add erf op (#21785)

* add erf op and python interface.

* add fp16 support for erf op.

* add unitests for erf op and its python interface.

paddle/fluid/operators/erf_op.cc

+/* 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 <memory>
+#include <string>
+#include <unordered_map>
+
+#include "paddle/fluid/operators/erf_op.h"
+#include "paddle/fluid/platform/float16.h"
+
+namespace paddle {
+namespace operators {
+
+class ErfOp : public framework::OperatorWithKernel {
+ public:
+  ErfOp(const std::string &type, const framework::VariableNameMap &inputs,
+        const framework::VariableNameMap &outputs,
+        const framework::AttributeMap &attrs)
+      : OperatorWithKernel(type, inputs, outputs, attrs) {}
+
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE_EQ(ctx->HasInput("X"), true,
+                      platform::errors::InvalidArgument(
+                          "Input(%s) of ErfOp should not be null.", "X"));
+    PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"), true,
+                      platform::errors::InvalidArgument(
+                          "Output(%s) of ErfOp should not be null.", "Out"));
+
+    ctx->ShareDim("X", /*->*/ "Out");
+    ctx->ShareLoD("X", /*->*/ "Out");
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext &ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
+  }
+};
+
+class ErfGradOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE_EQ(
+        ctx->HasInput(framework::GradVarName("Out")), true,
+        platform::errors::InvalidArgument(
+            "Input(%s) of ErfGradOp should not be null.", "DOut"));
+    PADDLE_ENFORCE_EQ(ctx->HasInput("X"), true,
+                      platform::errors::InvalidArgument(
+                          "Input(%s) of ErfGradOp should not be null.", "X"));
+    PADDLE_ENFORCE_EQ(ctx->HasOutput(framework::GradVarName("X")), true,
+                      platform::errors::InvalidArgument(
+                          "Output(%s) of ErfGradOp should not be null.", "DX"));
+    auto x_grad_name = framework::GradVarName("X");
+    ctx->SetOutputDim(x_grad_name, ctx->GetInputDim("X"));
+    ctx->ShareLoD("X", /*->*/ x_grad_name);
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext &ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
+  }
+};
+
+class ErfOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput("X", "The input tensor of erf operator.");
+    AddOutput("Out", "The output tensor of erf operator.");
+    AddComment(R"DOC(
+Erf Operator.
+
+The equation is:
+$$
+f(x) = \frac{2}{\sqrt{\pi}} \int_{0}^{x}e^{- \eta^{2}}d\eta
+$$
+
+The input `X` can carry the LoD (Level of Details) information,
+or not. And the output shares the LoD information with input `X`.
+)DOC");
+  }
+};
+
+template <typename T>
+class ErfGradOpMaker : public framework::SingleGradOpMaker<T> {
+ public:
+  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
+
+  std::unique_ptr<T> Apply() const override {
+    auto *grad_op = new T();
+    grad_op->SetType("erf_grad");
+    grad_op->SetInput("X", this->Input("X"));
+    grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
+    grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
+    grad_op->SetAttrMap(this->Attrs());
+    return std::unique_ptr<T>(grad_op);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(erf, ops::ErfOp, ops::ErfOpMaker,
+                  ops::ErfGradOpMaker<paddle::framework::OpDesc>,
+                  ops::ErfGradOpMaker<paddle::imperative::OpBase>);
+REGISTER_OPERATOR(erf_grad, ops::ErfGradOp);
+REGISTER_OP_CPU_KERNEL(
+    erf, ops::ErfKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ErfKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ErfKernel<paddle::platform::CPUDeviceContext,
+                   paddle::platform::float16>);
+REGISTER_OP_CPU_KERNEL(
+    erf_grad, ops::ErfGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ErfGradKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ErfGradKernel<paddle::platform::CPUDeviceContext,
+                       paddle::platform::float16>);

paddle/fluid/operators/erf_op.cu

+/* 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/erf_op.h"
+#include "paddle/fluid/platform/float16.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_CUDA_KERNEL(
+    erf, ops::ErfKernel<paddle::platform::CUDADeviceContext, float>,
+    ops::ErfKernel<paddle::platform::CUDADeviceContext, double>,
+    ops::ErfKernel<paddle::platform::CUDADeviceContext,
+                   paddle::platform::float16>);
+REGISTER_OP_CUDA_KERNEL(
+    erf_grad, ops::ErfGradKernel<paddle::platform::CUDADeviceContext, float>,
+    ops::ErfGradKernel<paddle::platform::CUDADeviceContext, double>,
+    ops::ErfGradKernel<paddle::platform::CUDADeviceContext,
+                       paddle::platform::float16>);

paddle/fluid/operators/erf_op.h

+/* 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. */
+
+#pragma once
+#ifndef _USE_MATH_DEFINES
+#define _USE_MATH_DEFINES
+#endif
+#include <cmath>
+#include "paddle/fluid/framework/eigen.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class ErfKernel : public framework::OpKernel<T> {
+ public:
+  virtual void Compute(const framework::ExecutionContext& context) const {
+    auto* out = context.Output<framework::Tensor>("Out");
+    auto* in = context.Input<framework::Tensor>("X");
+    out->mutable_data<T>(in->place());
+
+    auto eigen_out = framework::EigenVector<T>::Flatten(*out);
+    auto eigen_in = framework::EigenVector<T>::Flatten(*in);
+    auto& place =
+        *context.template device_context<DeviceContext>().eigen_device();
+    eigen_out.device(place) = eigen_in.erf();
+  }
+};
+
+template <typename DeviceContext, typename T>
+class ErfGradKernel : public framework::OpKernel<T> {
+ public:
+  virtual void Compute(const framework::ExecutionContext& context) const {
+    auto* x = context.Input<framework::Tensor>("X");
+    auto* dout =
+        context.Input<framework::Tensor>(framework::GradVarName("Out"));
+    auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
+
+    dx->mutable_data<T>(dout->place());
+
+    auto eigen_x = framework::EigenVector<T>::Flatten(*x);
+    auto eigen_dout = framework::EigenVector<T>::Flatten(*dout);
+    auto eigen_dx = framework::EigenVector<T>::Flatten(*dx);
+    auto& place =
+        *context.template device_context<DeviceContext>().eigen_device();
+    eigen_dx.device(place) =
+        eigen_dout * static_cast<T>(M_2_SQRTPI) * (-(eigen_x.square())).exp();
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/layers/ops.py

@@ -318,3 +318,82 @@ Examples:
         # array([[ 0.70456535, -0.15380788, -0.13207214],
         #        [ 0.08796856,  0.20387867,  0.2080159 ]], dtype=float32)
 """
+
+__all__ += ['erf']
+
+_erf_ = generate_layer_fn('erf')
+
+
+def erf(x):
+    locals_var = locals().copy()
+    kwargs = dict()
+    for name, val in locals_var.items():
+        if val is not None:
+            kwargs[name] = val
+    return _erf_(**kwargs)
+
+
+erf.__doc__ = """
+:strong:`Erf Operator`
+For more details, see [Error function](https://en.wikipedia.org/wiki/Error_function).
+
+Equation:
+    ..  math::
+        out = \\frac{2}{\\sqrt{\\pi}} \\int_{0}^{x}e^{- \\eta^{2}}d\\eta
+
+Args:
+
+    x(Variable): The input of Erf op, Tensor or LoDTensor, dtype: float32 or float64.
+
+Returns:
+
+    Variable: The output of Erf op, Tensor or LoDTensor, dtype: float32 or float64, the same as the input, shape: the same as the input.
+
+Examples:
+    
+    .. code-block:: python
+    
+        # declarative mode
+        import numpy as np
+        from paddle import fluid
+        
+        x = fluid.data(name="x", shape=(-1, 3), dtype="float32")
+        y = fluid.layers.erf(x)
+        
+        place = fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        start = fluid.default_startup_program()
+        main = fluid.default_main_program()
+        
+        data = np.random.randn(2, 3).astype("float32")
+        exe.run(start)
+        
+        y_np, = exe.run(main, feed={"x": data}, fetch_list=[y])
+        
+        data
+        # array([[ 0.4643714 , -1.1509596 ,  1.2538221 ],
+        #        [ 0.34369683,  0.27478245,  1.1805398 ]], dtype=float32)
+        y_np
+        # array([[ 0.48863927, -0.8964121 ,  0.9237998 ],
+        #        [ 0.37307587,  0.30242872,  0.9049887 ]], dtype=float32)
+
+    .. code-block:: python
+    
+        # imperative mode
+        import numpy as np
+        from paddle import fluid
+        import paddle.fluid.dygraph as dg
+        
+        data = np.random.randn(2, 3).astype("float32")
+        place = fluid.CPUPlace()
+        with dg.guard(place) as g:
+            x = dg.to_variable(data)
+            y = fluid.layers.erf(x)
+            y_np = y.numpy()
+        data
+        # array([[ 0.4643714 , -1.1509596 ,  1.2538221 ],
+        #        [ 0.34369683,  0.27478245,  1.1805398 ]], dtype=float32)
+        y_np
+        # array([[ 0.48863927, -0.8964121 ,  0.9237998 ],
+        #        [ 0.37307587,  0.30242872,  0.9049887 ]], dtype=float32)
+"""

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

+#   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.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+from scipy.special import erf
+from op_test import OpTest
+
+import paddle.fluid as fluid
+import paddle.fluid.dygraph as dg
+
+
+class TestErfOp(OpTest):
+    def setUp(self):
+        self.op_type = "erf"
+        self.dtype = self._init_dtype()
+        self.x_shape = [11, 17]
+        x = np.random.uniform(-1, 1, size=self.x_shape).astype(self.dtype)
+        y_ref = erf(x).astype(self.dtype)
+        self.inputs = {'X': x}
+        self.outputs = {'Out': y_ref}
+
+    def _init_dtype(self):
+        return "float64"
+
+    def test_check_output(self):
+        self.check_output()
+
+    def test_check_grad(self):
+        self.check_grad(['X'], 'Out')
+
+
+class TestErfLayer(unittest.TestCase):
+    def _test_case(self, place):
+        x = np.random.uniform(-1, 1, size=(11, 17)).astype(np.float64)
+        y_ref = erf(x)
+        with dg.guard(place) as g:
+            x_var = dg.to_variable(x)
+            y_var = fluid.layers.erf(x_var)
+            y_test = y_var.numpy()
+        self.assertTrue(np.allclose(y_ref, y_test))
+
+    def test_case(self):
+        self._test_case(fluid.CPUPlace())
+        if fluid.is_compiled_with_cuda():
+            self._test_case(fluid.CUDAPlace(0))
+
+
+if __name__ == '__main__':
+    unittest.main()