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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/06/30 20:23:41 UTC
[GitHub] szha closed pull request #9860: [WIP] CMake NNPack support
szha closed pull request #9860: [WIP] CMake NNPack support
URL: https://github.com/apache/incubator-mxnet/pull/9860
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diff --git a/.gitignore b/.gitignore
index 6be98c50466..90a05eaa2cd 100644
--- a/.gitignore
+++ b/.gitignore
@@ -127,6 +127,11 @@ CMakeFiles
cmake_install.cmake
lib
+# Kate / Kdevelop files
+*.kate-swp
+*.kdev4
+
+
# Visual Studio Code
.vscode
diff --git a/.gitmodules b/.gitmodules
index cdb8a553679..ea391ea584a 100644
--- a/.gitmodules
+++ b/.gitmodules
@@ -26,3 +26,6 @@
[submodule "3rdparty/cub"]
path = 3rdparty/cub
url = https://github.com/dmlc/cub
+[submodule "3rdparty/nnpack/NNPACK"]
+ path = 3rdparty/NNPACK
+ url = https://github.com/Maratyszcza/NNPACK
diff --git a/3rdparty/NNPACK b/3rdparty/NNPACK
new file mode 160000
index 00000000000..83af25db118
--- /dev/null
+++ b/3rdparty/NNPACK
@@ -0,0 +1 @@
+Subproject commit 83af25db11883e160e65005f065f260488643c26
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 16d365355ce..6f97af51ad3 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -34,6 +34,7 @@ mxnet_option(USE_VTUNE "Enable use of Intel Amplifier XE (VTune)" OFF
mxnet_option(ENABLE_CUDA_RTC "Build with CUDA runtime compilation support" ON)
mxnet_option(INSTALL_EXAMPLES "Install the example source files." OFF)
mxnet_option(USE_SIGNAL_HANDLER "Print stack traces on segfaults." OFF)
+mxnet_option(USE_NNPACK "Build with NNPack support." OFF)
if(USE_CUDA AND NOT USE_OLDCMAKECUDA)
message(STATUS "CMake version '${CMAKE_VERSION}' using generator '${CMAKE_GENERATOR}'")
@@ -551,6 +552,52 @@ if(NOT EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/nnvm/CMakeLists.txt")
list(APPEND mxnet_LINKER_LIBS ${nnvm_LINKER_LIBS})
endif()
+# ---[ NNPack
+if(USE_NNPACK)
+ if (USE_MKLDNN)
+ message(FATAL_ERROR "Either MKLDNN or NNPack can be enabled but not both.")
+ endif()
+ # Add in NNPack and its dependencies
+ set(NNPACK_SOURCE_DIR "${CMAKE_SOURCE_DIR}/3rdparty/NNPACK")
+ if (EXISTS "${NNPACK_SOURCE_DIR}")
+ if (GOOGLETEST_SOURCE_DIR AND EXISTS "${GOOGLETEST_SOURCE_DIR}")
+ set(GOOGLETEST_SOURCE_DIR "${GTEST_ROOT}" CACHE STRING "Google Test source directory")
+ endif()
+
+ # Disable NNPack internal testing
+ set(NNPACK_BUILD_TESTS OFF CACHE BOOL "")
+ set(NNPACK_BUILD_BENCHMARKS OFF CACHE BOOL "")
+
+ # Compile statically
+ set(NNPACK_LIBRARY_TYPE "static" CACHE STRING "")
+ set(PTHREADPOOL_LIBRARY_TYPE "static" CACHE STRING "")
+ set(CPUINFO_LIBRARY_TYPE "static" CACHE STRING "")
+
+ # put NNPack dependencies in appropriate folders, see NNPack
+ # for other options
+ set(CONFU_DEPENDENCIES_SOURCE_DIR "${NNPACK_SOURCE_DIR}/deps"
+ CACHE PATH "Confu-style dependencies source directory")
+ set(CONFU_DEPENDENCIES_BINARY_DIR "${CMAKE_BINARY_DIR}/3rdparty/NNPACK/deps"
+ CACHE PATH "Confu-style dependencies source directory")
+
+ add_subdirectory("${NNPACK_SOURCE_DIR}")
+
+ # compile with -fPIC
+ set_property(TARGET nnpack PROPERTY POSITION_INDEPENDENT_CODE ON)
+ set_property(TARGET pthreadpool PROPERTY POSITION_INDEPENDENT_CODE ON)
+ set_property(TARGET cpuinfo PROPERTY POSITION_INDEPENDENT_CODE ON)
+
+ include_directories(${NNPACK_SOURCE_DIR}/include)
+ #PTHREADPOOL_SOURCE_DIR is set in cache by NNPack
+ include_directories(${PTHREADPOOL_SOURCE_DIR}/include)
+ add_definitions(-DMXNET_USE_NNPACK=1)
+ set(NNPack_LINKER_LIBS nnpack)
+ list(APPEND mxnet_LINKER_LIBS ${NNPack_LINKER_LIBS})
+ else()
+ message("NNPack submodule not found.")
+ endif()
+endif()
+
if(NOT MSVC)
# Only add c++11 flags and definitions after cuda compiling
add_definitions(-DDMLC_USE_CXX11)
diff --git a/src/operator/convolution_v1.cc b/src/operator/convolution_v1.cc
index 86c0fbb3329..7d561f7d5ca 100644
--- a/src/operator/convolution_v1.cc
+++ b/src/operator/convolution_v1.cc
@@ -25,9 +25,6 @@
*/
#include "./convolution_v1-inl.h"
-#if MXNET_USE_NNPACK == 1
-#include "./nnpack/nnpack_convolution-inl.h"
-#endif // MXNET_USE_NNPACK
namespace mxnet {
namespace op {
diff --git a/src/operator/nn/convolution.cc b/src/operator/nn/convolution.cc
index 951063fb4b2..69ed4713d2c 100644
--- a/src/operator/nn/convolution.cc
+++ b/src/operator/nn/convolution.cc
@@ -28,9 +28,7 @@
#include "../elemwise_op_common.h"
#include "./mkldnn/mkldnn_ops-inl.h"
#include "./mkldnn/mkldnn_base-inl.h"
-#if MXNET_USE_NNPACK == 1
-#include "./nnpack/nnpack_convolution-inl.h"
-#endif // MXNET_USE_NNPACK
+#include "./nnpack/nnpack_ops-inl.h"
namespace mxnet {
namespace op {
diff --git a/src/operator/nn/fully_connected.cc b/src/operator/nn/fully_connected.cc
index 4362408a23a..b2b202a4ce0 100644
--- a/src/operator/nn/fully_connected.cc
+++ b/src/operator/nn/fully_connected.cc
@@ -25,9 +25,7 @@
#include "./fully_connected-inl.h"
#include "./mkldnn/mkldnn_ops-inl.h"
#include "./mkldnn/mkldnn_base-inl.h"
-#if MXNET_USE_NNPACK == 1
-#include "./nnpack/nnpack_fully_connected-inl.h"
-#endif // MXNET_USE_NNPACK
+#include "./nnpack/nnpack_ops-inl.h"
namespace mxnet {
namespace op {
diff --git a/src/operator/nn/nnpack/nnpack_ops-inl.h b/src/operator/nn/nnpack/nnpack_ops-inl.h
new file mode 100644
index 00000000000..279349206aa
--- /dev/null
+++ b/src/operator/nn/nnpack/nnpack_ops-inl.h
@@ -0,0 +1,68 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ * \file nnpack_ops-inl.h
+ * \brief
+ * \author David Braude
+*/
+
+#ifndef MXNET_OPERATOR_NN_NNPACK_NNPACK_OPS_INL_H_
+#define MXNET_OPERATOR_NN_NNPACK_NNPACK_OPS_INL_H_
+
+#if MXNET_USE_NNPACK == 1
+
+#include <mxnet/io.h>
+#include <mxnet/base.h>
+#include <mxnet/ndarray.h>
+#include <mxnet/operator.h>
+#include <mxnet/operator_util.h>
+#include <dmlc/logging.h>
+#include <dmlc/optional.h>
+#include <vector>
+#include <nnpack.h>
+
+// TODO:
+// Convolutional layer
+// Inference-optimized forward propagation (nnp_convolution_inference)
+// Training-optimized forward propagation (nnp_convolution_output)
+// Training-optimized backward input gradient update (nnp_convolution_input_gradient)
+// Training-optimized backward kernel gradient update (nnp_convolution_kernel_gradient)
+// Fully-connected layer
+// Inference-optimized forward propagation (nnp_fully_connected_inference and nnp_fully_connected_inference_f16f32 version for FP16 weights)
+// Training-optimized forward propagation (nnp_fully_connected_output)
+// Max pooling layer
+// Forward propagation, both for training and inference, (nnp_max_pooling_output)
+// ReLU layer (with parametrized negative slope)
+// Forward propagation, both for training and inference, optionally in-place, (nnp_relu_output)
+// Backward input gradient update (nnp_relu_input_gradient)
+
+namespace mxnet {
+namespace op {
+
+/* For softmax */
+void NNPACKSoftmaxForward(const nnvm::NodeAttrs& attrs, const OpContext &ctx,
+ const NDArray &in_data, const OpReqType &req,
+ const NDArray &out_data);
+
+} // namespace op
+} // namespace mxnet
+#endif // MXNET_USE_MKLDNN == 1
+
+#endif // MXNET_OPERATOR_NN_MKLDNN_MKLDNN_OPS_INL_H_
diff --git a/src/operator/nnpack/nnpack_util.cc b/src/operator/nn/nnpack/nnpack_softmax.cc
similarity index 59%
rename from src/operator/nnpack/nnpack_util.cc
rename to src/operator/nn/nnpack/nnpack_softmax.cc
index 7d075e0554b..a1246545e6c 100644
--- a/src/operator/nnpack/nnpack_util.cc
+++ b/src/operator/nn/nnpack/nnpack_softmax.cc
@@ -18,20 +18,31 @@
*/
/*!
- * Copyright (c) 2016 by Contributors
- * \file nnpack_util.cc
+ * \file nnpack_softmax.cc
* \brief
- * \author Wei Wu
+ * \author David Braude
*/
-#if MXNET_USE_NNPACK == 1
-#include "nnpack_util.h"
+#include "../softmax-inl.h"
+#include "./nnpack_ops-inl.h"
+
+#if MXNET_USE_NNPACK == 1
namespace mxnet {
namespace op {
-NNPACKInitialize nnpackinitialize;
+void NNPACKSoftmaxForward(const nnvm::NodeAttrs& attrs, const OpContext &ctx,
+ const NDArray &in_data, const OpReqType &req,
+ const NDArray &out_data) {
+ const SoftmaxParam& param = nnvm::get<SoftmaxParam>(attrs.parsed);
+// enum nnp_status nnp_softmax_output(
+// size_t batch_size,
+// size_t channels,
+// const float input[],
+// float output[],
+// pthreadpool_t threadpool);
+}
-} // namespace op
-} // namespace mxnet
-#endif // MXNET_USE_NNPACK
+} // namespace op
+} // namespace mxnet
+#endif
diff --git a/src/operator/nn/pooling.cc b/src/operator/nn/pooling.cc
index f719e0753e0..d13d43b1325 100644
--- a/src/operator/nn/pooling.cc
+++ b/src/operator/nn/pooling.cc
@@ -25,12 +25,8 @@
*/
#include "../elemwise_op_common.h"
#include "./pooling-inl.h"
-#if MXNET_USE_NNPACK == 1
-#include "./nnpack/nnpack_pooling-inl.h"
-#endif // MXNET_USE_NNPACK
-#if MXNET_USE_MKLDNN == 1
+// #include "./nnpack/nnpack_pooling-inl.h"
#include "./mkldnn/mkldnn_pooling-inl.h"
-#endif // MXNET_USE_MKLDNN
namespace mxnet {
namespace op {
diff --git a/src/operator/nnpack/nnpack_convolution-inl.h b/src/operator/nnpack/nnpack_convolution-inl.h
deleted file mode 100644
index 0e2c73693d1..00000000000
--- a/src/operator/nnpack/nnpack_convolution-inl.h
+++ /dev/null
@@ -1,124 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you 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.
- */
-
-/*!
- * Copyright (c) 2016 by Contributors
- * \file nnpack_convolution-inl.h
- * \brief
- * \author Carwin
-*/
-#ifndef MXNET_OPERATOR_NNPACK_NNPACK_CONVOLUTION_INL_H_
-#define MXNET_OPERATOR_NNPACK_NNPACK_CONVOLUTION_INL_H_
-
-#include <dmlc/logging.h>
-#include <dmlc/parameter.h>
-#include <mxnet/operator.h>
-#include <algorithm>
-#include <map>
-#include <vector>
-#include <string>
-#include <utility>
-#include "../convolution-inl.h"
-#include "nnpack.h"
-#include "nnpack_util.h"
-
-namespace mxnet {
-namespace op {
-
-template <typename xpu, typename DType>
-class NNPACKConvolutionOp : public ConvolutionOp<xpu, DType> {
- private:
- ConvolutionParam param_;
-
- public:
- explicit NNPACKConvolutionOp(ConvolutionParam p)
- : ConvolutionOp<xpu, DType>(p) {
- this->param_ = p;
- }
-
- public:
- virtual void Forward(const OpContext &ctx, const std::vector<TBlob> &in_data,
- const std::vector<OpReqType> &req,
- const std::vector<TBlob> &out_data,
- const std::vector<TBlob> &aux_args) {
- using namespace mshadow;
- using namespace mshadow::expr;
- Stream<xpu> *s = ctx.get_stream<xpu>();
- Tensor<xpu, 4, DType> data = in_data[conv::kData].get<xpu, 4, DType>(s);
- const size_t batch_size = data.shape_[0];
- const size_t input_c = data.shape_[1];
- const size_t input_h = data.shape_[2];
- const size_t input_w = data.shape_[3];
- Shape<3> wmat_shape =
- Shape3(param_.num_group, param_.num_filter / param_.num_group,
- input_c / param_.num_group * param_.kernel[0] *
- param_.kernel[1]);
- Tensor<xpu, 3, DType> wmat =
- in_data[conv::kWeight].get_with_shape<xpu, 3, DType>(wmat_shape, s);
- Tensor<xpu, 4, DType> out = out_data[conv::kOut].get<xpu, 4, DType>(s);
- nnp_size input_size = {input_w, input_h};
- nnp_padding input_padding = {param_.pad[0], param_.pad[1], param_.pad[0],
- param_.pad[1]};
- nnp_size kernel_size = {param_.kernel[1], param_.kernel[0]};
- nnp_size output_subsampling = {param_.stride[1], param_.stride[0]};
- Tensor<xpu, 1, DType> bias = in_data[conv::kBias].get<xpu, 1, DType>(s);
-
- nnp_convolution_algorithm algorithm = nnp_convolution_algorithm_auto;
- nnp_convolution_transform_strategy kts = nnp_convolution_transform_strategy_tuple_based;
- nnp_status status = nnp_status_success;
- if (batch_size == 1) {
- status = nnp_convolution_inference(
- algorithm, // enum nnp_convolution_algorithm,
- kts, // enum nnp_convolution_transform_strategy,
- input_c, // size_t input_channels,
- param_.num_filter, // size_t output_channels,
- input_size, // struct nnp_size input_size,
- input_padding, // struct nnp_padding input_padding,
- kernel_size, // struct nnp_size kernel_size,
- output_subsampling, // struct nnp_size output_subsampling,
- data.dptr_, // const float input[],
- wmat.dptr_, // const float kernel[],
- bias.dptr_, // const float bias[],
- out.dptr_, // float output[],
- nnpackinitialize.threadpool, // pthreadpool_t threadpool,
- nullptr);
- } else {
- status = nnp_convolution_output(
- algorithm, // enum nnp_convolution_algorithm algorithm,
- batch_size, // size_t batch size of input tensor
- input_c, // size_t input_channels,
- param_.num_filter, // size_t output_channels,
- input_size, // struct nnp_size input_size,
- input_padding, // struct nnp_padding input_padding,
- kernel_size, // struct nnp_size kernel_size,
- data.dptr_, // const float input[],
- wmat.dptr_, // const float kernel[],
- bias.dptr_, // const float bias[],
- out.dptr_, // float output[],
- nnpackinitialize.threadpool, // pthreadpool_t threadpool,
- nullptr);
- }
- if (nnp_status_success != status) {
- LOG(FATAL) << "nnpack convolution feedforward failed status=" << status;
- }
- }
-}; // class NNPACKConvolutionOp
-} // namespace op
-} // namespace mxnet
-#endif // MXNET_OPERATOR_NNPACK_NNPACK_CONVOLUTION_INL_H_
diff --git a/src/operator/nnpack/nnpack_fully_connected-inl.h b/src/operator/nnpack/nnpack_fully_connected-inl.h
deleted file mode 100644
index d9412d20d0c..00000000000
--- a/src/operator/nnpack/nnpack_fully_connected-inl.h
+++ /dev/null
@@ -1,108 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you 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.
- */
-
-/*!
- * Copyright (c) 2016 by Contributors
- * \file nnpack_fully_connected-inl.h
- * \brief
- * \author Wei Wu
-*/
-#ifndef MXNET_OPERATOR_NNPACK_NNPACK_FULLY_CONNECTED_INL_H_
-#define MXNET_OPERATOR_NNPACK_NNPACK_FULLY_CONNECTED_INL_H_
-
-#include <dmlc/logging.h>
-#include <dmlc/parameter.h>
-#include <mxnet/operator.h>
-#include <algorithm>
-#include <map>
-#include <vector>
-#include <string>
-#include <utility>
-#include "../fully_connected-inl.h"
-#include "nnpack.h"
-#include "nnpack_util.h"
-
-namespace mxnet {
-namespace op {
-
-template <typename xpu, typename DType>
-class NNPACKFullyConnectedOp : public FullyConnectedOp<xpu, DType> {
- private:
- FullyConnectedParam param_;
-
- public:
- explicit NNPACKFullyConnectedOp(FullyConnectedParam p)
- : FullyConnectedOp<xpu, DType>(p) {
- this->param_ = p;
- }
-
- public:
- virtual void Forward(const OpContext &ctx, const std::vector<TBlob> &in_data,
- const std::vector<OpReqType> &req,
- const std::vector<TBlob> &out_data,
- const std::vector<TBlob> &aux_args) {
- using namespace mshadow;
- using namespace mshadow::expr;
- if (req[fullc::kOut] == kNullOp) return;
- CHECK_EQ(req[fullc::kOut], kWriteTo);
- size_t expected = param_.no_bias ? 2 : 3;
- CHECK_EQ(in_data.size(), expected);
- CHECK_EQ(out_data.size(), 1);
- const TShape& ishape = in_data[fullc::kData].shape_;
- const TShape& oshape = out_data[fullc::kOut].shape_;
- Stream<xpu> *s = ctx.get_stream<xpu>();
- Tensor<xpu, 2, DType> data = in_data[fullc::kData].get_with_shape<xpu, 2, DType>(
- Shape2(ishape[0], ishape.ProdShape(1, ishape.ndim())), s);
- Tensor<xpu, 2, DType> wmat = in_data[fullc::kWeight].get<xpu, 2, DType>(s);
- Tensor<xpu, 2, DType> out = out_data[fullc::kOut].get_with_shape<xpu, 2, DType>(
- Shape2(oshape[0], oshape.ProdShape(1, oshape.ndim())), s);
- const size_t batch_size = data.shape_[0];
- const size_t input_c = data.shape_[1];
- nnp_status status = nnp_status_success;
- if (batch_size == 1) {
- status = nnp_fully_connected_inference(
- input_c, // size_t input_channels,
- param_.num_hidden, // size_t output_channels,
- data.dptr_, // const float input[],
- wmat.dptr_, // const float kernel[],
- out.dptr_, // float output[],
- nnpackinitialize.threadpool); // pthreadpool_t threadpool,
- } else {
- status = nnp_fully_connected_output(
- batch_size, // size_t batch size of input tensor
- input_c, // size_t input_channels,
- param_.num_hidden, // size_t output_channels,
- data.dptr_, // const float input[],
- wmat.dptr_, // const float kernel[],
- out.dptr_, // float output[],
- nnpackinitialize.threadpool, // pthreadpool_t threadpool,
- nullptr);
- }
- if (nnp_status_success != status) {
- LOG(FATAL) << "nnpack fully conneted feedforward failed status=" << status;
- }
- if (!param_.no_bias) {
- Tensor<xpu, 1, DType> bias = in_data[fullc::kBias].get<xpu, 1, DType>(s);
- out += repmat(bias, data.size(0));
- }
- }
-}; // class NNPACKFullyConnectedOp
-} // namespace op
-} // namespace mxnet
-#endif // MXNET_OPERATOR_NNPACK_NNPACK_FULLY_CONNECTED_INL_H_
diff --git a/src/operator/nnpack/nnpack_pooling-inl.h b/src/operator/nnpack/nnpack_pooling-inl.h
deleted file mode 100644
index 25b47832275..00000000000
--- a/src/operator/nnpack/nnpack_pooling-inl.h
+++ /dev/null
@@ -1,91 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you 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.
- */
-
-/*!
- * Copyright (c) 2016 by Contributors
- * \file nnpack_pooling-inl.h
- * \brief
- * \author Wei Wu
-*/
-#ifndef MXNET_OPERATOR_NNPACK_NNPACK_POOLING_INL_H_
-#define MXNET_OPERATOR_NNPACK_NNPACK_POOLING_INL_H_
-
-#include <dmlc/logging.h>
-#include <dmlc/parameter.h>
-#include <mxnet/operator.h>
-#include <algorithm>
-#include <map>
-#include <vector>
-#include <string>
-#include <utility>
-#include "../pooling-inl.h"
-#include "nnpack.h"
-#include "nnpack_util.h"
-
-namespace mxnet {
-namespace op {
-
-template <typename xpu, typename DType>
-class NNPACKPoolingOp : public PoolingOp<xpu, DType> {
- private:
- PoolingParam param_;
-
- public:
- explicit NNPACKPoolingOp(PoolingParam p)
- : PoolingOp<xpu, DType>(p) {
- this->param_ = p;
- }
-
- public:
- virtual void Forward(const OpContext &ctx, const std::vector<TBlob> &in_data,
- const std::vector<OpReqType> &req,
- const std::vector<TBlob> &out_data,
- const std::vector<TBlob> &aux_args) {
- using namespace mshadow;
- using namespace mshadow::expr;
- Stream<xpu> *s = ctx.get_stream<xpu>();
- Tensor<xpu, 4, DType> data = in_data[pool_enum::kData].get<xpu, 4, DType>(s);
- const size_t batch_size = data.shape_[0];
- const size_t input_c = data.shape_[1];
- const size_t input_h = data.shape_[2];
- const size_t input_w = data.shape_[3];
- Tensor<xpu, 4, DType> out = out_data[pool_enum::kOut].get<xpu, 4, DType>(s);
- nnp_size input_size = {input_w, input_h};
- nnp_padding input_padding = {param_.pad[0], param_.pad[1], param_.pad[0],
- param_.pad[1]};
- nnp_size kernel_size = {param_.kernel[1], param_.kernel[0]};
- nnp_size output_subsampling = {param_.stride[1], param_.stride[0]};
- nnp_status status = nnp_max_pooling_output(
- batch_size, // size_t batch size of input tensor
- input_c, // size_t input_channels,
- input_size, // struct nnp_size input_size,
- input_padding, // struct nnp_padding input_padding,
- kernel_size, // struct nnp_size kernel_size,
- output_subsampling, // struct nnp_size output_subsampling,
- data.dptr_, // const float input[],
- out.dptr_, // float output[],
- nnpackinitialize.threadpool); // pthreadpool_t threadpool,
- if (nnp_status_success != status) {
- LOG(FATAL) << "nnpack max pooling feedforward failed status=" << status;
- }
- }
-}; // class NNPACKPoolingOp
-} // namespace op
-} // namespace mxnet
-#endif // MXNET_OPERATOR_NNPACK_NNPACK_POOLING_INL_H_
diff --git a/src/operator/nnpack/nnpack_util.h b/src/operator/nnpack/nnpack_util.h
deleted file mode 100644
index 2edfb79ad46..00000000000
--- a/src/operator/nnpack/nnpack_util.h
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you 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.
- */
-
-/*!
- * Copyright (c) 2016 by Contributors
- * \file nnpack_util.h
- * \brief
- * \author Carwin
-*/
-#ifndef MXNET_OPERATOR_NNPACK_NNPACK_UTIL_H_
-#define MXNET_OPERATOR_NNPACK_NNPACK_UTIL_H_
-
-#include <dmlc/logging.h>
-#include <dmlc/parameter.h>
-#include <nnpack.h>
-
-namespace mxnet {
-namespace op {
-
-class NNPACKInitialize {
- public:
- pthreadpool_t threadpool;
-
- public:
- NNPACKInitialize() {
- nnp_status status = nnp_initialize();
- if (nnp_status_success != status) {
- LOG(FATAL) << "nnp_initialize failed status=" << status;
- }
- int num_threads = dmlc::GetEnv("MXNET_CPU_NNPACK_NTHREADS", 4);
- this->threadpool = pthreadpool_create(num_threads);
- }
- virtual ~NNPACKInitialize() {
- nnp_status status = nnp_deinitialize();
- if (nnp_status_success != status) {
- LOG(FATAL) << "nnp_deinitialize failed status=" << status;
- }
- pthreadpool_destroy(threadpool);
- }
-};
-
-// nnpackinitialize will be used in all other nnpack op
-extern NNPACKInitialize nnpackinitialize;
-
-} // namespace op
-} // namespace mxnet
-
-#endif // MXNET_OPERATOR_NNPACK_NNPACK_UTIL_H_
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