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未验证 提交 4f9d6529 编写于 作者: C Chen Weihang 提交者： GitHub
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Polish framework error message part 7 (#27266) 

* polish framework error message part 7

* fix typo

* polish by reviewes comment
上级 950301bf
隐藏空白更改
内联 并排
Showing with 167 addition and 99 deletion
paddle/fluid/framework/reader.cc
浏览文件 @ 4f9d6529
...@@ -20,7 +20,10 @@ namespace framework { ...@@ -20,7 +20,10 @@ namespace framework {
void ReaderBase::ReadNext(std::vector<LoDTensor> *out) { void ReaderBase::ReadNext(std::vector<LoDTensor> *out) {
std::lock_guard<std::mutex> lock(mu_); std::lock_guard<std::mutex> lock(mu_);
PADDLE_ENFORCE_EQ(status_, ReaderStatus::kRunning); PADDLE_ENFORCE_EQ(status_, ReaderStatus::kRunning,
platform::errors::Unavailable(
"The current reader has stopped running and cannot "
"continue to read the next batch of data."));
ReadNextImpl(out); ReadNextImpl(out);
} }
......
paddle/fluid/framework/rw_lock.h
浏览文件 @ 4f9d6529
...@@ -32,17 +32,21 @@ struct RWLock { ...@@ -32,17 +32,21 @@ struct RWLock {
~RWLock() { pthread_rwlock_destroy(&lock_); } ~RWLock() { pthread_rwlock_destroy(&lock_); }
inline void RDLock() { inline void RDLock() {
PADDLE_ENFORCE_EQ(pthread_rwlock_rdlock(&lock_), 0, PADDLE_ENFORCE_EQ(
"acquire read lock failed"); pthread_rwlock_rdlock(&lock_), 0,
platform::errors::External("The pthread failed to acquire read lock."));
} }
inline void WRLock() { inline void WRLock() {
PADDLE_ENFORCE_EQ(pthread_rwlock_wrlock(&lock_), 0, PADDLE_ENFORCE_EQ(pthread_rwlock_wrlock(&lock_), 0,
"acquire write lock failed"); platform::errors::External(
"The pthread failed to acquire write lock."));
} }
inline void UNLock() { inline void UNLock() {
PADDLE_ENFORCE_EQ(pthread_rwlock_unlock(&lock_), 0, "unlock failed"); PADDLE_ENFORCE_EQ(
pthread_rwlock_unlock(&lock_), 0,
platform::errors::External("The pthread failed to unlock."));
} }
private: private:
......
paddle/fluid/framework/save_load_util.cc
浏览文件 @ 4f9d6529
...@@ -33,7 +33,8 @@ void CheckInStreamState(std::istream& istre, size_t length) { ...@@ -33,7 +33,8 @@ void CheckInStreamState(std::istream& istre, size_t length) {
VLOG(5) << "Can't read [" << length << "] from file" VLOG(5) << "Can't read [" << length << "] from file"
<< "file seems breakem"; << "file seems breakem";
PADDLE_THROW("Model load error, file seems breaken"); PADDLE_THROW(platform::errors::Unavailable(
"Model load failed, istream state error."));
} }
} }
...@@ -58,10 +59,11 @@ size_t ReadTensorNumber(std::istream& istre) { ...@@ -58,10 +59,11 @@ size_t ReadTensorNumber(std::istream& istre) {
sizeof(char) * tensor_number_mark.size()); sizeof(char) * tensor_number_mark.size());
std::string str_read_tensor_number_mark(tensor_number_mark_buffer, std::string str_read_tensor_number_mark(tensor_number_mark_buffer,
tensor_number_mark.size()); tensor_number_mark.size());
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(tensor_number_mark, str_read_tensor_number_mark,
tensor_number_mark, str_read_tensor_number_mark, platform::errors::InvalidArgument(
"Tensor number mark not match, expect [%s], but read from file is [%]", "Tensor number mark does not match, expect mark is "
tensor_number_mark, str_read_tensor_number_mark); "[%s], but the mark read from file is [%s].",
tensor_number_mark, str_read_tensor_number_mark));
size_t tensor_number = 0; size_t tensor_number = 0;
istre.read(reinterpret_cast<char*>(&tensor_number), sizeof(tensor_number)); istre.read(reinterpret_cast<char*>(&tensor_number), sizeof(tensor_number));
...@@ -79,10 +81,11 @@ std::string ReadTensorName(std::istream& istre) { ...@@ -79,10 +81,11 @@ std::string ReadTensorName(std::istream& istre) {
std::string str_read_tensor_name_mark(name_mark_buffer, std::string str_read_tensor_name_mark(name_mark_buffer,
tensor_name_mark.size()); tensor_name_mark.size());
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(tensor_name_mark, str_read_tensor_name_mark,
tensor_name_mark, str_read_tensor_name_mark, platform::errors::InvalidArgument(
"Tensor name mark not match, expect [%s], but read from file is [%]", "Tensor name mark does not match, expect mark is [%s], "
tensor_name_mark, str_read_tensor_name_mark); "but the mark read from file is [%s].",
tensor_name_mark, str_read_tensor_name_mark));
size_t tensor_name_length = 0; size_t tensor_name_length = 0;
istre.read(reinterpret_cast<char*>(&tensor_name_length), istre.read(reinterpret_cast<char*>(&tensor_name_length),
...@@ -117,16 +120,18 @@ bool SaveStaticNameListToDisk( ...@@ -117,16 +120,18 @@ bool SaveStaticNameListToDisk(
for (size_t i = 0; i < vec_tensor_name_list.size(); ++i) { for (size_t i = 0; i < vec_tensor_name_list.size(); ++i) {
auto var_ptr = scope.FindVar(vec_tensor_name_list[i]); auto var_ptr = scope.FindVar(vec_tensor_name_list[i]);
PADDLE_ENFORCE_NE( PADDLE_ENFORCE_NOT_NULL(
var_ptr, nullptr, var_ptr, platform::errors::NotFound("Variable (%s) is not found when "
"Variable find error, when save model, can't not find vairable [%s], " "saving model, please make sure "
"Please make sure you have run StartUpProgram", "that exe.run(startup_program) has "
vec_tensor_name_list[i]); "been executed.",
vec_tensor_name_list[i]));
Tensor* tensor = var_ptr->GetMutable<LoDTensor>(); Tensor* tensor = var_ptr->GetMutable<LoDTensor>();
PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true, PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true,
"Paramter [%s] not initialzed," platform::errors::PreconditionNotMet(
"Please make sure you have run StartUpProgram", "Paramter [%s] is not initialzed, please make sure "
vec_tensor_name_list[i]); "that exe.run(startup_program) has been executed.",
vec_tensor_name_list[i]));
map_tensor[vec_tensor_name_list[i]] = tensor; map_tensor[vec_tensor_name_list[i]] = tensor;
} }
...@@ -145,9 +150,10 @@ bool SaveDygraphVarBaseListToDisk( ...@@ -145,9 +150,10 @@ bool SaveDygraphVarBaseListToDisk(
Tensor* tensor = var_ptr->GetMutable<LoDTensor>(); Tensor* tensor = var_ptr->GetMutable<LoDTensor>();
PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true, PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true,
"Paramter [%s] not initialzed," platform::errors::PreconditionNotMet(
"Please make sure you have run StartUpProgram", "Paramter [%s] is not initialzed, please make sure "
vec_var_base_list[i]->Name()); "that exe.run(startup_program) has been executed.",
vec_var_base_list[i]->Name()));
map_tensor[vec_var_base_list[i]->Name()] = tensor; map_tensor[vec_var_base_list[i]->Name()] = tensor;
} }
...@@ -185,34 +191,41 @@ bool LoadStaticNameListFromDisk( ...@@ -185,34 +191,41 @@ bool LoadStaticNameListFromDisk(
for (size_t i = 0; i < vec_tensor_name_list.size(); ++i) { for (size_t i = 0; i < vec_tensor_name_list.size(); ++i) {
auto it = map_load_tensor.find(vec_tensor_name_list[i]); auto it = map_load_tensor.find(vec_tensor_name_list[i]);
PADDLE_ENFORCE(it != map_load_tensor.end(), PADDLE_ENFORCE_NE(it, map_load_tensor.end(),
"Paramete not found in Model file, " platform::errors::NotFound(
"Can not find [%s] in model file [%s]", "Parameter (%s) not found in model file (%s).",
vec_tensor_name_list[i], file_name); vec_tensor_name_list[i], file_name));
auto var_ptr = scope.FindVar(vec_tensor_name_list[i]); auto var_ptr = scope.FindVar(vec_tensor_name_list[i]);
PADDLE_ENFORCE_NE( PADDLE_ENFORCE_NOT_NULL(
var_ptr, nullptr, var_ptr,
"Parameter not created, when load model, can't not find parameter [%s] " platform::errors::PreconditionNotMet(
"please make sure you have run StartUpProgram", "Parameter (%s) is not created when loading model, "
vec_tensor_name_list[i]); "please make sure that exe.run(startup_program) has been executed.",
vec_tensor_name_list[i]));
Tensor* tensor = var_ptr->GetMutable<LoDTensor>(); Tensor* tensor = var_ptr->GetMutable<LoDTensor>();
PADDLE_ENFORCE_NE(tensor, nullptr, PADDLE_ENFORCE_NOT_NULL(
"Paramter [%s] not initialzed " tensor,
"please make sure you have run startUpProgram", platform::errors::PreconditionNotMet(
vec_tensor_name_list[i]); "Paramter [%s] is not initialzed, "
"please make sure that exe.run(startup_program) has been executed.",
vec_tensor_name_list[i]));
PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true, PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true,
"Paramter [%s] not initialzed " platform::errors::PreconditionNotMet(
"please make sure you have run StartUpProgram", "Paramter [%s] is not initialzed, "
vec_tensor_name_list[i]); "please make sure that exe.run(startup_program) has "
"been executed.v",
vec_tensor_name_list[i]));
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(
tensor->dims(), it->second->dims(), tensor->dims(), it->second->dims(),
"Shape not matching: the Program requires a parameter with a shape of " platform::errors::InvalidArgument(
"(%s), " "Shape does not match, the program requires a parameter with a "
"while the loaded parameter (namely [ %s ]) has a shape of (%s).", "shape of "
tensor->dims(), vec_tensor_name_list[i], it->second->dims()); "(%s), while the loaded parameter (namely [ %s ]) has a shape of "
"(%s).",
tensor->dims(), vec_tensor_name_list[i], it->second->dims()));
TensorCopySync(*(it->second.get()), tensor->place(), tensor); TensorCopySync(*(it->second.get()), tensor->place(), tensor);
...@@ -239,9 +252,9 @@ bool SaveTensorToDisk(const std::string& file_name, ...@@ -239,9 +252,9 @@ bool SaveTensorToDisk(const std::string& file_name,
MkDirRecursively(DirName(file_name).c_str()); MkDirRecursively(DirName(file_name).c_str());
std::ofstream fout(file_name, std::ios::binary); std::ofstream fout(file_name, std::ios::binary);
if (!fout) { PADDLE_ENFORCE_EQ(
PADDLE_THROW("File open error. Can not open file [%s]", file_name); fout.is_open(), true,
} platform::errors::Unavailable("File (%s) open failed.", file_name));
// first 256 byte for reserve for fulture upgrade // first 256 byte for reserve for fulture upgrade
char* kReserveBuffer = new char[model_file_reserve_size]; char* kReserveBuffer = new char[model_file_reserve_size];
...@@ -292,9 +305,8 @@ bool SaveTensorToDisk(const std::string& file_name, ...@@ -292,9 +305,8 @@ bool SaveTensorToDisk(const std::string& file_name,
TensorCopySync(*tensor, platform::CPUPlace(), &temp); TensorCopySync(*tensor, platform::CPUPlace(), &temp);
data_ptr = temp.data<void>(); data_ptr = temp.data<void>();
#else #else
PADDLE_THROW( PADDLE_THROW(platform::errors::Unavailable(
"Tensor is in CUDA device, but paddle not compile with CUDA, this " "Tensor is in CUDA device, but paddle not compiled with CUDA."));
"should not happen");
#endif #endif
} }
fout.write(static_cast<const char*>(data_ptr), fout.write(static_cast<const char*>(data_ptr),
...@@ -302,8 +314,9 @@ bool SaveTensorToDisk(const std::string& file_name, ...@@ -302,8 +314,9 @@ bool SaveTensorToDisk(const std::string& file_name,
} }
if (!fout) { if (!fout) {
PADDLE_THROW("Model save failed, data write to model file [%s] error", PADDLE_THROW(platform::errors::Unavailable(
file_name); "Model save failed, error when writing data into model file [%s].",
file_name));
} }
fout.close(); fout.close();
...@@ -316,9 +329,9 @@ bool LoadTensorFromDisk( ...@@ -316,9 +329,9 @@ bool LoadTensorFromDisk(
std::map<std::string, std::shared_ptr<Tensor>>* map_tensor) { std::map<std::string, std::shared_ptr<Tensor>>* map_tensor) {
std::ifstream fin(file_name, std::ios::binary); std::ifstream fin(file_name, std::ios::binary);
if (!fin) { PADDLE_ENFORCE_EQ(
PADDLE_THROW("File open error. Can not open model file [%s]", file_name); fin.is_open(), true,
} platform::errors::Unavailable("File (%s) open failed.", file_name));
ReadReserveBuffer(fin); ReadReserveBuffer(fin);
...@@ -331,7 +344,8 @@ bool LoadTensorFromDisk( ...@@ -331,7 +344,8 @@ bool LoadTensorFromDisk(
uint32_t version; uint32_t version;
fin.read(reinterpret_cast<char*>(&version), sizeof(version)); fin.read(reinterpret_cast<char*>(&version), sizeof(version));
CheckInStreamState(fin, sizeof(version)); CheckInStreamState(fin, sizeof(version));
PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is supported"); PADDLE_ENFORCE_EQ(version, 0U, platform::errors::InvalidArgument(
"Only version 0 tensor is supported."));
proto::VarType::TensorDesc desc; proto::VarType::TensorDesc desc;
{ {
// int32_t size // int32_t size
...@@ -344,7 +358,7 @@ bool LoadTensorFromDisk( ...@@ -344,7 +358,7 @@ bool LoadTensorFromDisk(
CheckInStreamState(fin, sizeof(size)); CheckInStreamState(fin, sizeof(size));
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(
desc.ParseFromArray(buf.get(), size), true, desc.ParseFromArray(buf.get(), size), true,
platform::errors::InvalidArgument("Cannot parse tensor desc")); platform::errors::InvalidArgument("Parse tensor desc failed."));
} }
{ // read tensor { // read tensor
......
paddle/fluid/framework/selected_rows.cc
浏览文件 @ 4f9d6529
...@@ -113,7 +113,9 @@ void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows, ...@@ -113,7 +113,9 @@ void DeserializeFromStream(std::istream& is, SelectedRows* selected_rows,
// the 1st field, unit32_t version for SelectedRows // the 1st field, unit32_t version for SelectedRows
uint32_t version; uint32_t version;
is.read(reinterpret_cast<char*>(&version), sizeof(version)); is.read(reinterpret_cast<char*>(&version), sizeof(version));
PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is supported"); PADDLE_ENFORCE_EQ(version, 0U,
platform::errors::InvalidArgument(
"Only version 0 SelectedRows is supported."));
} }
{ {
// the 2st field, rows information // the 2st field, rows information
...@@ -155,24 +157,27 @@ int64_t SelectedRows::AutoGrownIndex(int64_t key, bool auto_grown, ...@@ -155,24 +157,27 @@ int64_t SelectedRows::AutoGrownIndex(int64_t key, bool auto_grown,
auto iter = id_to_index_.find(key); auto iter = id_to_index_.find(key);
if (iter == id_to_index_.end()) { if (iter == id_to_index_.end()) {
rwlock_->UNLock(); rwlock_->UNLock();
if (!auto_grown) { PADDLE_ENFORCE_EQ(
PADDLE_THROW("key %d not found", key); auto_grown, true,
} platform::errors::NotFound("Input key(%lld) is not found.", key));
rwlock_->WRLock(); rwlock_->WRLock();
auto map_size = id_to_index_.size(); auto map_size = id_to_index_.size();
auto vector_size = rows_.size(); auto vector_size = rows_.size();
if (map_size != vector_size) { if (map_size != vector_size) {
rwlock_->UNLock(); rwlock_->UNLock();
PADDLE_THROW( PADDLE_THROW(platform::errors::InvalidArgument(
"id_to_index_ size %d should have the same size with rows_ %d", "Row map size(%zu) should be equal to rows size(%zu).", map_size,
map_size, vector_size); vector_size));
} }
auto write_iter = id_to_index_.find(key); auto write_iter = id_to_index_.find(key);
if (write_iter == id_to_index_.end()) { if (write_iter == id_to_index_.end()) {
int row_num = rows_.size(); int row_num = rows_.size();
if (row_num == value_->dims()[0]) { if (row_num == value_->dims()[0]) {
rwlock_->UNLock(); rwlock_->UNLock();
PADDLE_THROW("selected rows is full, then length exceed %d", row_num); PADDLE_THROW(platform::errors::InvalidArgument(
"Selected rows is full, then length exceed the length of first "
"dimension (%d).",
row_num));
} }
// key logic to put a key into id_to_index_ // key logic to put a key into id_to_index_
rows_.push_back(key); rows_.push_back(key);
...@@ -203,15 +208,20 @@ void SelectedRows::SyncIndex() { ...@@ -203,15 +208,20 @@ void SelectedRows::SyncIndex() {
void SelectedRows::Get(const framework::Tensor& ids, framework::Tensor* value, void SelectedRows::Get(const framework::Tensor& ids, framework::Tensor* value,
bool auto_grown, bool is_test) { bool auto_grown, bool is_test) {
PADDLE_ENFORCE(value->IsInitialized(), PADDLE_ENFORCE_EQ(value->IsInitialized(), true,
"The value tensor should be initialized."); platform::errors::InvalidArgument(
"The value tensor is not initialized."));
if (ids.numel() == 0) { if (ids.numel() == 0) {
VLOG(3) << "keys is empty, please check data!"; VLOG(3) << "keys is empty, please check data!";
} else { } else {
int64_t value_width = value_->numel() / value_->dims()[0]; int64_t value_width = value_->numel() / value_->dims()[0];
PADDLE_ENFORCE_EQ(value_width, value->numel() / value->dims()[0], PADDLE_ENFORCE_EQ(
"output tensor should have the same shape with table " value_width, value->numel() / value->dims()[0],
"except the dims[0]."); platform::errors::InvalidArgument(
"Output tensor should have the same shape with table "
"except the first dimmension, excepted value width not counting "
"the first dimension is %d, actual value width is %d.",
value_width, value->numel() / value->dims()[0]));
for (int i = 0; i < ids.numel(); ++i) { for (int i = 0; i < ids.numel(); ++i) {
auto id = ids.data<int64_t>()[i]; auto id = ids.data<int64_t>()[i];
int64_t index = AutoGrownIndex(id, auto_grown, is_test); int64_t index = AutoGrownIndex(id, auto_grown, is_test);
......
paddle/fluid/framework/selected_rows.h
浏览文件 @ 4f9d6529
...@@ -82,7 +82,8 @@ class SelectedRows { ...@@ -82,7 +82,8 @@ class SelectedRows {
int64_t Index(int64_t key) const { int64_t Index(int64_t key) const {
auto it = std::find(rows_.begin(), rows_.end(), key); auto it = std::find(rows_.begin(), rows_.end(), key);
if (it == rows_.end()) { if (it == rows_.end()) {
PADDLE_THROW("id %s not in table", key); PADDLE_THROW(platform::errors::NotFound(
"Input id (%lld) is not in current rows table.", key));
} }
return static_cast<int64_t>(std::distance(rows_.begin(), it)); return static_cast<int64_t>(std::distance(rows_.begin(), it));
} }
......
paddle/fluid/framework/shape_inference.cc
浏览文件 @ 4f9d6529
...@@ -25,20 +25,22 @@ namespace framework { ...@@ -25,20 +25,22 @@ namespace framework {
std::vector<DDim> InferShapeContext::GetReaderDims( std::vector<DDim> InferShapeContext::GetReaderDims(
const std::string &name) const { const std::string &name) const {
const std::vector<std::string> &arg_names = Inputs(name); const std::vector<std::string> &arg_names = Inputs(name);
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
arg_names.size(), 1UL, platform::errors::InvalidArgument(
"Reader input '%s' should hold one element, but now it holds %d", name, "Reader input '%s' should hold one element, but now it "
arg_names.size()); "holds %d elements.",
name, arg_names.size()));
return this->GetRepeatedDims(arg_names[0]); return this->GetRepeatedDims(arg_names[0]);
} }
void InferShapeContext::SetReaderDims(const std::string &name, void InferShapeContext::SetReaderDims(const std::string &name,
const std::vector<DDim> &dims) { const std::vector<DDim> &dims) {
const std::vector<std::string> &arg_names = Outputs(name); const std::vector<std::string> &arg_names = Outputs(name);
PADDLE_ENFORCE_EQ( PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
arg_names.size(), 1UL, platform::errors::InvalidArgument(
"Reader output '%s' should hold one element, but now it holds %d", name, "Reader output '%s' should hold one element, but now "
arg_names.size()); "it holds %d elements.",
name, arg_names.size()));
return this->SetRepeatedDims(arg_names[0], dims); return this->SetRepeatedDims(arg_names[0], dims);
} }
......
paddle/fluid/framework/tensor_util.cc
浏览文件 @ 4f9d6529
...@@ -94,9 +94,17 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -94,9 +94,17 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
auto src_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, src_place); auto src_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, src_place);
auto dst_cpu_place = BOOST_GET_CONST(platform::CPUPlace, dst_place); auto dst_cpu_place = BOOST_GET_CONST(platform::CPUPlace, dst_place);
auto ctx_place = ctx.GetPlace(); auto ctx_place = ctx.GetPlace();
PADDLE_ENFORCE_EQ(platform::is_gpu_place(ctx_place), true); PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx_place), true,
platform::errors::PreconditionNotMet(
"Context place error, excepted GPUPlace, but actually %s.",
ctx_place));
auto ctx_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, ctx_place); auto ctx_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, ctx_place);
PADDLE_ENFORCE_EQ(src_gpu_place, ctx_gpu_place); PADDLE_ENFORCE_EQ(src_gpu_place, ctx_gpu_place,
platform::errors::Unavailable(
"Source place and context place do not match, source "
"place is %s, context place is %s.",
src_gpu_place, ctx_gpu_place));
auto stream = auto stream =
reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream(); reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream();
memory::Copy(dst_cpu_place, dst_ptr, src_gpu_place, src_ptr, size, stream); memory::Copy(dst_cpu_place, dst_ptr, src_gpu_place, src_ptr, size, stream);
...@@ -106,9 +114,17 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -106,9 +114,17 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
auto src_cpu_place = BOOST_GET_CONST(platform::CPUPlace, src_place); auto src_cpu_place = BOOST_GET_CONST(platform::CPUPlace, src_place);
auto dst_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dst_place); auto dst_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dst_place);
auto ctx_place = ctx.GetPlace(); auto ctx_place = ctx.GetPlace();
PADDLE_ENFORCE_EQ(platform::is_gpu_place(ctx_place), true); PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx_place), true,
platform::errors::PreconditionNotMet(
"Context place error, excepted GPUPlace, but actually %s.",
ctx_place));
auto ctx_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, ctx_place); auto ctx_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, ctx_place);
PADDLE_ENFORCE_EQ(dst_gpu_place, ctx_gpu_place); PADDLE_ENFORCE_EQ(dst_gpu_place, ctx_gpu_place,
platform::errors::Unavailable(
"Destination place and context place do not match, "
"destination place is %s, context place is %s.",
dst_gpu_place, ctx_gpu_place));
auto stream = auto stream =
reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream(); reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream();
memory::Copy(dst_gpu_place, dst_ptr, src_cpu_place, src_ptr, size, stream); memory::Copy(dst_gpu_place, dst_ptr, src_cpu_place, src_ptr, size, stream);
...@@ -164,7 +180,11 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -164,7 +180,11 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
auto src_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, src_place); auto src_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, src_place);
auto dst_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dst_place); auto dst_gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dst_place);
auto ctx_place = ctx.GetPlace(); auto ctx_place = ctx.GetPlace();
PADDLE_ENFORCE_EQ(platform::is_gpu_place(ctx_place), true); PADDLE_ENFORCE_EQ(
platform::is_gpu_place(ctx_place), true,
platform::errors::PreconditionNotMet(
"Context place error, excepted GPUPlace, but actually %s.",
ctx_place));
auto stream = auto stream =
reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream(); reinterpret_cast<const platform::CUDADeviceContext&>(ctx).stream();
if (platform::is_same_place(src_place, dst_place)) { if (platform::is_same_place(src_place, dst_place)) {
...@@ -180,12 +200,14 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -180,12 +200,14 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size,
stream); stream);
} else { } else {
PADDLE_THROW("ctx is not belong to dst_gpu_place or src_gpu_place."); PADDLE_THROW(platform::errors::Unavailable(
"Context place dose not match the source and destination place."));
} }
} }
} }
else { // NOLINT else { // NOLINT
PADDLE_THROW("Copy from %s to %s is not supported.", src_place, dst_place); PADDLE_THROW(platform::errors::Unimplemented(
"Copying from %s to %s is not supported.", src_place, dst_place));
} }
#endif #endif
} }
...@@ -298,7 +320,8 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place, ...@@ -298,7 +320,8 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
nullptr); nullptr);
} }
else { // NOLINT else { // NOLINT
PADDLE_THROW("Copy from %s to %s is not supported.", src_place, dst_place); PADDLE_THROW(platform::errors::Unimplemented(
"Copy from %s to %s is not supported.", src_place, dst_place));
} }
#endif #endif
} }
...@@ -832,7 +855,9 @@ void TensorFromStream(std::istream& is, Tensor* tensor, ...@@ -832,7 +855,9 @@ void TensorFromStream(std::istream& is, Tensor* tensor,
void* GetDstPtrByDLDataType(DLDataType type, framework::Tensor* dst, void* GetDstPtrByDLDataType(DLDataType type, framework::Tensor* dst,
const platform::Place& dst_place) { const platform::Place& dst_place) {
// vector types not currently supported // vector types not currently supported
PADDLE_ENFORCE_LE(type.lanes, 1, "vector types not currently supported"); PADDLE_ENFORCE_LE(type.lanes, 1,
platform::errors::Unimplemented(
"Vector type is not supported currently."));
switch (type.bits) { switch (type.bits) {
case 8: case 8:
...@@ -840,32 +865,37 @@ void* GetDstPtrByDLDataType(DLDataType type, framework::Tensor* dst, ...@@ -840,32 +865,37 @@ void* GetDstPtrByDLDataType(DLDataType type, framework::Tensor* dst,
return static_cast<void*>(dst->mutable_data<int8_t>(dst_place)); return static_cast<void*>(dst->mutable_data<int8_t>(dst_place));
if (type.code == kDLUInt) if (type.code == kDLUInt)
return static_cast<void*>(dst->mutable_data<uint8_t>(dst_place)); return static_cast<void*>(dst->mutable_data<uint8_t>(dst_place));
PADDLE_THROW("There is no this type.code <%d> when type.bits is <%d>.", PADDLE_THROW(platform::errors::Unimplemented(
type.code, type.bits); "DLDataType code <%d> is illegal when DLDataType.bits is <%d>.",
type.code, type.bits));
case 16: case 16:
if (type.code == kDLInt) if (type.code == kDLInt)
return static_cast<void*>(dst->mutable_data<int16_t>(dst_place)); return static_cast<void*>(dst->mutable_data<int16_t>(dst_place));
if (type.code == kDLFloat) if (type.code == kDLFloat)
return static_cast<void*>( return static_cast<void*>(
dst->mutable_data<paddle::platform::float16>(dst_place)); dst->mutable_data<paddle::platform::float16>(dst_place));
PADDLE_THROW("There is no this type.code <%d> when type.bits is <%d>.", PADDLE_THROW(platform::errors::Unimplemented(
type.code, type.bits); "DLDataType code <%d> is illegal when DLDataType.bits is <%d>.",
type.code, type.bits));
case 32: case 32:
if (type.code == kDLInt) if (type.code == kDLInt)
return static_cast<void*>(dst->mutable_data<int32_t>(dst_place)); return static_cast<void*>(dst->mutable_data<int32_t>(dst_place));
if (type.code == kDLFloat) if (type.code == kDLFloat)
return static_cast<void*>(dst->mutable_data<float>(dst_place)); return static_cast<void*>(dst->mutable_data<float>(dst_place));
PADDLE_THROW("There is no this type.code <%d> when type.bits is <%d>.", PADDLE_THROW(platform::errors::Unimplemented(
type.code, type.bits); "DLDataType code <%d> is illegal when DLDataType.bits is <%d>.",
type.code, type.bits));
case 64: case 64:
if (type.code == kDLInt) if (type.code == kDLInt)
return static_cast<void*>(dst->mutable_data<int64_t>(dst_place)); return static_cast<void*>(dst->mutable_data<int64_t>(dst_place));
if (type.code == kDLFloat) if (type.code == kDLFloat)
return static_cast<void*>(dst->mutable_data<double>(dst_place)); return static_cast<void*>(dst->mutable_data<double>(dst_place));
PADDLE_THROW("There is no this type.code <%d> when type.bits is <%d>.", PADDLE_THROW(platform::errors::Unimplemented(
type.code, type.bits); "DLDataType code <%d> is illegal when DLDataType.bits is <%d>.",
type.code, type.bits));
default: default:
PADDLE_THROW("Unsupport type.bits %d", type.bits); PADDLE_THROW(platform::errors::Unimplemented(
"Unsupported DLDataType.bits %d.", type.bits));
} }
} }
......
paddle/fluid/framework/tensor_util.h
浏览文件 @ 4f9d6529
...@@ -183,7 +183,11 @@ void TensorToVector(const Tensor& src, std::vector<T>* dst) { ...@@ -183,7 +183,11 @@ void TensorToVector(const Tensor& src, std::vector<T>* dst) {
dst->resize(src.numel()); dst->resize(src.numel());
auto dst_ptr = static_cast<void*>(dst->data()); auto dst_ptr = static_cast<void*>(dst->data());
PADDLE_ENFORCE_EQ(platform::is_cpu_place(src.place()), true); PADDLE_ENFORCE_EQ(
platform::is_cpu_place(src.place()), true,
platform::errors::InvalidArgument(
"The input tensor should be CPU device, but actually it is in %s.",
src.place()));
memory::Copy(dst_place, dst_ptr, memory::Copy(dst_place, dst_ptr,
BOOST_GET_CONST(platform::CPUPlace, src.place()), src_ptr, size); BOOST_GET_CONST(platform::CPUPlace, src.place()), src_ptr, size);
......
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