Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into shufflechannel

paddle/fluid/framework/ngraph_bridge.cc

@@ -31,10 +31,12 @@ std::map<std::string,
                             std::shared_ptr<std::unordered_map<
                                 std::string, std::shared_ptr<ngraph::Node>>>)>>
     NgraphBridge::NG_NODE_MAP = {
+        {"fill_constant", paddle::operators::ngraphs::BuildFillConstantNode},
         {"mul", paddle::operators::ngraphs::BuildMulNode},
         {"mul_grad", paddle::operators::ngraphs::BuildMulGradNode},
         {"relu", paddle::operators::ngraphs::BuildUnaryNode<ngraph::op::Relu>},
-        {"tanh", paddle::operators::ngraphs::BuildUnaryNode<ngraph::op::Tanh>}};
+        {"tanh", paddle::operators::ngraphs::BuildUnaryNode<ngraph::op::Tanh>},
+        {"top_k", paddle::operators::ngraphs::BuildTopKNode}};
 
 void NgraphBridge::BuildNgNode(const std::shared_ptr<OperatorBase>& op) {
   auto& op_type = op->Type();

paddle/fluid/operators/dequantize_mkldnn_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 "mkldnn.hpp"
+#include "paddle/fluid/framework/data_layout_transform.h"
+#include "paddle/fluid/framework/tensor.h"
+#include "paddle/fluid/operators/dequantize_op.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
+
+namespace paddle {
+namespace operators {
+
+using mkldnn::memory;
+using mkldnn::primitive;
+using mkldnn::reorder;
+using platform::to_void_cast;
+using Tensor = framework::Tensor;
+using framework::DataLayout;
+using mkldnn::stream;
+using platform::GetMKLDNNFormat;
+
+template <typename T>
+class DeQuantOpKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* input = ctx.Input<Tensor>("Input");
+    auto scale_data = ctx.Attr<float>("Scale");
+    auto* output = ctx.Output<Tensor>("Output");
+    auto& dev_ctx =
+        ctx.template device_context<platform::MKLDNNDeviceContext>();
+    const auto& engine = dev_ctx.GetEngine();
+
+    const T* input_data = input->data<T>();
+    float* output_data = output->mutable_data<float>(ctx.GetPlace());
+    std::vector<float> reorder_scale = {1.0f / scale_data};
+
+    std::vector<primitive> pipeline;
+    std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
+    std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
+    mkldnn::memory::data_type src_dt =
+        paddle::framework::ToMKLDNNDataType(input->type());
+    mkldnn::memory::format src_fmt = input->format();
+
+    mkldnn::primitive_attr attri;
+    int mask = 0;
+    attri.set_output_scales(mask, reorder_scale);
+
+    auto src_md = platform::MKLDNNMemDesc({src_tz}, src_dt, src_fmt);
+    auto src_pd = mkldnn::memory::primitive_desc(src_md, engine);
+    auto src_memory =
+        std::make_shared<mkldnn::memory>(src_pd, to_void_cast<T>(input_data));
+    std::shared_ptr<primitive::at> src_memory_p =
+        std::shared_ptr<primitive::at>(new primitive::at(*src_memory));
+
+    auto dst_md = platform::MKLDNNMemDesc({dst_tz}, memory::data_type::f32,
+                                          memory::format::nchw);
+    auto dst_pd = mkldnn::memory::primitive_desc(dst_md, engine);
+    auto dst_memory = mkldnn::memory(dst_pd, to_void_cast<float>(output_data));
+
+    auto reorder_pd = std::shared_ptr<reorder::primitive_desc>(
+        new reorder::primitive_desc(src_pd, dst_pd, attri));
+    auto reorder_p = std::shared_ptr<reorder>(
+        new reorder(*reorder_pd, *src_memory_p, dst_memory));
+    pipeline.push_back(*reorder_p);
+    stream(stream::kind::eager).submit(pipeline).wait();
+
+    output->set_format(GetMKLDNNFormat(dst_memory));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_KERNEL(dequantize, MKLDNN, ::paddle::platform::CPUPlace,
+                   ops::DeQuantOpKernel<uint8_t>, ops::DeQuantOpKernel<int8_t>);

paddle/fluid/operators/dequantize_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/dequantize_op.h"
+#ifdef PADDLE_WITH_MKLDNN
+#include "paddle/fluid/platform/mkldnn_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+framework::OpKernelType DeQuantOp::GetExpectedKernelType(
+    const framework::ExecutionContext& ctx) const {
+  framework::LibraryType library_ = framework::LibraryType::kMKLDNN;
+  framework::DataLayout layout_ = framework::DataLayout::kMKLDNN;
+
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout_, library_);
+}
+
+void DeQuantOpMaker::Make() {
+  AddInput("Input", "input data");
+  AddOutput("Output", "output data");
+  AddAttr<float>("Scale", "scale data").SetDefault({1.0f});
+  AddComment(R"DOC(This op will dequantize data from INT8 to FP32)DOC");
+}
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(dequantize, ops::DeQuantOp, ops::DeQuantOpMaker,
+                  paddle::framework::DefaultGradOpDescMaker<true>);

paddle/fluid/operators/dequantize_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 <string>
+#include <vector>
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using framework::OpKernelType;
+using framework::Tensor;
+
+class DeQuantOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    ctx->SetOutputDim("Output", ctx->GetInputDim("Input"));
+    ctx->ShareLoD("Input", /*->*/ "Output");
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override;
+};
+
+class DeQuantOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override;
+};
+
+class DeQuantGradOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {}
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/ngraph/ngraph_ops.h

@@ -22,4 +22,6 @@ limitations under the License. */
 #pragma once
 
 #include "ops/binary_unnary_op.h"
+#include "ops/fill_constant_op.h"
 #include "ops/mul_op.h"
+#include "ops/top_k_op.h"

paddle/fluid/operators/ngraph/ops/binary_unnary_op.h

@@ -45,7 +45,6 @@ static void BuildUnaryNode(
   auto out = std::make_shared<T>(input);
   paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
 }
-
 }  // namespace ngraphs
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/ngraph/ops/fill_constant_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. */
+
+#ifdef PADDLE_WITH_NGRAPH
+#pragma once
+
+#include <string>
+#include <vector>
+#include "ngraph/ngraph.hpp"
+#include "paddle/fluid/platform/ngraph_helper.h"
+
+namespace paddle {
+namespace operators {
+namespace ngraphs {
+
+void BuildFillConstantNode(
+    const std::shared_ptr<paddle::framework::OperatorBase>& op,
+    std::shared_ptr<
+        std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
+        ngb_node_map) {
+  auto op_attrs = paddle::framework::AttrReader(op->Attrs());
+  auto vsp = op_attrs.Get<std::vector<int64_t>>("shape");
+  ngraph::Shape shape;
+  for (auto& sp : vsp) {
+    shape.push_back(sp);
+  }
+  float value = op_attrs.Get<float>("value");
+  ngraph::element::Type ng_dtype;
+  auto data_type = static_cast<paddle::framework::proto::VarType::Type>(
+      op_attrs.Get<int>("dtype"));
+  if (data_type == paddle::framework::proto::VarType::FP32) {
+    ng_dtype = ngraph::element::f32;
+  } else if (data_type == paddle::framework::proto::VarType::FP64) {
+    ng_dtype = ngraph::element::f64;
+  } else if (data_type == paddle::framework::proto::VarType::INT64) {
+    ng_dtype = ngraph::element::i64;
+  } else if (data_type == paddle::framework::proto::VarType::INT32) {
+    ng_dtype = ngraph::element::i32;
+  } else if (data_type == paddle::framework::proto::VarType::BOOL) {
+    ng_dtype = ngraph::element::boolean;
+  } else {
+    PADDLE_THROW("unsupported data type: %s", data_type);
+  }
+  auto out = ngraph::op::Constant::create(ng_dtype, shape, {value});
+  paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
+}
+}  // namespace ngraphs
+}  // namespace operators
+}  // namespace paddle
+#endif

paddle/fluid/operators/ngraph/ops/top_k_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. */
+
+#ifdef PADDLE_WITH_NGRAPH
+#pragma once
+
+#include <string>
+#include "ngraph/ngraph.hpp"
+#include "paddle/fluid/platform/ngraph_helper.h"
+
+namespace paddle {
+namespace operators {
+namespace ngraphs {
+
+void BuildTopKNode(
+    const std::shared_ptr<paddle::framework::OperatorBase>& op,
+    std::shared_ptr<
+        std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
+        ngb_node_map) {
+  auto op_attrs = paddle::framework::AttrReader(op->Attrs());
+  int k = op_attrs.Get<int>("k");
+  auto input = paddle::platform::GetInputNode(op, "X", ngb_node_map);
+  auto top_k = std::make_shared<ngraph::op::TopK>(
+      input, input->get_shape().size() - 1, ngraph::element::i64, k);
+  std::shared_ptr<ngraph::Node> indices =
+      std::make_shared<ngraph::op::GetOutputElement>(top_k, 0);
+  std::shared_ptr<ngraph::Node> out =
+      std::make_shared<ngraph::op::GetOutputElement>(top_k, 1);
+  auto dummy_out = paddle::platform::GetOutputNode(op, "Out", ngb_node_map);
+  if (dummy_out && dummy_out->get_element_type() != out->get_element_type()) {
+    out = std::make_shared<ngraph::op::Convert>(out,
+                                                dummy_out->get_element_type());
+  }
+  paddle::platform::SetOutputNode(op, "Indices", indices, ngb_node_map);
+  paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
+}
+}  // namespace ngraphs
+}  // namespace operators
+}  // namespace paddle
+#endif

paddle/fluid/operators/quantize_mkldnn_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 "mkldnn.hpp"
+#include "paddle/fluid/framework/tensor.h"
+#include "paddle/fluid/operators/quantize_op.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
+#include "paddle/fluid/platform/mkldnn_reuse.h"
+
+namespace paddle {
+namespace operators {
+
+using mkldnn::memory;
+using mkldnn::primitive;
+using mkldnn::reorder;
+using platform::to_void_cast;
+using Tensor = framework::Tensor;
+using framework::DataLayout;
+using mkldnn::stream;
+using platform::GetMKLDNNFormat;
+
+template <typename T>
+class QuantOpKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* input = ctx.Input<Tensor>("Input");
+    auto scale_data = ctx.Attr<float>("Scale");
+    auto* output = ctx.Output<Tensor>("Output");
+    auto& dev_ctx =
+        ctx.template device_context<platform::MKLDNNDeviceContext>();
+    const auto& engine = dev_ctx.GetEngine();
+
+    std::vector<primitive> pipeline;
+    std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
+    std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
+
+    const T* input_data = input->data<T>();
+
+    mkldnn::primitive_attr attri;
+    int mask = 0;
+    attri.set_output_scales(mask, {scale_data});
+
+    auto src_md = platform::MKLDNNMemDesc({src_tz}, memory::data_type::f32,
+                                          input->format());
+    auto src_pd = mkldnn::memory::primitive_desc(src_md, engine);
+    auto src_memory =
+        std::make_shared<mkldnn::memory>(src_pd, to_void_cast<T>(input_data));
+    std::shared_ptr<primitive::at> src_memory_p =
+        std::shared_ptr<primitive::at>(new primitive::at(*src_memory));
+
+    bool is_negative = ctx.Attr<bool>("is_negative_input");
+    std::shared_ptr<mkldnn::memory::primitive_desc> dst_pd;
+    std::shared_ptr<mkldnn::memory> dst_memory;
+    if (is_negative) {
+      platform::ConvMKLDNNHandler::SetDstMemory<int8_t>(
+          ctx, output, dst_tz, engine, dst_pd, dst_memory);
+    } else {
+      platform::ConvMKLDNNHandler::SetDstMemory<uint8_t>(
+          ctx, output, dst_tz, engine, dst_pd, dst_memory);
+    }
+    auto reorder_pd = std::shared_ptr<reorder::primitive_desc>(
+        new reorder::primitive_desc(src_pd, *dst_pd, attri));
+    auto reorder_p = std::shared_ptr<reorder>(
+        new reorder(*reorder_pd, *src_memory_p, *dst_memory));
+    pipeline.push_back(*reorder_p);
+    stream(stream::kind::eager).submit(pipeline).wait();
+    output->set_layout(DataLayout::kMKLDNN);
+    output->set_format(GetMKLDNNFormat(*dst_memory));
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+namespace ops = paddle::operators;
+
+// TODO(Xiaoli) Support FP32->S8 quantization.
+
+REGISTER_OP_KERNEL(quantize, MKLDNN, ::paddle::platform::CPUPlace,
+                   ops::QuantOpKernel<float>);

paddle/fluid/operators/quantize_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/quantize_op.h"
+#ifdef PADDLE_WITH_MKLDNN
+#include "paddle/fluid/platform/mkldnn_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+framework::OpKernelType QuantOp::GetExpectedKernelType(
+    const framework::ExecutionContext& ctx) const {
+  framework::LibraryType library_ = framework::LibraryType::kMKLDNN;
+  framework::DataLayout layout_ = framework::DataLayout::kMKLDNN;
+
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout_, library_);
+}
+
+void QuantOpMaker::Make() {
+  AddInput("Input", "input data");
+  AddOutput("Output", "output data");
+  AddAttr<bool>("is_negative_input",
+                "(bool, default false) Only used in mkldnn INT8 kernel")
+      .SetDefault(false);
+  AddAttr<float>("Scale", "scale data").SetDefault({1.0f});
+  AddComment(R"DOC(This op will quantize data from FP32 to INT8)DOC");
+}
+
+}  // namespace operators
+}  // namespace paddle
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(quantize, ops::QuantOp, ops::QuantOpMaker,
+                  paddle::framework::DefaultGradOpDescMaker<true>);

paddle/fluid/operators/quantize_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 <string>
+#include <vector>
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using framework::OpKernelType;
+using framework::Tensor;
+
+class QuantOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    ctx->SetOutputDim("Output", ctx->GetInputDim("Input"));
+    ctx->ShareLoD("Input", /*->*/ "Output");
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override;
+};
+
+class QuantOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override;
+};
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/platform/mkldnn_reuse.h

@@ -15,6 +15,7 @@ limitations under the License. */
 
 #include <string>
 #include <vector>
+#include "paddle/fluid/framework/data_layout_transform.h"
 #include "paddle/fluid/framework/operator.h"
 #include "paddle/fluid/platform/mkldnn_helper.h"
 #include "paddle/fluid/platform/place.h"
@@ -181,6 +182,21 @@ class MKLDNNHandler {
     return dims2str(operand_dims) + suffix;
   }
 
+  template <typename M>
+  static void SetDstMemory(
+      const framework::ExecutionContext& ctx, framework::Tensor* output,
+      std::vector<int> dst_tz, const mkldnn::engine& engine,
+      std::shared_ptr<mkldnn::memory::primitive_desc>& dst_pd,  // NOLINT
+      std::shared_ptr<mkldnn::memory>& dst_memory) {            // NOLINT
+    M* output_data = output->mutable_data<M>(ctx.GetPlace());
+    auto dst_md = platform::MKLDNNMemDesc(
+        {dst_tz}, paddle::framework::ToMKLDNNDataType(
+                      framework::DataTypeTrait<M>::DataType),
+        mkldnn::memory::format::nhwc);
+    dst_pd.reset(new mkldnn::memory::primitive_desc(dst_md, engine));
+    dst_memory.reset(new mkldnn::memory(*dst_pd, to_void_cast<M>(output_data)));
+  }
+
  protected:
   static std::string dims2str(const mkldnn::memory::dims& operand_dims) {
     std::string dstr = "";

python/paddle/fluid/tests/unittests/ngraph/test_fill_constant_ngraph_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
+from paddle.fluid.tests.unittests.test_fill_constant_op import TestFillConstantOp1, TestFillConstantOp2, TestFillConstantOpWithSelectedRows
+
+
+class TestNGRAPHFillConstantOp1(TestFillConstantOp1):
+    def setUp(self):
+        super(TestNGRAPHFillConstantOp1, self).setUp()
+
+
+class TestNGRAPHFillConstantOp2(TestFillConstantOp2):
+    def setUp(self):
+        super(TestNGRAPHFillConstantOp2, self).setUp()
+
+
+class TestNGRAPHFillConstantOpWithSelectedRows(
+        TestFillConstantOpWithSelectedRows):
+    def setUp(self):
+        super(TestFillConstantOpWithSelectedRows, self).setUp()
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ngraph/test_top_k_ngraph_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
+from paddle.fluid.tests.unittests.test_top_k_op import TestTopkOp, TestTopkOp3d, TestTopkOp2, TestTopkOp3, TestTopkOp4
+
+
+class TestNGRAPHTopkOp(TestTopkOp):
+    def setUp(self):
+        super(TestNGRAPHTopkOp, self).setUp()
+
+
+class TestNGRAPHTopkOp2(TestTopkOp2):
+    def setUp(self):
+        super(TestNGRAPHTopkOp2, self).setUp()
+
+
+class TestNGRAPHTopkOp3(TestTopkOp3):
+    def setUp(self):
+        super(TestNGRAPHTopkOp3, self).setUp()
+
+
+class TestNGRAPHTopkOp4(TestTopkOp4):
+    def setUp(self):
+        super(TestNGRAPHTopkOp4, self).setUp()
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/test_dequantize_mkldnn_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 op_test import OpTest
+
+
+class TestDeQuantizeOp(OpTest):
+    def setUp(self):
+        self.op_type = 'dequantize'
+        self.scale = 2.0
+        self.input_size = [1, 1, 5, 5]  #Naive nChw16c
+        self.data_type = 'int8'
+        self.set_scale()
+        self.set_data_type()
+
+        if self.data_type == 'int8':
+            input = (np.random.randint(0, 100, self.input_size) - 50
+                     ).astype(self.data_type)
+            output = (input * (1 / self.scale)).astype('float')
+        else:
+            input = (np.random.randint(0, 100,
+                                       self.input_size)).astype(self.data_type)
+            output = (input * (1 / self.scale)).astype('float')
+
+        self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
+
+        self.outputs = {'Output': output}
+
+        self.attrs = {'Scale': self.scale, }
+
+    def test_check_output(self):
+        self.check_output()
+
+    def set_scale(self):
+        pass
+
+    def set_data_type(OpTest):
+        pass
+
+
+class TestDeQuantizeOp1(TestDeQuantizeOp):
+    def set_scale(self):
+        self.scale = 1.5
+
+    def set_data_type(self):
+        self.data_type = 'int8'
+
+
+class TestDeQuantizeOp2(TestDeQuantizeOp):
+    def set_scale(self):
+        self.scale = 0.8
+
+    def set_data_type(self):
+        self.data_type = 'uint8'
+
+
+if __name__ == '__main__':
+    unittest.main()

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

@@ -1018,9 +1018,8 @@ class TestBook(unittest.TestCase):
     def test_shuffle_channel(self):
         program = Program()
         with program_guard(program):
-            x = layers.data(name="x", shape=[1, 4, 2, 2], dtype="float32")
-            group = layers.data(name="group", shape=[1], dtype="int32")
-            out = layers.shuffle_channel(x, group)
+            x = layers.data(name="x", shape=[10, 16, 4, 4], dtype="float32")
+            out = layers.shuffle_channel(x, group=2)
             self.assertIsNotNone(out)
         print(str(program))
 

python/paddle/fluid/tests/unittests/test_quantize_mkldnn_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 op_test import OpTest
+
+
+class TestQuantizeOp(OpTest):
+    def setUp(self):
+        self.op_type = 'quantize'
+        self.scale = 2.0
+        self.input_size = [1, 1, 5, 5]  #Naive nChw16c
+        self.is_negative = False
+        self.set_scale()
+        self.set_is_negative()
+
+        if self.is_negative:
+            input = (100 * np.random.random_sample(self.input_size) - 50
+                     ).astype('float32')
+            output = np.round(input * self.scale).astype('int8')
+        else:
+            input = (100 *
+                     np.random.random_sample(self.input_size)).astype('float32')
+            output = np.round(input * self.scale).astype('uint8')
+
+        self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
+
+        self.outputs = {'Output': output}
+
+        self.attrs = {
+            'Scale': self.scale,
+            'is_negative_input': self.is_negative
+        }
+
+    def test_check_output(self):
+        self.check_output()
+
+    def set_scale(self):
+        pass
+
+    def set_is_negative(self):
+        pass
+
+
+class TestQuantizeOp1(TestQuantizeOp):
+    def set_scale(self):
+        self.scale = 1.5
+
+    def set_is_negative(self):
+        self.is_nagative = True
+
+
+class TestQuantizeOp2(TestQuantizeOp):
+    def set_scale(self):
+        self.scale = 0.1
+
+    def set_is_negative(self):
+        self.is_nagative = False
+
+
+if __name__ == '__main__':
+    unittest.main()

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

@@ -25,11 +25,11 @@ import paddle.fluid.core as core
 class TestShuffleChannelOp(OpTest):
     def setUp(self):
         self.op_type = "shuffle_channel"
-        self.batch_size = 1
-        self.input_channels = 4
-        self.layer_h = 2
-        self.layer_w = 2
-        self.group = 2
+        self.batch_size = 10
+        self.input_channels = 16
+        self.layer_h = 4
+        self.layer_w = 4
+        self.group = 4
         self.x = np.random.random(
             (self.batch_size, self.input_channels, self.layer_h,
              self.layer_w)).astype('float32')