Merge pull request #16320 from zhoukunsheng/all_any

add reduce_all, reduce_any op

paddle/fluid/API.spec

@@ -118,6 +118,8 @@ paddle.fluid.layers.reduce_mean (ArgSpec(args=['input', 'dim', 'keep_dim', 'name
 paddle.fluid.layers.reduce_max (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '66a622db727551761ce4eb73eaa7f6a4'))
 paddle.fluid.layers.reduce_min (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'd50ac552b5d131468ed466d08bb2d38c'))
 paddle.fluid.layers.reduce_prod (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'fcd8301a0ce15f219c7a4bcd0c1e8eca'))
+paddle.fluid.layers.reduce_all (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '646ca4d4a2cc16084f59de44b6927eca'))
+paddle.fluid.layers.reduce_any (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'f36661060aeeaf6c6b1331e41b3726fa'))
 paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '2b290d3d77882bfe9bb8d331cac8cdd3'))
 paddle.fluid.layers.sequence_last_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'c16a892f44f7fe71bfa5afc32d3f34ce'))
 paddle.fluid.layers.sequence_slice (ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fdcea0e8b5bc7d8d4b1b072c521014e6'))

paddle/fluid/operators/reduce_ops/reduce_all_op.cc

@@ -0,0 +1,20 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+
+#include "paddle/fluid/operators/reduce_ops/reduce_all_op.h"
+
+REGISTER_REDUCE_OP(reduce_all);
+REGISTER_OP_CPU_KERNEL(reduce_all,
+                       ops::ReduceKernel<paddle::platform::CPUDeviceContext,
+                                         bool, ops::AllFunctor>);

paddle/fluid/operators/reduce_ops/reduce_all_op.cu

@@ -0,0 +1,19 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+
+#include "paddle/fluid/operators/reduce_ops/reduce_all_op.h"
+
+REGISTER_OP_CUDA_KERNEL(reduce_all,
+                        ops::ReduceKernel<paddle::platform::CUDADeviceContext,
+                                          bool, ops::AllFunctor>);

paddle/fluid/operators/reduce_ops/reduce_all_op.h

@@ -0,0 +1,29 @@
+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+#pragma once
+
+#include "paddle/fluid/operators/reduce_ops/reduce_op.h"
+
+namespace paddle {
+namespace operators {
+
+struct AllFunctor {
+  template <typename DeviceContext, typename X, typename Y, typename Dim>
+  void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) {
+    y->device(place) = x->all(dim);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/reduce_ops/reduce_any_op.cc

@@ -0,0 +1,20 @@
+// Copyright (c) 2018 PaddlePaddle Authors. Any Rights Reserved.
+//
+// Licensed 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.
+
+#include "paddle/fluid/operators/reduce_ops/reduce_any_op.h"
+
+REGISTER_REDUCE_OP(reduce_any);
+REGISTER_OP_CPU_KERNEL(reduce_any,
+                       ops::ReduceKernel<paddle::platform::CPUDeviceContext,
+                                         bool, ops::AnyFunctor>);

paddle/fluid/operators/reduce_ops/reduce_any_op.cu

@@ -0,0 +1,19 @@
+// Copyright (c) 2018 PaddlePaddle Authors. Any Rights Reserved.
+//
+// Licensed 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.
+
+#include "paddle/fluid/operators/reduce_ops/reduce_any_op.h"
+
+REGISTER_OP_CUDA_KERNEL(reduce_any,
+                        ops::ReduceKernel<paddle::platform::CUDADeviceContext,
+                                          bool, ops::AnyFunctor>);

paddle/fluid/operators/reduce_ops/reduce_any_op.h

@@ -0,0 +1,29 @@
+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+#pragma once
+
+#include "paddle/fluid/operators/reduce_ops/reduce_op.h"
+
+namespace paddle {
+namespace operators {
+
+struct AnyFunctor {
+  template <typename DeviceContext, typename X, typename Y, typename Dim>
+  void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) {
+    y->device(place) = x->any(dim);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/layers/nn.py

@@ -73,6 +73,8 @@ __all__ = [
     'reduce_max',
     'reduce_min',
     'reduce_prod',
+    'reduce_all',
+    'reduce_any',
     'sequence_first_step',
     'sequence_last_step',
     'sequence_slice',
@@ -4738,6 +4740,106 @@ def reduce_prod(input, dim=None, keep_dim=False, name=None):
     return out
 
 
+def reduce_all(input, dim=None, keep_dim=False, name=None):
+    """
+    Computes the ``logical and`` of tensor elements over the given dimension.
+
+    Args:
+        input (Variable): The input variable which is a Tensor or LoDTensor.
+        dim (list|int|None): The dimension along which the logical and is computed.
+            If :attr:`None`, compute the logical and over all elements of
+            :attr:`input` and return a Tensor variable with a single element,
+            otherwise must be in the range :math:`[-rank(input), rank(input))`.
+            If :math:`dim[i] < 0`, the dimension to reduce is :math:`rank + dim[i]`.
+        keep_dim (bool): Whether to reserve the reduced dimension in the
+            output Tensor. The result tensor will have one fewer dimension
+            than the :attr:`input` unless :attr:`keep_dim` is true.
+        name(str|None): A name for this layer(optional). If set None, the layer
+                       will be named automatically.
+
+    Returns:
+        Variable: The reduced Tensor variable.
+
+    Examples:
+        .. code-block:: python
+        
+            # x is a bool Tensor variable with following elements:
+            #    [[True, False]
+            #     [True, True]]
+            # Each example is followed by the correspending output tensor.
+            fluid.layers.reduce_all(x)  # False 
+            fluid.layers.reduce_all(x, dim=0)  # [True, False]
+            fluid.layers.reduce_all(x, dim=-1)  # [False, True]
+            fluid.layers.reduce_all(x, dim=1,
+                                     keep_dim=True)  # [[False], [True]]
+
+    """
+    helper = LayerHelper('reduce_all', **locals())
+    out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
+    if dim is not None and not isinstance(dim, list):
+        dim = [dim]
+    helper.append_op(
+        type='reduce_all',
+        inputs={'X': input},
+        outputs={'Out': out},
+        attrs={
+            'dim': dim if dim != None else [0],
+            'keep_dim': keep_dim,
+            'reduce_all': True if dim == None else False
+        })
+    return out
+
+
+def reduce_any(input, dim=None, keep_dim=False, name=None):
+    """
+    Computes the ``logical or`` of tensor elements over the given dimension.
+
+    Args:
+        input (Variable): The input variable which is a Tensor or LoDTensor.
+        dim (list|int|None): The dimension along which the logical or is computed.
+            If :attr:`None`, compute the logical or over all elements of
+            :attr:`input` and return a Tensor variable with a single element,
+            otherwise must be in the range :math:`[-rank(input), rank(input))`.
+            If :math:`dim[i] < 0`, the dimension to reduce is :math:`rank + dim[i]`.
+        keep_dim (bool): Whether to reserve the reduced dimension in the
+            output Tensor. The result tensor will have one fewer dimension
+            than the :attr:`input` unless :attr:`keep_dim` is true.
+        name(str|None): A name for this layer(optional). If set None, the layer
+                       will be named automatically.
+
+    Returns:
+        Variable: The reduced Tensor variable.
+
+    Examples:
+        .. code-block:: python
+
+            # x is a bool Tensor variable with following elements:
+            #    [[True, False]
+            #     [False, False]]
+            # Each example is followed by the correspending output tensor.
+            fluid.layers.reduce_any(x)  # True
+            fluid.layers.reduce_any(x, dim=0)  # [True, False]
+            fluid.layers.reduce_any(x, dim=-1)  # [True, False]
+            fluid.layers.reduce_any(x, dim=1,
+                                     keep_dim=True)  # [[True], [False]]
+
+    """
+    helper = LayerHelper('reduce_any', **locals())
+    out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
+    if dim is not None and not isinstance(dim, list):
+        dim = [dim]
+    helper.append_op(
+        type='reduce_any',
+        inputs={'X': input},
+        outputs={'Out': out},
+        attrs={
+            'dim': dim if dim != None else [0],
+            'keep_dim': keep_dim,
+            'reduce_all': True if dim == None else False
+        })
+    return out
+
+
 def split(input, num_or_sections, dim=-1, name=None):
     """
     Split the input tensor into multiple sub-tensors.

python/paddle/fluid/tests/unittests/test_reduce_op.py

@@ -91,6 +91,78 @@ class TestProdOp(OpTest):
         self.check_grad(['X'], 'Out')
 
 
+class TestAllOp(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_all"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.outputs = {'Out': self.inputs['X'].all()}
+        self.attrs = {'reduce_all': True}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestAllOpWithDim(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_all"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.attrs = {'dim': [1]}
+        self.outputs = {'Out': self.inputs['X'].all(axis=1)}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestAllOpWithKeepDim(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_all"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.attrs = {'dim': [1], 'keep_dim': True}
+        self.outputs = {
+            'Out': np.expand_dims(
+                self.inputs['X'].all(axis=1), axis=1)
+        }
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestAnyOp(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_any"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.outputs = {'Out': self.inputs['X'].any()}
+        self.attrs = {'reduce_all': True}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestAnyOpWithDim(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_any"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.attrs = {'dim': [1]}
+        self.outputs = {'Out': self.inputs['X'].any(axis=1)}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestAnyOpWithKeepDim(OpTest):
+    def setUp(self):
+        self.op_type = "reduce_any"
+        self.inputs = {'X': np.random.randint(0, 2, (5, 6, 10)).astype("bool")}
+        self.attrs = {'dim': [1], 'keep_dim': True}
+        self.outputs = {
+            'Out': np.expand_dims(
+                self.inputs['X'].any(axis=1), axis=1)
+        }
+
+    def test_check_output(self):
+        self.check_output()
+
+
 class Test1DReduce(OpTest):
     def setUp(self):
         self.op_type = "reduce_sum"