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conv2d support bfloat16 #32221

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merged 16 commits into from
Jun 2, 2021
Merged

conv2d support bfloat16 #32221

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687e28b
conv2d support bfloat16, test=develop
Avin0323 Apr 13, 2021
252dbcf
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
Avin0323 Apr 22, 2021
747d096
limit bfloat16 type supported with cudnn version, test=develop
Avin0323 Apr 22, 2021
8bab3d7
fix compilation error, test=develop
Avin0323 Apr 22, 2021
74bb02d
add conv2d unittest with bfloat16 data type, test=develop
Avin0323 Apr 22, 2021
cd612c5
fix conv2d unittest with bfloat16 data type, test=develop
Avin0323 Apr 25, 2021
4069f78
modify according to the review comments, test=develop
Avin0323 May 18, 2021
7d3a4d5
Merge branch 'develop' into conv2d-support-bf16
Avin0323 May 18, 2021
c41fe74
fix compilation error, test=develop
Avin0323 May 18, 2021
f3ca4b8
revert code, test=develop
Avin0323 May 19, 2021
5a3e730
fix conv2d unittests error with bfloat16, test=develop
Avin0323 May 20, 2021
f23f1d2
fix test_fusion_lstm_bf16_mkldnn_op error, test=develop
Avin0323 May 20, 2021
15f3315
check cudnn version in runtime, test=develop
Avin0323 May 25, 2021
394d8d4
fix check cudnn version error, test=develop
Avin0323 May 25, 2021
12cc70b
Merge branch 'develop' into conv2d-support-bf16
Avin0323 May 26, 2021
62fcd51
Merge branch 'develop' into conv2d-support-bf16
Avin0323 Jun 1, 2021
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42 changes: 30 additions & 12 deletions paddle/fluid/operators/conv_cudnn_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -51,6 +51,13 @@ template <typename T>
class CUDNNConvOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
#if CUDNN_VERSION_MIN(8, 1, 0)
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这个检查能不能放到一个公共的地方，比如CudnnDataType<bfloat16>里面？

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CudnnDataType<bfloat16>里只能做编译期检查，这里直接改为cudnn8.1以下不添加bfloat16数据类型的Kernel。

PADDLE_ENFORCE_EQ(
std::is_same_v<T, platform::bfloat16>, true,
platform::errors::Unavailable(
"conv2d supports bfloat16 data type , but it only works when "
"the version of cudnn is larger than 8.1.0"));
#endif
auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx.GetPlace()), true,
Expand Down Expand Up @@ -362,6 +369,13 @@ template <typename T>
class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
#if CUDNN_VERSION_MIN(8, 1, 0)
PADDLE_ENFORCE_EQ(
std::is_same_v<T, platform::bfloat16>, true,
platform::errors::Unavailable(
"conv2d supports bfloat16 data type , but it only works when "
"the version of cudnn is larger than 8.1.0"));
#endif
auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx.GetPlace()), true,
Expand Down Expand Up @@ -812,6 +826,13 @@ template <typename T>
class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
#if CUDNN_VERSION_MIN(8, 1, 0)
PADDLE_ENFORCE_EQ(
std::is_same_v<T, platform::bfloat16>, true,
platform::errors::Unavailable(
"conv2d supports bfloat16 data type , but it only works when "
"the version of cudnn is larger than 8.1.0"));
#endif
auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx.GetPlace()), true,
Expand Down Expand Up @@ -1363,14 +1384,7 @@ REGISTER_OP_KERNEL(
conv2d_grad_grad, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvDoubleGradOpKernel<float>,
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::float16>);
// ROCM has limit thread in depthwise_conv.cu and willl result in accuracy issue
// Use depthwise_conv2d in MIOPEN to resolve this issue
REGISTER_OP_KERNEL(depthwise_conv2d, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvOpKernel<float>,
paddle::operators::CUDNNConvOpKernel<plat::float16>);
REGISTER_OP_KERNEL(depthwise_conv2d_grad, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvGradOpKernel<float>,
paddle::operators::CUDNNConvGradOpKernel<plat::float16>);

REGISTER_OP_CUDA_KERNEL(
depthwise_conv2d_grad_grad,
paddle::operators::CUDNNConvDoubleGradOpKernel<float>,
Expand All @@ -1389,22 +1403,26 @@ REGISTER_OP_KERNEL(
REGISTER_OP_KERNEL(conv2d, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvOpKernel<float>,
paddle::operators::CUDNNConvOpKernel<double>,
paddle::operators::CUDNNConvOpKernel<plat::float16>);
paddle::operators::CUDNNConvOpKernel<plat::float16>,
paddle::operators::CUDNNConvOpKernel<plat::bfloat16>);
REGISTER_OP_KERNEL(conv2d_grad, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvGradOpKernel<float>,
paddle::operators::CUDNNConvGradOpKernel<double>,
paddle::operators::CUDNNConvGradOpKernel<plat::float16>);
paddle::operators::CUDNNConvGradOpKernel<plat::float16>,
paddle::operators::CUDNNConvGradOpKernel<plat::bfloat16>);
REGISTER_OP_KERNEL(
conv2d_grad_grad, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvDoubleGradOpKernel<float>,
paddle::operators::CUDNNConvDoubleGradOpKernel<double>,
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::float16>);
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::float16>,
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::bfloat16>);

REGISTER_OP_CUDA_KERNEL(
depthwise_conv2d_grad_grad,
paddle::operators::CUDNNConvDoubleGradOpKernel<float>,
paddle::operators::CUDNNConvDoubleGradOpKernel<double>,
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::float16>);
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::float16>,
paddle::operators::CUDNNConvDoubleGradOpKernel<plat::bfloat16>);

REGISTER_OP_KERNEL(conv3d, CUDNN, plat::CUDAPlace,
paddle::operators::CUDNNConvOpKernel<float>,
Expand Down
5 changes: 5 additions & 0 deletions paddle/fluid/platform/cudnn_desc.h
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,11 @@ inline cudnnDataType_t ToCudnnDataType(
case framework::proto::VarType::FP64:
type = CUDNN_DATA_DOUBLE;
break;
#if CUDNN_VERSION_MIN(8, 1, 0)
case framework::proto::VarType::BF16:
type = CUDNN_DATA_BFLOAT16;
break;
#endif
default:
break;
}
Expand Down
21 changes: 21 additions & 0 deletions paddle/fluid/platform/cudnn_helper.h
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Expand Up @@ -131,6 +131,27 @@ inline ActivationMode StringToActivationMode(const std::string& str) {
template <typename T>
class CudnnDataType;

template <>
class CudnnDataType<bfloat16> {
public:
// CUDNN_DATA_BFLOAT16 is not valid before cudnn8.1
#if CUDNN_VERSION_MIN(8, 1, 0)
static const cudnnDataType_t type = CUDNN_DATA_BFLOAT16;
#else
static const cudnnDataType_t type = CUDNN_DATA_HALF;
#endif
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@AshburnLee AshburnLee Apr 23, 2021 •
edited
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#else分支不需要吧。当cudnn版本 < 8.1时，整个class应该不被编译。所以是不是在class整体头尾分别加上#if和#endif。

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因为conv2d对于bfloat16需要编译成功，代码逻辑中CudnnDataType<bfloat16>部分会被实例化，如果将整个模板特化使用预处理会出现编译失败问题。

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cudnn8.1版本以下也不该用half类型，应该直接挂掉。另外，你加的都是#ifdef做编译时判断，运行时判断也要加一下？可以参考（但也不完整，需要加下cudnn version的判断）：

Paddle/paddle/fluid/operators/conv_op.cc

Lines 187 to 191 in 79f7ba6

if (input_data_type == framework::proto::VarType::FP16) {
PADDLE_ENFORCE_EQ(library, framework::LibraryType::kCUDNN,
platform::errors::InvalidArgument(
"float16 can only be used when CUDNN is used"));
}

using ScalingParamType = const float;
using BatchNormParamType = float;
static ScalingParamType* kOne() {
static ScalingParamType v = 1.0;
return &v;
}
static ScalingParamType* kZero() {
static ScalingParamType v = 0.0;
return &v;
}
};

template <>
class CudnnDataType<float16> {
public:
Expand Down
40 changes: 40 additions & 0 deletions python/paddle/fluid/tests/unittests/test_conv2d_op.py
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Expand Up @@ -167,6 +167,37 @@ def test_check_grad_no_input(self):
globals()[cls_name] = TestConv2DCUDNNFp16


def create_test_cudnn_bf16_class(parent, grad_check=True):
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conv的测试不需要依赖OpTest单测框架的增强？

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需要的，目前已merge最新代码，同步OpTest单测框架改动。

@unittest.skipIf(
not core.is_compiled_with_cuda() or core.cudnn_version() < 8100,
"core is not compiled with CUDA and cudnn version need larger than 8.1.0"
)
class TestConv2DCUDNNBF16(parent):
def init_kernel_type(self):
self.use_cudnn = True
self.dtype = np.uint16

def test_check_output(self):
place = core.CUDAPlace(0)
self.check_output_with_place(place, atol=1e-2)

def test_check_grad_no_filter(self):
place = core.CUDAPlace(0)
if grad_check:
self.check_grad_with_place(
place, ['Input'], 'Output', no_grad_set=set(['Filter']))

def test_check_grad_no_input(self):
place = core.CUDAPlace(0)
if grad_check:
self.check_grad_with_place(
place, ['Filter'], 'Output', no_grad_set=set(['Input']))

cls_name = "{0}_{1}".format(parent.__name__, "CUDNNBF16")
TestConv2DCUDNNBF16.__name__ = cls_name
globals()[cls_name] = TestConv2DCUDNNBF16


def create_test_channel_last_class(parent):
class TestChannelLastCase(parent):
def init_data_format(self):
Expand Down Expand Up @@ -554,6 +585,15 @@ def init_group(self):
create_test_cudnn_fp16_class(TestWith1x1, grad_check=False)
create_test_cudnn_fp16_class(TestWithInput1x1Filter1x1, grad_check=False)

#----------------Conv2DCUDNN bf16----------------

create_test_cudnn_bf16_class(TestConv2DOp, grad_check=False)
create_test_cudnn_bf16_class(TestWithPad, grad_check=False)
create_test_cudnn_bf16_class(TestWithStride, grad_check=False)
create_test_cudnn_bf16_class(TestWithGroup, grad_check=False)
create_test_cudnn_bf16_class(TestWith1x1, grad_check=False)
create_test_cudnn_bf16_class(TestWithInput1x1Filter1x1, grad_check=False)
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都不检查梯度？

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之前试参考cpu上bf16测试，重新commit代码已默认添加反向测试。


#----------------TestDepthwiseConv -----


Expand Down