add ones_like op (#17388)

paddle/fluid/API.spec

@@ -300,6 +300,7 @@ paddle.fluid.layers.isfinite (ArgSpec(args=['x'], varargs=None, keywords=None, d
 paddle.fluid.layers.range (ArgSpec(args=['start', 'end', 'step', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', 'a45b42f21bc5a4e84b60981a3d629ab3'))
 paddle.fluid.layers.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '3663d1148946eed4c1c34c81be586b9e'))
 paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd88a23bcdc443719b3953593f7cef14a'))
+paddle.fluid.layers.ones_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', '642afd126553337d6796600e886a6525'))
 paddle.fluid.layers.diag (ArgSpec(args=['diagonal'], varargs=None, keywords=None, defaults=None), ('document', '88a15e15f0098d549f07a01eaebf9ce3'))
 paddle.fluid.layers.While ('paddle.fluid.layers.control_flow.While', ('document', '50110155608a00f43d3d3fd1be41dcb4'))
 paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))

paddle/fluid/operators/fill_any_like_op.cc

@@ -0,0 +1,64 @@
+/* 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. */
+
+#include "paddle/fluid/operators/fill_any_like_op.h"
+
+namespace paddle {
+namespace operators {
+
+class FillAnyLikeOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("X"),
+                   "Input(X) of FillAnyLikeOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of FillAnyLikeOp should not be null.");
+    ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
+    ctx->ShareLoD("X", /*->*/ "Out");
+  }
+};
+
+class FillAnyLikeOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput("X", "The input of fill-zeros-like op.");
+    AddOutput("Out", "The variable will be filled up with specified value.");
+    AddAttr<float>("value", "The filled value").SetDefault(0.0);
+    AddComment(R"DOC(
+FillAnyLike Operator.
+
+Fill up a variable with Attr(value).
+The output will have the same shape and dtype as the input.
+
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(fill_any_like, ops::FillAnyLikeOp,
+                             ops::FillAnyLikeOpMaker);
+
+REGISTER_OP_CPU_KERNEL(
+    fill_any_like,
+    ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, int64_t>,
+    ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext,
+                           paddle::platform::float16>,
+    ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, bool>);

paddle/fluid/operators/fill_any_like_op.cu

@@ -0,0 +1,27 @@
+/* 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. */
+
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/fill_any_like_op.h"
+#include "paddle/fluid/platform/float16.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_CUDA_KERNEL(
+    fill_any_like,
+    ops::FillAnyLikeKernel<paddle::platform::CUDADeviceContext, int32_t>,
+    ops::FillAnyLikeKernel<paddle::platform::CUDADeviceContext, int64_t>,
+    ops::FillAnyLikeKernel<paddle::platform::CUDADeviceContext, float>,
+    ops::FillAnyLikeKernel<paddle::platform::CUDADeviceContext,
+                           paddle::platform::float16>,
+    ops::FillAnyLikeKernel<paddle::platform::CUDADeviceContext, bool>);

paddle/fluid/operators/fill_any_like_op.h

@@ -0,0 +1,60 @@
+/* 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 <cmath>
+#include <limits>
+#include <type_traits>
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/math/math_function.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class FillAnyLikeKernel : public framework::OpKernel<T> {
+ public:
+  using CommonType = typename std::common_type<
+      float,
+      typename std::conditional<std::is_same<T, platform::float16>::value,
+                                float, T>::type>::type;
+
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* out = context.Output<framework::Tensor>("Out");
+    out->mutable_data<T>(context.GetPlace());
+
+    // TODO(fangzeyang): Once context.Attribute supports double dtype, this
+    // kernel should be updated to support double dtype, too.
+    float value = context.Attr<float>("value");
+
+    auto common_type_value = static_cast<CommonType>(value);
+
+    PADDLE_ENFORCE(
+        (common_type_value >=
+         static_cast<CommonType>(std::numeric_limits<T>::lowest())) &&
+            (common_type_value <=
+             static_cast<CommonType>(std::numeric_limits<T>::max())),
+        "filled value is out of range for targeted type in fill_any_like "
+        "kernel");
+
+    PADDLE_ENFORCE(!std::isnan(value), "filled value is NaN");
+
+    math::SetConstant<DeviceContext, T> setter;
+    setter(context.template device_context<DeviceContext>(), out,
+           static_cast<T>(value));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/layers/tensor.py

@@ -28,7 +28,7 @@ __all__ = [
     'tensor_array_to_tensor', 'concat', 'sums', 'assign',
     'fill_constant_batch_size_like', 'fill_constant', 'argmin', 'argmax',
     'argsort', 'ones', 'zeros', 'reverse', 'has_inf', 'has_nan', 'isfinite',
-    'range', 'linspace', 'zeros_like', 'diag'
+    'range', 'linspace', 'zeros_like', 'ones_like', 'diag'
 ]
 
 
@@ -989,3 +989,38 @@ def diag(diagonal):
 
     out.stop_gradient = True
     return out
+
+
+def ones_like(x, out=None):
+    """
+    **ones_like**
+
+    This function creates a ones tensor which has identical shape and dtype 
+    with `x`.
+
+    Args:
+        x(Variable): The input tensor which specifies shape and dtype.
+        out(Variable): The output tensor.
+
+    Returns:
+        x(Variable): The tensor variable storing the output.
+
+    Examples:
+        .. code-block:: python
+
+          import paddle.fluid as fluid
+
+          x = fluid.layers.data(name='x', dtype='float32', shape=[3], append_batch_size=False)
+          data = fluid.layers.ones_like(x) # [1.0, 1.0, 1.0]
+
+    """
+
+    helper = LayerHelper("ones_like", **locals())
+    if out is None:
+        out = helper.create_variable_for_type_inference(dtype=x.dtype)
+    helper.append_op(
+        type='fill_any_like',
+        inputs={'X': [x]},
+        attrs={'value': 1.0},
+        outputs={'Out': [out]})
+    return out

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

@@ -0,0 +1,81 @@
+#   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.
+
+from __future__ import print_function
+
+import paddle.fluid.core as core
+import paddle.compat as cpt
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestFillAnyLikeOp(OpTest):
+    def setUp(self):
+        self.op_type = "fill_any_like"
+        self.dtype = np.int32
+        self.value = 0.0
+        self.init()
+        self.inputs = {'X': np.random.random((219, 232)).astype(self.dtype)}
+        self.attrs = {'value': self.value}
+        self.outputs = {'Out': self.value * np.ones_like(self.inputs["X"])}
+
+    def init(self):
+        pass
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestFillAnyLikeOpFloat32(TestFillAnyLikeOp):
+    def init(self):
+        self.dtype = np.float32
+        self.value = 0.0
+
+
+class TestFillAnyLikeOpValue1(TestFillAnyLikeOp):
+    def init(self):
+        self.value = 1.0
+
+
+class TestFillAnyLikeOpValue2(TestFillAnyLikeOp):
+    def init(self):
+        self.value = 1e-10
+
+
+class TestFillAnyLikeOpValue3(TestFillAnyLikeOp):
+    def init(self):
+        self.value = 1e-100
+
+
+class TestFillAnyLikeOpOverflow(TestFillAnyLikeOp):
+    def init(self):
+        self.value = 1e100
+
+    def test_check_output(self):
+        exception = None
+        try:
+            self.check_output()
+        except core.EnforceNotMet as ex:
+            exception = ex
+        self.assertIsNotNone(exception)
+
+
+class TestFillAnyLikeOpFloat16(TestFillAnyLikeOp):
+    def init(self):
+        self.dtype = np.float16
+
+
+if __name__ == "__main__":
+    unittest.main()