Read/Write/Show + To read or write images files, use `imread` or `imwrite`. ```python @@ -34,7 +35,9 @@ for i in range(10): ``` ### Color space conversion + Supported conversion methods: + - bgr2gray - gray2bgr - bgr2rgb @@ -50,6 +53,7 @@ img3 = mmcv.bgr2hsv(img) ``` ### Resize + There are three resize methods. All `imresize_*` methods have an argument `return_scale`, if this argument is `False`, then the return value is merely the resized image, otherwise is a tuple `(resized_img, scale)`. @@ -70,6 +74,7 @@ mmcv.imrescale(img, (1000, 800)) ``` ### Rotate + To rotate an image by some angle, use `imrotate`. The center can be specified, which is the center of original image by default. There are two modes of rotating, one is to keep the image size unchanged so that some parts of the image will be @@ -96,6 +101,7 @@ img_ = mmcv.imrotate(img, 30, auto_bound=True) ``` ### Flip + To flip an image, use `imflip`. ```python @@ -109,6 +115,7 @@ mmcv.imflip(img, direction='vertical') ``` ### Crop + `imcrop` can crop the image with one or some regions, represented as (x1, y1, x2, y2). ```python @@ -130,6 +137,7 @@ patches = mmcv.imcrop(img, bboxes, scale_ratio=1.2) ``` ### Padding + There are two methods `impad` and `impad_to_multiple` to pad an image to the specific size with given values. diff --git a/docs/io.md b/docs/io.md index 9bcc31865a..3142e6e729 100644 --- a/docs/io.md +++ b/docs/io.md @@ -3,6 +3,7 @@ This module provides two universal API to load and dump files of different formats. ### Load and dump data + `mmcv` provides a universal api for loading and dumping data, currently supported formats are json, yaml and pickle. @@ -82,6 +83,7 @@ class PickleHandler(mmcv.BaseFileHandler): ### Load a text file as a list or dict For example `a.txt` is a text file with 5 lines. + ``` a b @@ -104,6 +106,7 @@ Then use `list_from_file` to load the list from a.txt. ``` For example `b.txt` is a text file with 5 lines. + ``` 1 cat 2 dog cow diff --git a/docs/utils.md b/docs/utils.md index 9e29539d14..bcc71bfdff 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -38,7 +38,7 @@ Currently, it supports four predefined variables: `{{ fileExtname }}` - the current opened file's extension, e.g. .ext -These variable names are referred from https://code.visualstudio.com/docs/editor/variables-reference. +These variable names are referred from [VS Code](https://code.visualstudio.com/docs/editor/variables-reference). Here is one examples of config with predefined variables. @@ -58,7 +58,6 @@ c = '{{ fileExtname }}' ... c='.py') ``` - For all format configs, inheritance is supported. To reuse fields in other config files, specify `_base_='./config_a.py'` or a list of configs `_base_=['./config_a.py', './config_b.py']`. Here are 4 examples of config inheritance. @@ -70,7 +69,7 @@ a = 1 b = dict(b1=[0, 1, 2], b2=None) ``` -#### Inherit from base config without overlaped keys. +#### Inherit from base config without overlaped keys `config_b.py` @@ -91,7 +90,7 @@ d = 'string' New fields in `config_b.py` are combined with old fields in `config_a.py` -#### Inherit from base config with overlaped keys. +#### Inherit from base config with overlaped keys `config_c.py` @@ -111,7 +110,7 @@ c = (1, 2) `b.b2=None` in `config_a` is replaced with `b.b2=1` in `config_c.py`. -#### Inherit from base config with ignored fields. +#### Inherit from base config with ignored fields `config_d.py` @@ -131,7 +130,7 @@ c = (1, 2) You may also set `_delete_=True` to ignore some fields in base configs. All old keys `b1, b2, b3` in `b` are replaced with new keys `b2, b3`. -#### Inherit from multiple base configs (the base configs should not contain the same keys). +#### Inherit from multiple base configs (the base configs should not contain the same keys) `config_e.py` diff --git a/docs/video.md b/docs/video.md index 93d66d702e..a01f377164 100644 --- a/docs/video.md +++ b/docs/video.md @@ -6,7 +6,6 @@ This module provides the following functionalities. - Some methods for editing (cut, concat, resize) videos. - Optical flow read/write/warp. - ### VideoReader The `VideoReader` class provides sequence like apis to access video frames. diff --git a/mmcv/cnn/bricks/conv2d_adaptive_padding.py b/mmcv/cnn/bricks/conv2d_adaptive_padding.py index 1143d25f3e..6b636b0345 100644 --- a/mmcv/cnn/bricks/conv2d_adaptive_padding.py +++ b/mmcv/cnn/bricks/conv2d_adaptive_padding.py @@ -8,11 +8,11 @@ @CONV_LAYERS.register_module() class Conv2dAdaptivePadding(nn.Conv2d): - """ Implementation of 2D convolution in tensorflow with `padding` as - "same", which applies padding to input (if needed) so that input image - gets fully covered by filter and stride you specified. For stride 1, this - will ensure that output image size is same as input. For stride of 2, - output dimensions will be half, for example. + """Implementation of 2D convolution in tensorflow with `padding` as "same", + which applies padding to input (if needed) so that input image gets fully + covered by filter and stride you specified. For stride 1, this will ensure + that output image size is same as input. For stride of 2, output dimensions + will be half, for example. Args: in_channels (int): Number of channels in the input image From fe83261b94ab37e2786b2f787f3ae3b2f5dcdaec Mon Sep 17 00:00:00 2001 From: Cao Yuhang Date: Fri, 2 Oct 2020 00:03:55 +0800 Subject: [PATCH 79/81] revert dcn (#597) --- mmcv/ops/csrc/pytorch/deform_conv_cuda.cu | 3 --- 1 file changed, 3 deletions(-) diff --git a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu index ee96b36241..2d17f59fd2 100644 --- a/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu +++ b/mmcv/ops/csrc/pytorch/deform_conv_cuda.cu @@ -278,8 +278,6 @@ void DeformConvForwardCUDAKernelLauncher(Tensor input, Tensor weight, } columns = columns.view({columns.size(0) * columns.size(1), columns.size(2)}); - weight = weight.view({weight.size(0) * weight.size(1), weight.size(2), - weight.size(3), weight.size(4)}); } output_buffer = output_buffer.view( @@ -377,7 +375,6 @@ void DeformConvBackwardInputCUDAKernelLauncher( gradOutput = gradOutput.view( {gradOutput.size(0), gradOutput.size(1) * gradOutput.size(2), gradOutput.size(3), gradOutput.size(4), gradOutput.size(5)}); - weight = weight.view({nOutputPlane, nInputPlane, kH, kW}); deformable_col2im_coord(columns, input[elt], offset[elt], nInputPlane, inputHeight, inputWidth, kH, kW, padH, padW, dH, dW, From 005c408748446bab1615873c46ae65a3a7124a29 Mon Sep 17 00:00:00 2001 From: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com> Date: Tue, 6 Oct 2020 12:44:56 +0800 Subject: [PATCH 80/81] Fix wrappers version comparison (#602) * add version check in wrappers * fix assersion * use digital version for version comparison * fix unit tests * reformat * fall back to compare the first two version * fix unittest * fix unittest * fix unit test * clean unnecessary change --- mmcv/cnn/bricks/wrappers.py | 13 +++++++++---- tests/test_cnn/test_wrappers.py | 4 ++-- 2 files changed, 11 insertions(+), 6 deletions(-) diff --git a/mmcv/cnn/bricks/wrappers.py b/mmcv/cnn/bricks/wrappers.py index e525b00c6f..6f9b694d55 100644 --- a/mmcv/cnn/bricks/wrappers.py +++ b/mmcv/cnn/bricks/wrappers.py @@ -12,6 +12,10 @@ from .registry import CONV_LAYERS, UPSAMPLE_LAYERS +# torch.__version__ could be 1.3.1+cu92, we only need the first two +# for comparison +TORCH_VERSION = tuple(int(x) for x in torch.__version__.split('.')[:2]) + class NewEmptyTensorOp(torch.autograd.Function): @@ -30,7 +34,7 @@ def backward(ctx, grad): class Conv2d(nn.Conv2d): def forward(self, x): - if x.numel() == 0 and torch.__version__ <= '1.4.0': + if x.numel() == 0 and TORCH_VERSION <= (1, 4): out_shape = [x.shape[0], self.out_channels] for i, k, p, s, d in zip(x.shape[-2:], self.kernel_size, self.padding, self.stride, self.dilation): @@ -53,7 +57,7 @@ def forward(self, x): class ConvTranspose2d(nn.ConvTranspose2d): def forward(self, x): - if x.numel() == 0 and torch.__version__ <= '1.4.0': + if x.numel() == 0 and TORCH_VERSION <= (1, 4): out_shape = [x.shape[0], self.out_channels] for i, k, p, s, d, op in zip(x.shape[-2:], self.kernel_size, self.padding, self.stride, @@ -74,7 +78,7 @@ class MaxPool2d(nn.MaxPool2d): def forward(self, x): # PyTorch 1.6 does not support empty tensor inference yet - if x.numel() == 0 and torch.__version__ <= '1.6.0': + if x.numel() == 0 and TORCH_VERSION <= (1, 6): out_shape = list(x.shape[:2]) for i, k, p, s, d in zip(x.shape[-2:], _pair(self.kernel_size), _pair(self.padding), _pair(self.stride), @@ -91,7 +95,8 @@ def forward(self, x): class Linear(torch.nn.Linear): def forward(self, x): - if x.numel() == 0: + # empty tensor forward of Linear layer is supported in Pytorch 1.6 + if x.numel() == 0 and TORCH_VERSION <= (1, 5): out_shape = [x.shape[0], self.out_features] empty = NewEmptyTensorOp.apply(x, out_shape) if self.training: diff --git a/tests/test_cnn/test_wrappers.py b/tests/test_cnn/test_wrappers.py index 067cb6465b..755970c6ad 100644 --- a/tests/test_cnn/test_wrappers.py +++ b/tests/test_cnn/test_wrappers.py @@ -169,7 +169,7 @@ def test_linear(): wrapper(x_empty) -@patch('torch.__version__', '1.6.1') +@patch('mmcv.cnn.bricks.wrappers.TORCH_VERSION', (1, 7)) def test_nn_op_forward_called(): for m in ['Conv2d', 'ConvTranspose2d', 'MaxPool2d']: @@ -191,7 +191,7 @@ def test_nn_op_forward_called(): x_empty = torch.randn(0, 3) wrapper = Linear(3, 3) wrapper(x_empty) - nn_module_forward.assert_not_called() + nn_module_forward.assert_called_with(x_empty) # non-randn input x_normal = torch.randn(1, 3) From 665fee244180ed20a694cdce64f652ace4f77006 Mon Sep 17 00:00:00 2001 From: Kai Chen Date: Wed, 7 Oct 2020 23:09:52 +0800 Subject: [PATCH 81/81] bump version to 1.1.5 (#603) --- mmcv/version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mmcv/version.py b/mmcv/version.py index d1518fd195..cb03ca7a32 100644 --- a/mmcv/version.py +++ b/mmcv/version.py @@ -1,6 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.1.4' +__version__ = '1.1.5' def parse_version_info(version_str):