Add the argsort operator

paddle/fluid/operators/argsort_op.cc

+/* Copyright (c) 2016 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/argsort_op.h"
+
+namespace paddle {
+namespace operators {
+
+class ArgsortOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("X"),
+                   "Input(X) of ArgsortOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of ArgsortOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Indices"),
+                   "Output(Indices) of ArgsortOp should not be null.");
+
+    auto in_dims = ctx->GetInputDim("X");
+    int axis = static_cast<int>(ctx->Attrs().Get<int>("axis"));
+
+    auto num_dims = in_dims.size();
+    PADDLE_ENFORCE(axis < num_dims,
+                   "Attr(axis) %d of ArgsortOp is out of bounds for Input(X) "
+                   "dimension %d.",
+                   axis, num_dims);
+    PADDLE_ENFORCE(axis >= 0 || axis == -1,
+                   "Attr(axis) %d of ArgsortOp must be nonnegative or equal to "
+                   "-1.",
+                   axis);
+
+    ctx->SetOutputDim("Out", in_dims);
+    ctx->SetOutputDim("Indices", in_dims);
+    ctx->ShareLoD("X", "Out");
+    ctx->ShareLoD("X", "Indices");
+  }
+};
+
+class ArgsortOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput("X", "(Tensor) The input of Argsort op.");
+    AddOutput("Out", "(Tensor) The sorted tensor of Argsort op.");
+    AddOutput("Indices",
+              "(Tensor) The indices of a tensor giving the sorted order.");
+    AddComment(R"DOC(
+Argsort operator
+
+Performs sorting on the input tensor along the given axis and outputs two 
+tensors, Output(Out) and Output(Indices). They reserve the same shape 
+with Input(X), and Output(Out) represents the sorted tensor while 
+Output(Indices) gives the sorted order along the given axis Attr(axis).
+
+ )DOC");
+    AddAttr<int>("axis",
+                 "(int, default -1) The axis along which to sort the tensor, "
+                 "default -1, the last dimension.")
+        .SetDefault(-1);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OPERATOR(argsort, ops::ArgsortOp, ops::ArgsortOpMaker,
+                  paddle::framework::EmptyGradOpMaker);
+REGISTER_OP_CPU_KERNEL(argsort,
+                       ops::ArgsortKernel<paddle::platform::CPUPlace, float>,
+                       ops::ArgsortKernel<paddle::platform::CPUPlace, double>);

paddle/fluid/operators/argsort_op.h

+/* Copyright (c) 2016 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 <algorithm>
+#include <iostream>
+#include <utility>
+#include <vector>
+#include "paddle/fluid/framework/eigen.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
+
+template <typename DeviceContext, typename T>
+class ArgsortKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* input = ctx.Input<Tensor>("X");
+    auto* output = ctx.Output<Tensor>("Out");
+    auto* indices = ctx.Output<Tensor>("Indices");
+    int axis = static_cast<int>(ctx.Attr<int>("axis"));
+
+    auto in_dims = input->dims();
+    axis = (axis == -1) ? (in_dims.size() - 1) : axis;
+
+    const T* in_data = input->data<T>();
+    T* out_data = output->mutable_data<T>(ctx.GetPlace());
+    int64_t* idx_data = indices->mutable_data<int64_t>(ctx.GetPlace());
+
+    int64_t part_dims_prod = input->numel() / in_dims[axis];
+    for (int64_t i = 0; i < part_dims_prod; ++i) {
+      int64_t idx = i;
+      std::vector<int64_t> idx_vec(in_dims.size(), 0);
+      for (int64_t dim = in_dims.size() - 1; dim >= 0; --dim) {
+        if (dim != axis) {
+          idx_vec[dim] = idx % in_dims[dim];
+          idx /= in_dims[dim];
+        }
+      }
+      std::vector<std::pair<T, int64_t>> in_vec;
+      std::vector<int64_t> org_index_vec(in_dims[axis], 0);
+      for (int64_t j = 0; j < in_dims[axis]; ++j) {
+        idx_vec[axis] = j;
+        int64_t index = idx_vec[0];
+        for (int64_t dim = 0; dim < in_dims.size() - 1; ++dim) {
+          index = index * in_dims[dim + 1] + idx_vec[dim + 1];
+        }
+        in_vec.push_back(std::pair<T, int64_t>(in_data[index], j));
+        org_index_vec[j] = index;
+      }
+
+      std::sort(
+          in_vec.begin(), in_vec.end(),
+          [](const std::pair<T, int64_t>& v1, const std::pair<T, int64_t>& v2) {
+            return v1.first < v2.first;
+          });
+
+      for (size_t j = 0; j < org_index_vec.size(); ++j) {
+        int64_t index = org_index_vec[j];
+        out_data[index] = in_vec[j].first;
+        idx_data[index] = in_vec[j].second;
+      }
+    }
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/tests/unittests/test_argsort_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.
+
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestArgsortOp(OpTest):
+    def setUp(self):
+        self.init_axis()
+        x = np.random.random((2, 3, 4, 5)).astype("float32")
+        self.indices = np.argsort(x, kind='quicksort', axis=self.axis)
+        self.out = np.sort(x, kind='quicksort', axis=self.axis)
+        self.op_type = "argsort"
+        self.inputs = {'X': x}
+        self.attrs = {'axis': self.axis}
+        self.outputs = {'Indices': self.indices, 'Out': self.out}
+
+    def init_axis(self):
+        self.axis = -1
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestArgsortOpAxis0(TestArgsortOp):
+    def init_axis(self):
+        self.axis = 0
+
+
+class TestArgsortOpAxis1(TestArgsortOp):
+    def init_axis(self):
+        self.axis = 1
+
+
+if __name__ == "__main__":
+    unittest.main()