Add label smooth operator

paddle/operators/label_smooth_op.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/operators/label_smooth_op.h"
+
+namespace paddle {
+namespace operators {
+
+class LabelSmoothOp : public framework::OperatorWithKernel {
+ public:
+  LabelSmoothOp(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(ctx->HasInput("X"),
+                   "Input(X) of LabelSmoothOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of LabelSmoothOp should not be null.");
+    auto in_dims = ctx->GetInputDim("X");
+    ctx->ShareLoD("X", /*->*/ "Out");
+    ctx->SetOutputDim("Out", in_dims);
+  }
+};
+
+class LabelSmoothOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  LabelSmoothOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("X", "The input label of LabelSmooth operator.");
+    AddOutput("Out", "The smoothed label of LabelSmooth operator.");
+    AddAttr<float>("epsilon",
+                   "(float, default 0.0f)"
+                   "The smoothing parameter of LabelSmooth operator.")
+        .SetDefault(0.0f);
+    AddComment(R"DOC(
+LabelSmooth Operator.
+
+)DOC");
+  }
+};
+
+class LabelSmoothGradOp : public framework::OperatorWithKernel {
+ public:
+  LabelSmoothGradOp(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(ctx->HasInput("X"), "Input(X) shouldn't be null.");
+    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
+                   "Input(Out@GRAD) shouldn't be null.");
+    ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+namespace ops = paddle::operators;
+
+REGISTER_OP(label_smooth, ops::LabelSmoothOp, ops::LabelSmoothOpMaker,
+            label_smooth_grad, ops::LabelSmoothGradOp);
+REGISTER_OP_CPU_KERNEL(
+    label_smooth,
+    ops::LabelSmoothKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::LabelSmoothKernel<paddle::platform::CPUDeviceContext, double>);
+REGISTER_OP_CPU_KERNEL(
+    label_smooth_grad,
+    ops::LabelSmoothGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::LabelSmoothGradKernel<paddle::platform::CPUDeviceContext, double>);

paddle/operators/label_smooth_op.cu

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/operators/label_smooth_op.h"
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_CUDA_KERNEL(
+    label_smooth,
+    ops::LabelSmoothKernel<paddle::platform::CUDADeviceContext, float>,
+    ops::LabelSmoothKernel<paddle::platform::CUDADeviceContext, double>);
+REGISTER_OP_CUDA_KERNEL(
+    label_smooth_grad,
+    ops::LabelSmoothGradKernel<paddle::platform::CUDADeviceContext, float>,
+    ops::LabelSmoothGradKernel<paddle::platform::CUDADeviceContext, double>);

paddle/operators/label_smooth_op.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/framework/eigen.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class LabelSmoothKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const {
+    auto* out_t = ctx.Output<framework::LoDTensor>("Out");
+    auto* in_t = ctx.Input<framework::LoDTensor>("X");
+    auto label_dim = in_t->dims()[1];
+    out_t->mutable_data<T>(ctx.GetPlace());
+
+    auto epsilon = ctx.Attr<float>("epsilon");
+    auto out = framework::EigenVector<T>::Flatten(*out_t);
+    auto in = framework::EigenVector<T>::Flatten(*in_t);
+    auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
+    out.device(dev) =
+        static_cast<T>(1 - epsilon) * in + static_cast<T>(epsilon / label_dim);
+  }
+};
+
+template <typename DeviceContext, typename T>
+class LabelSmoothGradKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const {
+    auto* d_out_t = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
+    auto* d_in_t = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
+    d_in_t->mutable_data<T>(ctx.GetPlace());
+
+    auto d_out = framework::EigenVector<T>::Flatten(*d_out_t);
+    auto d_in = framework::EigenVector<T>::Flatten(*d_in_t);
+
+    auto epsilon = ctx.Attr<float>("epsilon");
+    auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
+    d_in.device(dev) = static_cast<T>(1 - epsilon) * d_out;
+  }
+};
+}  // namespace operators
+}  // namespace paddle

python/paddle/v2/fluid/tests/test_label_smooth_op.py

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
+#
+# 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.
+
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestLabelSmoothOp(OpTest):
+    def setUp(self):
+        self.op_type = "label_smooth"
+        epsilon = 0.1
+        batch_size, label_dim = 5, 10
+        label = np.zeros((batch_size, label_dim)).astype("float64")
+        nonzero_index = np.random.randint(label_dim, size=(batch_size))
+        label[np.arange(batch_size), nonzero_index] = 1
+        smoothed_label = (1 - epsilon) * label + epsilon / label_dim
+        self.inputs = {'X': label}
+        self.attrs = {'epsilon': epsilon}
+        self.outputs = {'Out': smoothed_label}
+
+    def test_check_output(self):
+        self.check_output()
+
+    def test_check_grad(self):
+        self.check_grad(["X"], "Out")
+
+
+if __name__ == '__main__':
+    unittest.main()