提交 597d9217 编写于 作者: D dzhwinter

clean demo_ci

上级 dbd0075b
......@@ -12,6 +12,8 @@ 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 <algorithm>
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/framework/channel.h"
......@@ -384,6 +386,7 @@ void Executor::RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
CreateVariables(ctx->prog_, local_scope, ctx->block_id_);
}
VLOG(3) << "Scope ptr " << local_scope;
for (auto& op : ctx->ops_) {
op->Run(*local_scope, place_);
// CheckResult(op->Type(), ctx, local_scope);
......@@ -445,8 +448,12 @@ void Executor::RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
VLOG(3) << "after tensor copy";
float sum = .0;
for(size_t i=0; i < check.numel(); ++i) {
if(std::type_index(check.type()) == std::type_index(typeid(int64_t))) {
sum += static_cast<float>(check.data<int64_t>()[i]);
} else {
sum += check.data<float>()[i];
}
}
VLOG(3) << "op " << op->Type() << " output var " << var_name << " sum " << sum;
}
}
......
......@@ -62,7 +62,7 @@ static DDim GetDims(const Scope& scope, const std::string& name,
if (var->IsType<LoDTensor>()) {
const LoDTensor& tensor = var->Get<LoDTensor>();
if (UNLIKELY(!tensor.IsInitialized())) {
if (!tensor.IsInitialized()) {
return DDim({-1});
}
return tensor.dims();
......@@ -91,13 +91,13 @@ static std::string GetDtype(const Scope& scope, const std::string& name) {
if (var->IsType<LoDTensor>()) {
const LoDTensor& tensor = var->Get<LoDTensor>();
if (UNLIKELY(!tensor.IsInitialized())) {
if (!tensor.IsInitialized()) {
return "";
}
return DataTypeToString(ToDataType(tensor.type()));
} else if (var->IsType<SelectedRows>()) {
auto tensor = var->Get<SelectedRows>().value();
if (UNLIKELY(!tensor.IsInitialized())) {
if (!tensor.IsInitialized()) {
return "uninited";
} else {
return DataTypeToString(ToDataType(tensor.type()));
......@@ -130,7 +130,7 @@ static LoD GetLoD(const Scope& scope, const std::string& name) {
if (var->IsType<LoDTensor>()) {
const LoDTensor& tensor = var->Get<LoDTensor>();
if (UNLIKELY(!tensor.IsInitialized())) {
if (!tensor.IsInitialized()) {
return default_lod;
}
return tensor.lod();
......@@ -206,6 +206,7 @@ const std::vector<std::string>& OperatorBase::Outputs(
}
std::string OperatorBase::DebugStringEx(const Scope* scope) const {
VLOG(3) << this->Type() << " scope ptr " << scope;
std::stringstream ss;
ss << "Op(" << type_ << "), inputs:{";
for (auto it = inputs_.begin(); it != inputs_.end();) {
......
......@@ -73,10 +73,11 @@ link_directories("${PADDLE_LIB}/paddle/fluid/inference")
# add_executable(${DEMO_NAME} ${DEMO_NAME}.cc)
# add_library(${DEMO_NAME} ${DEMO_NAME}.cc)
add_library(${DEMO_NAME} SHARED ${DEMO_NAME}.cc)
add_executable(real_data_icnet_tester real_data_icnet_tester.cc)
add_executable(test test.cc)
add_executable(thread_icnet_test thread_icnet_test.cc)
# add_library(${DEMO_NAME} SHARED ${DEMO_NAME}.cc)
# add_executable(test test.cc)
# add_executable(thread_icnet_test thread_icnet_test.cc)
if(WITH_MKL)
include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
......@@ -94,11 +95,7 @@ endif()
# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
if(WITH_STATIC_LIB)
set(DEPS
# ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}
D:/Paddle/bazel-dll/fluid_install_dir/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}
# E:/Paddle/build/paddle/fluid/inference/api/Release/libpaddle_inference_api${CMAKE_STATIC_LIBRARY_SUFFIX}
D:/Paddle/bazel-dll/paddle/fluid/inference/api/Release/libpaddle_inference_api${CMAKE_STATIC_LIBRARY_SUFFIX}
)
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
else()
set(DEPS
${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
......@@ -129,10 +126,10 @@ if(WITH_GPU)
endif()
endif()
target_link_libraries(${DEMO_NAME} ${DEPS})
target_link_libraries(test ${DEMO_NAME} )
target_link_libraries(thread_icnet_test ${DEPS})
target_link_libraries(real_data_icnet_tester ${DEPS})
target_compile_definitions(${DEMO_NAME} PRIVATE "API_DEFINITION")
# target_link_libraries(${DEMO_NAME} ${DEPS})
# target_link_libraries(test ${DEMO_NAME} )
# target_link_libraries(thread_icnet_test ${DEPS})
# target_compile_definitions(${DEMO_NAME} PRIVATE "API_DEFINITION")
......@@ -19,6 +19,7 @@
#include <iostream>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle {
// DEFINE_string(dirname, "./lb",
......@@ -27,8 +28,8 @@ namespace paddle {
NativeConfig GetConfig() {
NativeConfig config;
// config.model_dir = FLAGS_dirname;
config.prog_file= "lb/__model__";
config.param_file= "lb/__params__";
config.prog_file= "hs_lb_without_bn/__model__";
config.param_file= "hs_lb_without_bn/__params__";
config.fraction_of_gpu_memory = 0.8;
config.use_gpu = true;
config.device = 0;
......@@ -44,6 +45,7 @@ double time_diff(Time t1, Time t2) {
return counter.count() / 1000.0;
}
void test_naive(int batch_size){
NativeConfig config = GetConfig();
auto predictor = CreatePaddlePredictor<NativeConfig>(config);
......@@ -88,11 +90,10 @@ void test_naive(int batch_size){
PaddleTensor tensor_out;
std::vector<PaddleTensor> outputs(1, tensor_out);
predictor->Run(paddle_tensor_feeds, &outputs, batch_size);
// predictor->Run(paddle_tensor_feeds, &outputs, batch_size);
std::cout << "start predict123:" << std::endl;
auto time1 = time();
for(size_t i = 0; i < 1; i++) {
predictor->Run(paddle_tensor_feeds, &outputs, batch_size);
}
......
......@@ -42,6 +42,8 @@ class FetchOp : public framework::OperatorBase {
"Cannot find out_var in scope, out_var_name is %s",
out_name);
VLOG(3) << "fetch_var ptr " << fetch_var << " is " << (fetch_var == nullptr);
VLOG(3) << "out_var ptr " << out_var << " is " << (out_var == nullptr);
auto col = static_cast<size_t>(Attr<int>("col"));
auto *fetch_list = out_var->GetMutable<framework::FeedFetchList>();
......
......@@ -67,8 +67,12 @@ class LoadCombineOp : public framework::OperatorBase {
framework::TensorCopy(*tensor, platform::CPUPlace(), dev_ctx, &check);
float sum = .0;
for(size_t i=0; i < check.numel(); ++i) {
if(std::type_index(check.type()) == std::type_index(typeid(int64_t))) {
sum += static_cast<float>(check.data<int64_t>()[i]);
} else {
sum += check.data<float>()[i];
}
}
VLOG(3) << "sum result" << sum;
auto in_dtype = framework::ToDataType(tensor->type());
auto out_dtype =
......
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