[Relay][Op] Adaptive pooling

docs/api/python/topi.rst

@@ -57,6 +57,7 @@ List of operators
    topi.nn.dilate
    topi.nn.pool
    topi.nn.global_pool
+   topi.nn.adaptive_pool
    topi.nn.upsampling
    topi.nn.softmax
    topi.nn.dense

docs/langref/relay_op.rst

@@ -189,6 +189,8 @@ This level support backpropagation of broadcast operators. It is temporary.
    tvm.relay.annotation.on_device
    tvm.relay.reverse_reshape
    tvm.relay.nn.batch_matmul
+   tvm.relay.contrib.adaptive_max_pool2d
+   tvm.relay.contrib.adaptive_avg_pool2d
 
 
 Level 1 Definitions
@@ -318,3 +320,5 @@ Level 10 Definitions
 .. autofunction:: tvm.relay.annotation.on_device
 .. autofunction:: tvm.relay.reverse_reshape
 .. autofunction:: tvm.relay.nn.batch_matmul
+.. autofunction:: tvm.relay.contrib.adaptive_max_pool2d
+.. autofunction:: tvm.relay.contrib.adaptive_avg_pool2d

include/tvm/relay/attrs/nn.h

@@ -332,6 +332,22 @@ struct GlobalPool2DAttrs : public tvm::AttrsNode<GlobalPool2DAttrs> {
   }
 };
 
+/*! \brief Attributes for adaptive pool operator */
+struct AdaptivePool2DAttrs : public tvm::AttrsNode<AdaptivePool2DAttrs> {
+  Array<IndexExpr> output_size;
+  std::string layout;
+
+  TVM_DECLARE_ATTRS(AdaptivePool2DAttrs, "relay.attrs.AdaptivePool2DAttrs") {
+    TVM_ATTR_FIELD(output_size).set_default(Array<IndexExpr>({}))
+      .describe("Output height and width.");
+    TVM_ATTR_FIELD(layout).set_default("NCHW")
+      .describe("Dimension ordering of data and weight. Can be 'NCHW', 'NHWC', etc."
+                  "'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
+                  "dimensions respectively. Convolution is applied on the 'H' and"
+                  "'W' dimensions.");
+  }
+};
+
 
 /*! \brief Attributes for dense operator */
 struct DenseAttrs : public tvm::AttrsNode<DenseAttrs> {

nnvm/python/nnvm/top/nn.py

@@ -399,7 +399,7 @@ def schedule_avg_pool2d(attrs, outs, target):
 def schedule_global_max_pool2d(_, outs, target):
     """Schedule definition of global_max_pool2d"""
     with tvm.target.create(target):
-        return topi.generic.schedule_global_pool(outs)
+        return topi.generic.schedule_adaptive_pool(outs)
 
 reg.register_pattern("global_max_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)
 
@@ -409,7 +409,7 @@ def schedule_global_max_pool2d(_, outs, target):
 def schedule_global_avg_pool2d(_, outs, target):
     """Schedule definition of global_avg_pool2d"""
     with tvm.target.create(target):
-        return topi.generic.schedule_global_pool(outs)
+        return topi.generic.schedule_adaptive_pool(outs)
 
 reg.register_pattern("global_avg_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)
 

python/tvm/relay/__init__.py

@@ -40,6 +40,7 @@
 from . import nn
 from . import annotation
 from . import vision
+from . import contrib
 from . import image
 from . import frontend
 from . import backend

python/tvm/relay/contrib.py

@@ -0,0 +1,20 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=wildcard-import, unused-import, unused-wildcard-import
+"""Contrib operators."""
+# Re-export in a specific file name so that autodoc can pick it up
+from .op.contrib import *

python/tvm/relay/frontend/mxnet.py

@@ -190,10 +190,7 @@ def _pool2d(new_op, is_avg):
 
 def _mx_adaptive_avg_pooling(inputs, attrs):
     output_size = attrs.get_int_tuple("output_size", [])
-    if output_size != (1,):
-        raise tvm.error.OpAttributeUnimplemented(
-            "AdaptiveAvgPooling with output_size other than 1 is not supported yet.")
-    return _op.nn.global_avg_pool2d(inputs[0])
+    return _op.contrib.adaptive_avg_pool2d(inputs[0], output_size)
 
 
 def _mx_dropout(inputs, attrs):

python/tvm/relay/op/__init__.py

@@ -29,6 +29,7 @@
 from . import annotation
 from . import image
 from . import vision
+from . import contrib
 from . import op_attrs
 
 

python/tvm/relay/op/contrib/__init__.py

@@ -0,0 +1,21 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=wildcard-import
+"""Neural network related operators."""
+from __future__ import absolute_import as _abs
+from .contrib import *
+from . import _contrib

python/tvm/relay/op/contrib/_contrib.py

@@ -0,0 +1,43 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=invalid-name, unused-argument
+"""Backend compiler related feature registration"""
+from __future__ import absolute_import
+
+import topi
+from .. import op as reg
+from ..op import OpPattern
+
+
+# adaptive_max_pool2d
+@reg.register_schedule("contrib.adaptive_max_pool2d")
+def schedule_adaptive_max_pool2d(_, outs, target):
+    """Schedule definition of adaptive_max_pool2d"""
+    with target:
+        return topi.generic.schedule_adaptive_pool(outs)
+
+reg.register_pattern("contrib.adaptive_max_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)
+
+
+# adaptive_avg_pool2d
+@reg.register_schedule("contrib.adaptive_avg_pool2d")
+def schedule_adaptive_avg_pool2d(_, outs, target):
+    """Schedule definition of adaptive_avg_pool2d"""
+    with target:
+        return topi.generic.schedule_adaptive_pool(outs)
+
+reg.register_pattern("contrib.adaptive_avg_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)

python/tvm/relay/op/contrib/_make.py

@@ -0,0 +1,20 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""Constructor APIs"""
+from ...._ffi.function import _init_api
+
+_init_api("relay.op.contrib._make", __name__)

python/tvm/relay/op/contrib/contrib.py

@@ -0,0 +1,113 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#pylint: disable=invalid-name, too-many-lines
+"""Contrib operations."""
+from __future__ import absolute_import as _abs
+from . import _make
+
+
+def adaptive_max_pool2d(data,
+                        output_size=None,
+                        layout="NCHW"):
+    r"""2D adaptive max pooling operator. This operator is experimental.
+
+    This operator takes data as input and does 2D max value calculation
+    across each window represented by WxH.
+
+
+    In the default case, where the data_layout is `NCHW`
+    a data Tensor with shape `(batch_size, in_channels, height, width)`,
+    to produce an output Tensor with shape
+    (batch_size, in_channels, output_height, output_width).
+
+    The pooling kernel and stride sizes are automatically chosen for
+    desired output sizes.
+
+    For output_size:
+        If this argument is not provided, input height and width will be used
+        as output height and width.
+
+        If a single integer is provided for output_size, the output size is
+        (N x C x output_size x output_size) for any input (NCHW).
+
+        If a tuple of integers (height, width) are provided for output_size,
+        the output size is (N x C x height x width) for any input (NCHW).
+
+    Parameters
+    ----------
+    data : tvm.relay.Expr
+        The input data to the operator.
+
+    output_size : tuple of int. optional
+        Output height and width.
+
+    layout : str, optional
+        Layout of the input.
+
+    Returns
+    -------
+    result : tvm.relay.Expr
+        The computed result.
+    """
+    output_size = [] or output_size
+    return _make.adaptive_max_pool2d(data, output_size, layout)
+
+def adaptive_avg_pool2d(data,
+                        output_size=None,
+                        layout="NCHW"):
+    r"""2D adaptive average pooling operator. This operator is experimental.
+
+    This operator takes data as input and does 2D average value calculation
+    across each window represented by WxH.
+
+
+    In the default case, where the data_layout is `NCHW`
+    a data Tensor with shape `(batch_size, in_channels, height, width)`,
+    to produce an output Tensor with shape
+    (batch_size, in_channels, output_height, output_width).
+
+    The pooling kernel and stride sizes are automatically chosen for
+    desired output sizes.
+
+    For output_size:
+        If this argument is not provided, input height and width will be used
+        as output height and width.
+
+        If a single integer is provided for output_size, the output size is
+        (N x C x output_size x output_size) for any input (NCHW).
+
+        If a tuple of integers (height, width) are provided for output_size,
+        the output size is (N x C x height x width) for any input (NCHW).
+
+    Parameters
+    ----------
+    data : tvm.relay.Expr
+        The input data to the operator.
+
+    output_size : tuple of int. optional
+        Output height and width.
+
+    layout : str, optional
+        Layout of the input.
+
+    Returns
+    -------
+    result : tvm.relay.Expr
+        The computed result.
+    """
+    output_size = [] or output_size
+    return _make.adaptive_avg_pool2d(data, output_size, layout)

python/tvm/relay/op/nn/_nn.py

@@ -247,7 +247,7 @@ def schedule_avg_pool2d(attrs, outs, target):
 def schedule_global_max_pool2d(_, outs, target):
     """Schedule definition of global_max_pool2d"""
     with target:
-        return topi.generic.schedule_global_pool(outs)
+        return topi.generic.schedule_adaptive_pool(outs)
 
 
 reg.register_pattern("nn.global_max_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)
@@ -258,11 +258,12 @@ def schedule_global_max_pool2d(_, outs, target):
 def schedule_global_avg_pool2d(_, outs, target):
     """Schedule definition of global_avg_pool2d"""
     with target:
-        return topi.generic.schedule_global_pool(outs)
+        return topi.generic.schedule_adaptive_pool(outs)
 
 
 reg.register_pattern("nn.global_avg_pool2d", OpPattern.OUT_ELEMWISE_FUSABLE)
 
+
 # leaky_relu
 reg.register_schedule("nn.leaky_relu", schedule_broadcast)
 reg.register_pattern("nn.leaky_relu", OpPattern.ELEMWISE)