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shape_wrong

This commit is contained in:
hexia 2020-08-24 15:38:01 +08:00
parent da51877546
commit 4f25e7b10e
2 changed files with 9 additions and 6 deletions
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1
serving/CMakeLists.txt
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@ -99,6 +99,7 @@ add_executable(ms_serving ${SERVING_SRC})
target_link_libraries(ms_serving mindspore::event mindspore::event_pthreads)
target_link_libraries(ms_serving ${_REFLECTION} ${_GRPC_GRPCPP} ${_PROTOBUF_LIBPROTOBUF} pthread)
set_target_properties(ms_serving PROPERTIES POSITION_INDEPENDENT_CODE ON)
if (ENABLE_D)
add_compile_definitions(ENABLE_D)
target_link_libraries(ms_serving ${RUNTIME_LIB})

14
serving/core/http_process.cc
View File

@ -30,7 +30,7 @@ using nlohmann::json;
namespace mindspore {
namespace serving {
const int BUF_MAX = 0x1FFFFF;
const int BUF_MAX = 0x7FFFFFFF;
static constexpr char HTTP_DATA[] = "data";
static constexpr char HTTP_TENSOR[] = "tensor";
enum HTTP_TYPE { TYPE_DATA = 0, TYPE_TENSOR };
@ -46,10 +46,12 @@ Status GetPostMessage(struct evhttp_request *req, std::string *buf) {
if (post_size == 0) {
ERROR_INFER_STATUS(status, INVALID_INPUTS, "http message invalid");
return status;
} else if (post_size > BUF_MAX) {
ERROR_INFER_STATUS(status, INVALID_INPUTS, "http message is bigger than 0x7FFFFFFF.");
return status;
} else {
size_t copy_len = post_size > BUF_MAX ? BUF_MAX : post_size;
buf->resize(copy_len);
memcpy(buf->data(), evbuffer_pullup(req->input_buffer, -1), copy_len);
buf->resize(post_size);
memcpy(buf->data(), evbuffer_pullup(req->input_buffer, -1), post_size);
return status;
}
}
@ -85,7 +87,7 @@ Status CheckMessageValid(const json &message_info, HTTP_TYPE *type) {
count++;
}
if (count != 1) {
ERROR_INFER_STATUS(status, INVALID_INPUTS, "http message must have only one type of (data, tensor, text)");
ERROR_INFER_STATUS(status, INVALID_INPUTS, "http message must have only one type of (data, tensor)");
return status;
}
return status;
@ -206,7 +208,7 @@ Status TransDataToPredictRequest(const json &message_info, PredictRequest *reque
}
for (int i = 0; i < request->data_size(); i++) {
for (size_t j = 0; j < tensor_list[i].shape().size(); ++j) {
request->mutable_data(i)->mutable_tensor_shape()->add_dims(tensor_list[i].shape()[i]);
request->mutable_data(i)->mutable_tensor_shape()->add_dims(tensor_list[i].shape()[j]);
}
}
return SUCCESS;