提交 ade66754 编写于 作者: Y Yancey1989

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

......@@ -282,7 +282,3 @@ if(WITH_DOC)
find_python_module(recommonmark REQUIRED)
add_subdirectory(doc)
endif()
if (WITH_CONTRIB)
add_subdirectory(paddle/contrib)
endif()
......@@ -138,25 +138,24 @@ copy(memory_lib
set(inference_deps paddle_fluid_shared paddle_fluid)
if(WITH_CONTRIB)
message(STATUS "installing contrib")
set(contrib_dst_dir "${FLUID_INSTALL_DIR}/contrib/inference")
if (WITH_ANAKIN AND WITH_GPU)
copy(contrib_anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS
${PADDLE_BINARY_DIR}/paddle/contrib/inference/libinference_anakin_api* # compiled anakin api
${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release
DSTS ${contrib_dst_dir}/anakin ${contrib_dst_dir}/anakin)
list(APPEND inference_deps contrib_anakin_inference_lib)
endif()
copy(contrib_inference_lib DEPS paddle_inference_api paddle_inference_api_shared
SRCS ${PADDLE_SOURCE_DIR}/paddle/contrib/inference/paddle_inference_api.h
${PADDLE_BINARY_DIR}/paddle/contrib/inference/libpaddle_inference_api*
DSTS ${contrib_dst_dir} ${contrib_dst_dir})
list(APPEND inference_deps contrib_inference_lib)
set(module "inference/api")
if (WITH_ANAKIN AND WITH_GPU)
copy(anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release
DSTS ${dst_dir}/inference/anakin ${dst_dir}/inference/anakin)
list(APPEND inference_deps anakin_inference_lib)
endif()
copy(inference_api_lib DEPS paddle_inference_api paddle_inference_api_shared
SRCS ${src_dir}/${module}/paddle_inference_api.h
${src_dir}/${module}/demo_ci
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libpaddle_inference_api*
DSTS ${dst_dir}/inference ${dst_dir}/inference ${dst_dir}/inference
)
list(APPEND inference_deps inference_api_lib)
set(module "inference")
copy(inference_lib DEPS ${inference_deps}
SRCS ${src_dir}/${module}/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.*
......
......@@ -4,7 +4,6 @@ API
.. toctree::
:maxdepth: 1
overview.rst
model_configs.rst
data.rst
run_logic.rst
此差异已折叠。
......@@ -5,7 +5,7 @@ if (TENSORRT_FOUND)
add_subdirectory(tensorrt)
endif()
set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor )
set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor)
# TODO(panyx0718): Should this be called paddle_fluid_inference_api_internal?
cc_library(paddle_fluid_api
......@@ -38,3 +38,4 @@ if(WITH_TESTING)
# both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book
add_subdirectory(tests/book)
endif()
add_subdirectory(api)
......@@ -43,21 +43,21 @@ function(inference_api_test TARGET_NAME)
endfunction(inference_api_test)
cc_library(paddle_inference_api
SRCS paddle_inference_api.cc paddle_inference_api_impl.cc
SRCS api.cc api_impl.cc
DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
if(NOT APPLE)
set(LINK_FLAGS "-Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/paddle_inference_api.sym")
set(LINK_FLAGS "-Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/api.sym")
set_target_properties(paddle_inference_api PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
endif()
# Here the shared library doesn't depend on other fluid libraries, or double free will occur.
cc_library(paddle_inference_api_shared SHARED
SRCS paddle_inference_api.cc paddle_inference_api_impl.cc)
SRCS api.cc api_impl.cc)
add_dependencies(paddle_inference_api_shared ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
set_target_properties(paddle_inference_api_shared PROPERTIES OUTPUT_NAME paddle_inference_api)
if(NOT APPLE)
set(LINK_FLAGS "-Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/paddle_inference_api.map")
set(LINK_FLAGS "-Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/api.map")
set_target_properties(paddle_inference_api_shared PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
FILE(WRITE ${CMAKE_CURRENT_BINARY_DIR}/check_symbol.cmake
"execute_process(COMMAND bash -c \"${CMAKE_CURRENT_SOURCE_DIR}/check_symbol.sh"
......@@ -73,32 +73,32 @@ if(NOT APPLE)
endif()
cc_test(test_paddle_inference_api
SRCS test_paddle_inference_api.cc
SRCS test_api.cc
DEPS paddle_inference_api)
inference_api_test(test_paddle_inference_api_impl
inference_api_test(test_api_impl
ARGS test_word2vec test_image_classification)
if(WITH_GPU AND TENSORRT_FOUND)
cc_library(paddle_inference_tensorrt_subgraph_engine
SRCS paddle_inference_api_tensorrt_subgraph_engine.cc
DEPS paddle_inference_api analysis tensorrt_engine paddle_inference_api paddle_fluid_api)
SRCS api_tensorrt_subgraph_engine.cc
DEPS paddle_inference_api analysis tensorrt_engine paddle_fluid_api)
inference_api_test(test_paddle_inference_api_tensorrt_subgraph_engine ARGS test_word2vec)
inference_api_test(test_api_tensorrt_subgraph_engine ARGS test_word2vec)
endif()
if (WITH_ANAKIN) # only needed in CI
# Due to Anakin do not have official library releases and the versions of protobuf and cuda do not match Paddle's,
# so anakin library will not be merged to our official inference library. To use anakin prediction API, one need to
# compile the libinference_anakin_api.a and compile with anakin.so.
nv_library(inference_anakin_api SRCS paddle_inference_api.cc paddle_inference_api_anakin_engine.cc)
nv_library(inference_anakin_api_shared SHARED SRCS paddle_inference_api.cc paddle_inference_api_anakin_engine.cc)
nv_library(inference_anakin_api SRCS api.cc api_anakin_engine.cc)
nv_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc)
target_compile_options(inference_anakin_api BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
target_compile_options(inference_anakin_api_shared BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
target_link_libraries(inference_anakin_api anakin anakin_saber_common)
target_link_libraries(inference_anakin_api_shared anakin anakin_saber_common)
if (WITH_TESTING)
cc_test(inference_anakin_test SRCS paddle_inference_api_anakin_engine_tester.cc
cc_test(inference_anakin_test SRCS api_anakin_engine_tester.cc
ARGS --model=${ANAKIN_INSTALL_DIR}/mobilenet_v2.anakin.bin
DEPS inference_anakin_api)
target_compile_options(inference_anakin_test BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
......
......@@ -12,7 +12,7 @@ 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/contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle {
......
......@@ -12,8 +12,9 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/contrib/inference/paddle_inference_api_anakin_engine.h"
#include "paddle/fluid/inference/api/api_anakin_engine.h"
#include <cuda.h>
#include <vector>
namespace paddle {
......@@ -47,8 +48,7 @@ bool PaddleInferenceAnakinPredictor::Run(
}
auto d_tensor_in_p = executor_.get_in(input.name);
float *d_data_p = d_tensor_in_p->mutable_data();
if (cudaMemcpy(d_data_p,
static_cast<float *>(input.data.data()),
if (cudaMemcpy(d_data_p, static_cast<float *>(input.data.data()),
d_tensor_in_p->valid_size() * sizeof(float),
cudaMemcpyHostToDevice) != 0) {
LOG(ERROR) << "copy data from CPU to GPU error";
......@@ -70,8 +70,7 @@ bool PaddleInferenceAnakinPredictor::Run(
output.data.Resize(tensor->valid_size() * sizeof(float));
}
// Copy data from GPU -> CPU
if (cudaMemcpy(output.data.data(),
tensor->mutable_data(),
if (cudaMemcpy(output.data.data(), tensor->mutable_data(),
tensor->valid_size() * sizeof(float),
cudaMemcpyDeviceToHost) != 0) {
LOG(ERROR) << "copy data from GPU to CPU error";
......@@ -106,13 +105,12 @@ std::unique_ptr<PaddlePredictor> PaddleInferenceAnakinPredictor::Clone() {
// A factory to help create difference predictor.
template <>
std::unique_ptr<PaddlePredictor>
CreatePaddlePredictor<AnakinConfig, PaddleEngineKind::kAnakin>(
const AnakinConfig &config) {
std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
AnakinConfig, PaddleEngineKind::kAnakin>(const AnakinConfig &config) {
VLOG(3) << "Anakin Predictor create.";
std::unique_ptr<PaddlePredictor> x(
new PaddleInferenceAnakinPredictor(config));
return x;
};
}
} // namespace paddle
......@@ -19,7 +19,8 @@ limitations under the License. */
#pragma once
#include "paddle/contrib/inference/paddle_inference_api.h"
#include <vector>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
// from anakin
#include "framework/core/net/net.h"
......@@ -31,7 +32,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
public:
PaddleInferenceAnakinPredictor() {}
PaddleInferenceAnakinPredictor(const AnakinConfig& config);
explicit PaddleInferenceAnakinPredictor(const AnakinConfig& config);
// NOTE Unlike the native engine, the buffers of anakin engine's output_data
// should be allocated first.
......@@ -48,8 +49,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
private:
bool Init(const AnakinConfig& config);
anakin::graph::Graph<anakin::NV,
anakin::saber::AK_FLOAT,
anakin::graph::Graph<anakin::NV, anakin::saber::AK_FLOAT,
anakin::Precision::FP32>
graph_;
anakin::Net<anakin::NV, anakin::saber::AK_FLOAT, anakin::Precision::FP32>
......
......@@ -16,7 +16,7 @@ limitations under the License. */
#include <glog/logging.h>
#include <gtest/gtest.h>
#include "paddle/contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
DEFINE_string(model, "", "Directory of the inference model.");
......
......@@ -21,7 +21,7 @@ limitations under the License. */
#include <utility>
#include <vector>
#include "paddle/contrib/inference/paddle_inference_api_impl.h"
#include "paddle/fluid/inference/api/api_impl.h"
namespace paddle {
namespace {
......@@ -77,8 +77,8 @@ bool NativePaddlePredictor::Init(
if (!config_.model_dir.empty()) {
// Parameters are saved in separate files sited in
// the specified `dirname`.
inference_program_ = paddle::inference::Load(
executor_.get(), scope_.get(), config_.model_dir);
inference_program_ = paddle::inference::Load(executor_.get(), scope_.get(),
config_.model_dir);
} else if (!config_.prog_file.empty() && !config_.param_file.empty()) {
// All parameters are saved in a single file.
// The file names should be consistent with that used
......@@ -91,8 +91,8 @@ bool NativePaddlePredictor::Init(
}
ctx_ = executor_->Prepare(*inference_program_, 0);
executor_->CreateVariables(
*inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0);
executor_->CreateVariables(*inference_program_,
sub_scope_ ? sub_scope_ : scope_.get(), 0);
// Get the feed_target_names and fetch_target_names
feed_target_names_ = inference_program_->GetFeedTargetNames();
......@@ -105,7 +105,7 @@ NativePaddlePredictor::~NativePaddlePredictor() {
PADDLE_ENFORCE_NOT_NULL(scope_, "Should have parent scope!");
scope_->DeleteScope(sub_scope_);
}
};
}
bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
std::vector<PaddleTensor> *output_data) {
......@@ -134,10 +134,8 @@ bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
// if share variables, we need not create variables
VLOG(4) << "Run prepared context";
executor_->RunPreparedContext(
ctx_.get(),
sub_scope_ != nullptr ? sub_scope_ : scope_.get(),
&feed_targets,
&fetch_targets,
ctx_.get(), sub_scope_ != nullptr ? sub_scope_ : scope_.get(),
&feed_targets, &fetch_targets,
false /* don't create variable eatch time */);
VLOG(4) << "Finish prepared context";
if (!GetFetch(fetchs, output_data)) {
......@@ -181,8 +179,7 @@ bool NativePaddlePredictor::SetFeed(const std::vector<PaddleTensor> &inputs,
}
// TODO(panyx0718): Init LoDTensor from existing memcpy to save a copy.
std::memcpy(static_cast<void *>(input_ptr),
inputs[i].data.data(),
std::memcpy(static_cast<void *>(input_ptr), inputs[i].data.data(),
inputs[i].data.length());
feeds->push_back(input);
}
......@@ -232,8 +229,7 @@ bool NativePaddlePredictor::GetFetch(
size_t start = lod[0][j - 1] * common_dim;
size_t end = lod[0][j] * common_dim;
if (end > start) {
std::copy(output_ptr + start,
output_ptr + end,
std::copy(output_ptr + start, output_ptr + end,
data.begin() + (j - 1) * max_dim * common_dim);
}
}
......@@ -257,15 +253,13 @@ bool NativePaddlePredictor::GetFetch(
}
template <>
std::unique_ptr<PaddlePredictor>
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(
const NativeConfig &config) {
std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
NativeConfig, PaddleEngineKind::kNative>(const NativeConfig &config) {
VLOG(3) << "create NativePaddlePredictor";
if (config.use_gpu) {
// 1. GPU memeroy
PADDLE_ENFORCE_GT(
config.fraction_of_gpu_memory,
0.f,
config.fraction_of_gpu_memory, 0.f,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]");
PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
std::vector<std::string> flags;
......
......@@ -19,7 +19,7 @@
#include <string>
#include <vector>
#include "paddle/contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/framework/lod_tensor.h"
......
......@@ -12,9 +12,9 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/contrib/inference/paddle_inference_api.h"
#include "paddle/contrib/inference/paddle_inference_api_impl.h"
#include "paddle/fluid/inference/analysis/analyzer.h"
#include "paddle/fluid/inference/api/api_impl.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/utils/singleton.h"
namespace paddle {
......@@ -77,8 +77,8 @@ class TensorRTSubgraphPredictor : public NativePaddlePredictor {
ctx_ = executor_->Prepare(*inference_program_, 0);
VLOG(5) << "to create variables";
executor_->CreateVariables(
*inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0);
executor_->CreateVariables(*inference_program_,
sub_scope_ ? sub_scope_ : scope_.get(), 0);
// Get the feed_target_names and fetch_target_names
feed_target_names_ = inference_program_->GetFeedTargetNames();
......@@ -98,8 +98,7 @@ CreatePaddlePredictor<TensorRTConfig, PaddleEngineKind::kAutoMixedTensorRT>(
if (config.use_gpu) {
// 1. GPU memeroy
PADDLE_ENFORCE_GT(
config.fraction_of_gpu_memory,
0.f,
config.fraction_of_gpu_memory, 0.f,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]");
PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
std::vector<std::string> flags;
......
......@@ -55,11 +55,11 @@ endif()
# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
if(WITH_STATIC_LIB)
set(DEPS
${PADDLE_LIB}/contrib/inference/libpaddle_inference_api.a
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_inference_api.a
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.a)
else()
set(DEPS
${PADDLE_LIB}/contrib/inference/libpaddle_inference_api.so
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_inference_api.so
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.so)
endif()
set(EXTERNAL_LIB "-lrt -ldl -lpthread")
......
......@@ -64,7 +64,7 @@ for WITH_STATIC_LIB in ON OFF; do
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=$WITH_STATIC_LIB
make -j
for use_gpu in false; do
for use_gpu in $use_gpu_list; do
for vis_demo_name in $vis_demo_list; do
./vis_demo \
--modeldir=../data/$vis_demo_name/model \
......
......@@ -19,8 +19,8 @@ limitations under the License. */
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <memory>
#include <thread>
#include "contrib/inference/paddle_inference_api.h"
#include <thread> //NOLINT
#include "paddle/fluid/inference/paddle_inference_api.h"
#include "paddle/fluid/platform/enforce.h"
DEFINE_string(dirname, "", "Directory of the inference model.");
......@@ -63,8 +63,8 @@ void Main(bool use_gpu) {
PADDLE_ENFORCE(outputs.size(), 1UL);
// Check the output buffer size and result of each tid.
PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
float result[5] = {
0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706};
float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
0.000932706};
const size_t num_elements = outputs.front().data.length() / sizeof(float);
// The outputs' buffers are in CPU memory.
for (size_t i = 0; i < std::min(5UL, num_elements); i++) {
......@@ -107,8 +107,8 @@ void MainThreads(int num_threads, bool use_gpu) {
PADDLE_ENFORCE(outputs.size(), 1UL);
// Check the output buffer size and result of each tid.
PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
float result[5] = {
0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706};
float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
0.000932706};
const size_t num_elements =
outputs.front().data.length() / sizeof(float);
// The outputs' buffers are in CPU memory.
......
......@@ -13,16 +13,15 @@
// limitations under the License.
#pragma once
#include <algorithm>
#include <string>
#include <vector>
#include "contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/inference/paddle_inference_api.h"
namespace paddle {
namespace demo {
static void split(const std::string& str,
char sep,
static void split(const std::string& str, char sep,
std::vector<std::string>* pieces) {
pieces->clear();
if (str.empty()) {
......
......@@ -29,8 +29,7 @@ DECLARE_double(fraction_of_gpu_memory_to_use);
DEFINE_string(modeldir, "", "Directory of the inference model.");
DEFINE_string(refer, "", "path to reference result for comparison.");
DEFINE_string(
data,
"",
data, "",
"path of data; each line is a record, format is "
"'<space splitted floats as data>\t<space splitted ints as shape'");
DEFINE_bool(use_gpu, false, "Whether use gpu.");
......
......@@ -12,10 +12,9 @@ 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/contrib/inference/paddle_inference_api.h"
#include <glog/logging.h>
#include <gtest/gtest.h>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle {
......
......@@ -15,10 +15,10 @@ limitations under the License. */
#include <glog/logging.h>
#include <gtest/gtest.h>
#include <thread>
#include <thread> // NOLINT
#include "gflags/gflags.h"
#include "paddle/contrib/inference/paddle_inference_api_impl.h"
#include "paddle/fluid/inference/api/api_impl.h"
#include "paddle/fluid/inference/tests/test_helper.h"
DEFINE_string(dirname, "", "Directory of the inference model.");
......@@ -121,8 +121,8 @@ void MainImageClassification(bool use_gpu) {
// which should be in the range [0.0, 1.0].
feed_target_shapes[0][0] = batch_size;
framework::DDim input_dims = framework::make_ddim(feed_target_shapes[0]);
SetupTensor<float>(
&input, input_dims, static_cast<float>(0), static_cast<float>(1));
SetupTensor<float>(&input, input_dims, static_cast<float>(0),
static_cast<float>(1));
std::vector<framework::LoDTensor*> cpu_feeds;
cpu_feeds.push_back(&input);
......
......@@ -15,7 +15,7 @@
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <gtest/gtest.h>
#include "paddle/contrib/inference/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle {
......@@ -61,4 +61,4 @@ void Main(bool use_gpu) {
TEST(paddle_inference_api_tensorrt_subgraph_engine, main) { Main(true); }
} // namespace paddle
\ No newline at end of file
} // namespace paddle
......@@ -33,22 +33,14 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(in_dim.size(), 4,
"Input(X) format must be 4D tensor, eg., NCHW.");
int batch_size = in_dim[0];
int img_channels = in_dim[1];
int img_height = in_dim[2];
int img_width = in_dim[3];
auto kernels = ctx->Attrs().Get<std::vector<int>>("kernels");
auto strides = ctx->Attrs().Get<std::vector<int>>("strides");
auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[1]);
ctx->SetOutputDim("Out", {batch_size * output_height * output_width,
img_channels * kernels[0] * kernels[1]});
ctx->SetOutputDim("Out",
{in_dim[0], img_channels * kernels[0] * kernels[1]});
}
};
......
......@@ -109,12 +109,13 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
}
out->set_lod(lod);
} else {
out->mutable_data<T>(ctx.GetPlace());
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[1]);
out->mutable_data<T>({batch_size * output_height * output_width,
img_channels * kernels[0] * kernels[1]},
ctx.GetPlace());
const std::vector<int> dilations({1, 1});
auto out_dims = out->dims();
out->Resize({batch_size, out->numel() / batch_size});
......
......@@ -88,7 +88,7 @@ class SumMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
input_format = memory::format::nc;
}
for (int i = in_place ? 1 : 0; i < N; i++) {
for (int i = 0; i < N; i++) {
PADDLE_ENFORCE(in_vars[i]->IsType<LoDTensor>(),
"all inputs must be all LoDTensors");
auto& input = in_vars[i]->Get<LoDTensor>();
......
......@@ -19,6 +19,8 @@
# Utils
#=================================================
set -ex
function print_usage() {
echo -e "\n${RED}Usage${NONE}:
${BOLD}${SCRIPT_NAME}${NONE} [OPTION]"
......@@ -37,6 +39,7 @@ function print_usage() {
${BLUE}fluid_inference_lib${NONE}: deploy fluid inference library
${BLUE}check_style${NONE}: run code style check
${BLUE}cicheck${NONE}: run CI tasks
${BLUE}assert_api_not_changed${NONE}: check api compability
"
}
......@@ -326,11 +329,22 @@ function assert_api_not_changed() {
virtualenv .env
source .env/bin/activate
pip install ${PADDLE_ROOT}/build/python/dist/*whl
curl ${PADDLE_API_SPEC_URL:-https://raw.githubusercontent.com/PaddlePaddle/FluidAPISpec/master/API.spec} \
> origin.spec
python ${PADDLE_ROOT}/tools/print_signatures.py paddle.fluid > new.spec
python ${PADDLE_ROOT}/tools/diff_api.py origin.spec new.spec
python ${PADDLE_ROOT}/tools/diff_api.py ${PADDLE_ROOT}/paddle/fluid/API.spec new.spec
deactivate
API_CHANGE=`git diff --name-only HEAD^ | grep "paddle/fluid/API.spec" || true`
echo "checking API.spec change, PR: ${GIT_PR_ID}, changes: ${API_CHANGE}"
if [ ${API_CHANGE} ] && [ "${GIT_PR_ID}" != "" ]; then
# TODO: curl -H 'Authorization: token ${TOKEN}'
APPROVALS=`curl -H "Authorization: token ${GITHUB_API_TOKEN}" https://api.github.com/repos/PaddlePaddle/Paddle/pulls/${GIT_PR_ID}/reviews | \
python ${PADDLE_ROOT}/tools/check_pr_approval.py 2 7845005 2887803 728699 13348433`
echo "current pr ${GIT_PR_ID} got approvals: ${APPROVALS}"
if [ "${APPROVALS}" == "FALSE" ]; then
echo "You must have at least 2 approvals for the api change!"
exit 1
fi
fi
}
......@@ -531,13 +545,12 @@ function test_fluid_inference_lib() {
Testing fluid inference library ...
========================================
EOF
cd ${PADDLE_ROOT}/paddle/contrib/inference/demo_ci
cd ${PADDLE_ROOT}/paddle/fluid/inference/api/demo_ci
./run.sh ${PADDLE_ROOT} ${WITH_MKL:-ON} ${WITH_GPU:-OFF}
fi
}
function main() {
set -e
local CMD=$1
init
case $CMD in
......
......@@ -22,8 +22,7 @@ from ..executor import global_scope
from layer_function_generator import generate_layer_fn, templatedoc
__all__ = [
'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'Recv',
'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
'data', 'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
'double_buffer', 'random_data_generator', 'py_reader', 'Preprocessor',
'load'
]
......@@ -802,7 +801,7 @@ class Preprocessor(object):
self.sink_var_names = None
self.status = Preprocessor.BEFORE_SUB_BLOCK
def is_completed(self):
def _is_completed(self):
return self.sub_block and self.source_var_names and self.sink_var_names
@contextlib.contextmanager
......@@ -812,7 +811,7 @@ class Preprocessor(object):
yield
self.main_prog.rollback()
self.status = Preprocessor.AFTER_SUB_BLOCK
if not self.is_completed():
if not self._is_completed():
raise RuntimeError(
"The definition of preprocessor is incompleted! "
"Please make sure that you have set input and output "
......
......@@ -1180,16 +1180,16 @@ class ModelAverage(Optimizer):
self._add_average_restore_op(block, param_grad)
def _add_average_apply_op(self, block, param_grad):
param = block.clone_variable(param_grad[0])
grad = block.clone_variable(param_grad[1])
sum_1 = block.clone_variable(self._get_accumulator('sum_1', param))
sum_2 = block.clone_variable(self._get_accumulator('sum_2', param))
sum_3 = block.clone_variable(self._get_accumulator('sum_3', param))
num_accumulates = block.clone_variable(
param = block._clone_variable(param_grad[0])
grad = block._clone_variable(param_grad[1])
sum_1 = block._clone_variable(self._get_accumulator('sum_1', param))
sum_2 = block._clone_variable(self._get_accumulator('sum_2', param))
sum_3 = block._clone_variable(self._get_accumulator('sum_3', param))
num_accumulates = block._clone_variable(
self._get_accumulator('num_accumulates', param))
old_num_accumulates = block.clone_variable(
old_num_accumulates = block._clone_variable(
self._get_accumulator('old_num_accumulates', param))
num_updates = block.clone_variable(
num_updates = block._clone_variable(
self._get_accumulator('num_updates', param))
# backup param value to grad
layers.assign(input=param, output=grad)
......@@ -1203,8 +1203,8 @@ class ModelAverage(Optimizer):
layers.elementwise_div(x=sum, y=tmp, out=param)
def _add_average_restore_op(self, block, param_grad):
param = block.clone_variable(param_grad[0])
grad = block.clone_variable(param_grad[1])
param = block._clone_variable(param_grad[0])
grad = block._clone_variable(param_grad[1])
layers.assign(input=grad, output=param)
def _append_average_accumulate_op(self, param):
......
......@@ -22,6 +22,9 @@ import numpy
import paddle.fluid as fluid
import paddle.fluid.layers as layers
from paddle.fluid.layers.io import ListenAndServ
from paddle.fluid.layers.io import Recv
from paddle.fluid.layers.io import Send
class TestSendOp(unittest.TestCase):
......@@ -65,8 +68,7 @@ class TestSendOp(unittest.TestCase):
main = fluid.Program()
with fluid.program_guard(main):
serv = layers.ListenAndServ(
"127.0.0.1:0", ["X"], optimizer_mode=False)
serv = ListenAndServ("127.0.0.1:0", ["X"], optimizer_mode=False)
with serv.do():
out_var = main.global_block().create_var(
name="scale_0.tmp_0",
......@@ -99,8 +101,8 @@ class TestSendOp(unittest.TestCase):
persistable=False,
shape=[32, 32])
fluid.initializer.Constant(value=2.3)(get_var, main.global_block())
layers.Send("127.0.0.1:%d" % port, [x])
o = layers.Recv("127.0.0.1:%d" % port, [get_var])
Send("127.0.0.1:%d" % port, [x])
o = Recv("127.0.0.1:%d" % port, [get_var])
exe = fluid.Executor(place)
self.dist_out = exe.run(main, fetch_list=o) # o is a list
......
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
# 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
# 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.
#
add_subdirectory(inference)
from __future__ import print_function
import sys
import json
def check_approval(count, required_reviewers):
json_buff = ""
for line in sys.stdin:
json_buff = "".join([json_buff, line])
json_resp = json.loads(json_buff)
approves = 0
approved_user_ids = []
for review in json_resp:
if review["state"] == "APPROVED":
approves += 1
approved_user_ids.append(review["user"]["id"])
# convert to int
required_reviewers_int = set()
for rr in required_reviewers:
required_reviewers_int.add(int(rr))
if len(set(approved_user_ids) & required_reviewers_int) >= count:
print("TRUE")
else:
print("FALSE")
if __name__ == "__main__":
if len(sys.argv) > 1 and sys.argv[1].isdigit():
check_approval(int(sys.argv[1]), sys.argv[2:])
else:
print(
"Usage: python check_pr_approval.py [count] [required reviewer id] ..."
)
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