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提交 6c7d43e1 编写于 作者: W WangXi
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speed up output copy

上级 1a5bb9db
隐藏空白更改
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Showing with 12 addition and 24 deletion
core/general-client/src/general_model.cpp
浏览文件 @ 6c7d43e1
...@@ -285,22 +285,16 @@ int PredictorClient::batch_predict( ...@@ -285,22 +285,16 @@ int PredictorClient::batch_predict(
// int idx = _fetch_name_to_idx[name]; // int idx = _fetch_name_to_idx[name];
if (_fetch_name_to_type[name] == 0) { if (_fetch_name_to_type[name] == 0) {
VLOG(2) << "ferch var " << name << "type int"; VLOG(2) << "ferch var " << name << "type int";
model._int64_value_map[name].resize(
output.insts(0).tensor_array(idx).int64_data_size());
int size = output.insts(0).tensor_array(idx).int64_data_size(); int size = output.insts(0).tensor_array(idx).int64_data_size();
for (int i = 0; i < size; ++i) { model._int64_value_map[name] = std::vector<int64_t>(
model._int64_value_map[name][i] = output.insts(0).tensor_array(idx).int64_data().begin(),
output.insts(0).tensor_array(idx).int64_data(i); output.insts(0).tensor_array(idx).int64_data().begin() + size);
}
} else { } else {
VLOG(2) << "fetch var " << name << "type float"; VLOG(2) << "fetch var " << name << "type float";
model._float_value_map[name].resize(
output.insts(0).tensor_array(idx).float_data_size());
int size = output.insts(0).tensor_array(idx).float_data_size(); int size = output.insts(0).tensor_array(idx).float_data_size();
for (int i = 0; i < size; ++i) { model._float_value_map[name] = std::vector<float>(
model._float_value_map[name][i] = output.insts(0).tensor_array(idx).float_data().begin(),
output.insts(0).tensor_array(idx).float_data(i); output.insts(0).tensor_array(idx).float_data().begin() + size);
}
} }
idx += 1; idx += 1;
} }
...@@ -564,22 +558,16 @@ int PredictorClient::numpy_predict( ...@@ -564,22 +558,16 @@ int PredictorClient::numpy_predict(
// int idx = _fetch_name_to_idx[name]; // int idx = _fetch_name_to_idx[name];
if (_fetch_name_to_type[name] == 0) { if (_fetch_name_to_type[name] == 0) {
VLOG(2) << "ferch var " << name << "type int"; VLOG(2) << "ferch var " << name << "type int";
model._int64_value_map[name].resize(
output.insts(0).tensor_array(idx).int64_data_size());
int size = output.insts(0).tensor_array(idx).int64_data_size(); int size = output.insts(0).tensor_array(idx).int64_data_size();
for (int i = 0; i < size; ++i) { model._int64_value_map[name] = std::vector<int64_t>(
model._int64_value_map[name][i] = output.insts(0).tensor_array(idx).int64_data().begin(),
output.insts(0).tensor_array(idx).int64_data(i); output.insts(0).tensor_array(idx).int64_data().begin() + size);
}
} else { } else {
VLOG(2) << "fetch var " << name << "type float"; VLOG(2) << "fetch var " << name << "type float";
model._float_value_map[name].resize(
output.insts(0).tensor_array(idx).float_data_size());
int size = output.insts(0).tensor_array(idx).float_data_size(); int size = output.insts(0).tensor_array(idx).float_data_size();
for (int i = 0; i < size; ++i) { model._float_value_map[name] = std::vector<float>(
model._float_value_map[name][i] = output.insts(0).tensor_array(idx).float_data().begin(),
output.insts(0).tensor_array(idx).float_data(i); output.insts(0).tensor_array(idx).float_data().begin() + size);
}
} }
idx += 1; idx += 1;
} }
......
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