revert-15296-async_double_buffered_py_reader
dzhwinter
6 years ago
commit
06f2448848
@ -1,147 +0,0 @@
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# - This module looks for Sphinx
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# Find the Sphinx documentation generator
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#
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# This modules defines
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# SPHINX_EXECUTABLE
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# SPHINX_FOUND
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find_program(SPHINX_EXECUTABLE
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NAMES sphinx-build
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PATHS
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/usr/bin
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/usr/local/bin
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/opt/local/bin
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DOC "Sphinx documentation generator"
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)
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if( NOT SPHINX_EXECUTABLE )
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set(_Python_VERSIONS
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2.7 2.6 2.5 2.4 2.3 2.2 2.1 2.0 1.6 1.5
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)
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foreach( _version ${_Python_VERSIONS} )
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set( _sphinx_NAMES sphinx-build-${_version} )
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find_program( SPHINX_EXECUTABLE
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NAMES ${_sphinx_NAMES}
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PATHS
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/usr/bin
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/usr/local/bin
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/opt/loca/bin
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DOC "Sphinx documentation generator"
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)
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endforeach()
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endif()
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include(FindPackageHandleStandardArgs)
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find_package_handle_standard_args(Sphinx DEFAULT_MSG
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SPHINX_EXECUTABLE
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)
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option( SPHINX_HTML_OUTPUT "Build a single HTML with the whole content." ON )
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option( SPHINX_DIRHTML_OUTPUT "Build HTML pages, but with a single directory per document." OFF )
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option( SPHINX_HTMLHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in htmlhelp." OFF )
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option( SPHINX_QTHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in qthelp." OFF )
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option( SPHINX_DEVHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in devhelp." OFF )
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option( SPHINX_EPUB_OUTPUT "Build HTML pages with additional information for building a documentation collection in epub." OFF )
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option( SPHINX_LATEX_OUTPUT "Build LaTeX sources that can be compiled to a PDF document using pdflatex." OFF )
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option( SPHINX_MAN_OUTPUT "Build manual pages in groff format for UNIX systems." OFF )
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option( SPHINX_TEXT_OUTPUT "Build plain text files." OFF )
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mark_as_advanced(
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SPHINX_EXECUTABLE
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SPHINX_HTML_OUTPUT
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SPHINX_DIRHTML_OUTPUT
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SPHINX_HTMLHELP_OUTPUT
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SPHINX_QTHELP_OUTPUT
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SPHINX_DEVHELP_OUTPUT
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SPHINX_EPUB_OUTPUT
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SPHINX_LATEX_OUTPUT
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SPHINX_MAN_OUTPUT
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SPHINX_TEXT_OUTPUT
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)
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function( Sphinx_add_target target_name builder conf cache source destination )
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add_custom_target( ${target_name} ALL
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COMMAND ${SPHINX_EXECUTABLE} -b ${builder}
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-d ${cache}
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-c ${conf}
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${source}
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${destination}
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COMMENT "Generating sphinx documentation: ${builder}"
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COMMAND cd ${destination} && ln -sf ./index_*.html index.html
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)
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set_property(
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DIRECTORY APPEND PROPERTY
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ADDITIONAL_MAKE_CLEAN_FILES
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${destination}
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)
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endfunction()
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# Target dependencies can be optionally listed at the end.
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function( Sphinx_add_targets target_base_name conf source base_destination )
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set( _dependencies )
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foreach( arg IN LISTS ARGN )
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set( _dependencies ${_dependencies} ${arg} )
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endforeach()
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if( ${SPHINX_HTML_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_html html ${conf} ${source} ${base_destination}/html )
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add_dependencies( ${target_base_name}_html ${_dependencies} )
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endif()
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if( ${SPHINX_DIRHTML_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_dirhtml dirhtml ${conf} ${source} ${base_destination}/dirhtml )
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add_dependencies( ${target_base_name}_dirhtml ${_dependencies} )
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endif()
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if( ${SPHINX_QTHELP_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_qthelp qthelp ${conf} ${source} ${base_destination}/qthelp )
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add_dependencies( ${target_base_name}_qthelp ${_dependencies} )
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endif()
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if( ${SPHINX_DEVHELP_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_devhelp devhelp ${conf} ${source} ${base_destination}/devhelp )
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add_dependencies( ${target_base_name}_devhelp ${_dependencies} )
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endif()
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if( ${SPHINX_EPUB_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_epub epub ${conf} ${source} ${base_destination}/epub )
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add_dependencies( ${target_base_name}_epub ${_dependencies} )
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endif()
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if( ${SPHINX_LATEX_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_latex latex ${conf} ${source} ${base_destination}/latex )
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add_dependencies( ${target_base_name}_latex ${_dependencies} )
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endif()
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if( ${SPHINX_MAN_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_man man ${conf} ${source} ${base_destination}/man )
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add_dependencies( ${target_base_name}_man ${_dependencies} )
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endif()
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if( ${SPHINX_TEXT_OUTPUT} )
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Sphinx_add_target( ${target_base_name}_text text ${conf} ${source} ${base_destination}/text )
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add_dependencies( ${target_base_name}_text ${_dependencies} )
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endif()
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if( ${BUILD_TESTING} )
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sphinx_add_target( ${target_base_name}_linkcheck linkcheck ${conf} ${source} ${base_destination}/linkcheck )
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add_dependencies( ${target_base_name}_linkcheck ${_dependencies} )
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endif()
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endfunction()
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@ -0,0 +1,223 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/inference/tests/api/tester_helper.h"
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namespace paddle {
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namespace inference {
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using paddle::PaddleTensor;
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template <typename T>
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void GetValueFromStream(std::stringstream *ss, T *t) {
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(*ss) >> (*t);
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}
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template <>
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void GetValueFromStream<std::string>(std::stringstream *ss, std::string *t) {
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*t = ss->str();
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}
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// Split string to vector
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template <typename T>
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void Split(const std::string &line, char sep, std::vector<T> *v) {
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std::stringstream ss;
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T t;
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for (auto c : line) {
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if (c != sep) {
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ss << c;
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} else {
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GetValueFromStream<T>(&ss, &t);
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v->push_back(std::move(t));
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ss.str({});
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ss.clear();
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}
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}
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if (!ss.str().empty()) {
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GetValueFromStream<T>(&ss, &t);
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v->push_back(std::move(t));
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ss.str({});
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ss.clear();
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}
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}
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template <typename T>
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constexpr paddle::PaddleDType GetPaddleDType();
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template <>
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constexpr paddle::PaddleDType GetPaddleDType<int64_t>() {
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return paddle::PaddleDType::INT64;
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}
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template <>
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constexpr paddle::PaddleDType GetPaddleDType<float>() {
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return paddle::PaddleDType::FLOAT32;
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}
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// Parse tensor from string
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template <typename T>
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bool ParseTensor(const std::string &field, paddle::PaddleTensor *tensor) {
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std::vector<std::string> data;
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Split(field, ':', &data);
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if (data.size() < 2) return false;
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std::string shape_str = data[0];
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std::vector<int> shape;
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Split(shape_str, ' ', &shape);
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std::string mat_str = data[1];
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std::vector<T> mat;
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Split(mat_str, ' ', &mat);
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tensor->shape = shape;
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auto size =
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std::accumulate(shape.begin(), shape.end(), 1, std::multiplies<int>()) *
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sizeof(T);
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tensor->data.Resize(size);
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std::copy(mat.begin(), mat.end(), static_cast<T *>(tensor->data.data()));
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tensor->dtype = GetPaddleDType<T>();
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return true;
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}
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// Parse input tensors from string
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bool ParseLine(const std::string &line,
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std::vector<paddle::PaddleTensor> *tensors) {
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std::vector<std::string> fields;
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Split(line, ';', &fields);
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if (fields.size() < 5) return false;
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tensors->clear();
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tensors->reserve(5);
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int i = 0;
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// src_id
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paddle::PaddleTensor src_id;
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ParseTensor<int64_t>(fields[i++], &src_id);
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tensors->push_back(src_id);
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// pos_id
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paddle::PaddleTensor pos_id;
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ParseTensor<int64_t>(fields[i++], &pos_id);
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tensors->push_back(pos_id);
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// segment_id
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paddle::PaddleTensor segment_id;
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ParseTensor<int64_t>(fields[i++], &segment_id);
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tensors->push_back(segment_id);
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// self_attention_bias
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paddle::PaddleTensor self_attention_bias;
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ParseTensor<float>(fields[i++], &self_attention_bias);
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tensors->push_back(self_attention_bias);
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// next_segment_index
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paddle::PaddleTensor next_segment_index;
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ParseTensor<int64_t>(fields[i++], &next_segment_index);
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tensors->push_back(next_segment_index);
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return true;
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}
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bool LoadInputData(std::vector<std::vector<paddle::PaddleTensor>> *inputs) {
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if (FLAGS_infer_data.empty()) {
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LOG(ERROR) << "please set input data path";
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return false;
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}
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std::ifstream fin(FLAGS_infer_data);
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std::string line;
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int sample = 0;
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// The unit-test dataset only have 10 samples, each sample have 5 feeds.
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while (std::getline(fin, line)) {
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std::vector<paddle::PaddleTensor> feed_data;
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ParseLine(line, &feed_data);
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inputs->push_back(std::move(feed_data));
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sample++;
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if (!FLAGS_test_all_data && sample == FLAGS_batch_size) break;
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}
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LOG(INFO) << "number of samples: " << sample;
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return true;
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}
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void SetConfig(AnalysisConfig *config) { config->SetModel(FLAGS_infer_model); }
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void profile(bool use_mkldnn = false) {
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AnalysisConfig config;
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SetConfig(&config);
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if (use_mkldnn) {
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config.EnableMKLDNN();
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}
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std::vector<PaddleTensor> outputs;
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std::vector<std::vector<PaddleTensor>> inputs;
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LoadInputData(&inputs);
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TestPrediction(reinterpret_cast<const PaddlePredictor::Config *>(&config),
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inputs, &outputs, FLAGS_num_threads);
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}
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TEST(Analyzer_bert, profile) { profile(); }
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#ifdef PADDLE_WITH_MKLDNN
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TEST(Analyzer_bert, profile_mkldnn) { profile(true); }
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#endif
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// Check the fuse status
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TEST(Analyzer_bert, fuse_statis) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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int num_ops;
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auto predictor = CreatePaddlePredictor<AnalysisConfig>(cfg);
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auto fuse_statis = GetFuseStatis(
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static_cast<AnalysisPredictor *>(predictor.get()), &num_ops);
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LOG(INFO) << "num_ops: " << num_ops;
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}
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// Compare result of NativeConfig and AnalysisConfig
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void compare(bool use_mkldnn = false) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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if (use_mkldnn) {
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cfg.EnableMKLDNN();
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}
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std::vector<std::vector<PaddleTensor>> inputs;
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LoadInputData(&inputs);
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CompareNativeAndAnalysis(
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reinterpret_cast<const PaddlePredictor::Config *>(&cfg), inputs);
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}
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TEST(Analyzer_bert, compare) { compare(); }
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#ifdef PADDLE_WITH_MKLDNN
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TEST(Analyzer_bert, compare_mkldnn) { compare(true /* use_mkldnn */); }
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#endif
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// Compare Deterministic result
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TEST(Analyzer_bert, compare_determine) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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std::vector<std::vector<PaddleTensor>> inputs;
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LoadInputData(&inputs);
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CompareDeterministic(reinterpret_cast<const PaddlePredictor::Config *>(&cfg),
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inputs);
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}
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} // namespace inference
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} // namespace paddle
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