You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
113 lines
4.2 KiB
113 lines
4.2 KiB
/* 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
|
|
|
|
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. */
|
|
|
|
#pragma once
|
|
#include <paddle/fluid/framework/operator.h>
|
|
#include <string>
|
|
#include <vector>
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
template <typename T = int32_t>
|
|
inline std::vector<T> GetDataFromTensor(const framework::Tensor* x) {
|
|
std::vector<T> vec_new_data;
|
|
if (x->type() == framework::proto::VarType::INT32) {
|
|
auto* data = x->data<int>();
|
|
framework::Tensor cpu_attr_tensor;
|
|
if (!platform::is_cpu_place(x->place())) {
|
|
TensorCopySync(*x, platform::CPUPlace(), &cpu_attr_tensor);
|
|
data = cpu_attr_tensor.data<int>();
|
|
}
|
|
vec_new_data = std::vector<T>(data, data + x->numel());
|
|
} else if (x->type() == framework::proto::VarType::INT64) {
|
|
auto* data = x->data<int64_t>();
|
|
framework::Tensor cpu_attr_tensor;
|
|
if (!platform::is_cpu_place(x->place())) {
|
|
TensorCopySync(*x, platform::CPUPlace(), &cpu_attr_tensor);
|
|
data = cpu_attr_tensor.data<int64_t>();
|
|
}
|
|
// NOTE: Converting int64 to int32 may cause data overflow.
|
|
vec_new_data = std::vector<T>(data, data + x->numel());
|
|
} else {
|
|
PADDLE_THROW(platform::errors::InvalidArgument(
|
|
"The dtype of Tensor must be int32 or int64, but received: %s",
|
|
x->type()));
|
|
}
|
|
return vec_new_data;
|
|
}
|
|
|
|
template <typename T = int32_t>
|
|
inline std::vector<T> GetDataFromTensorList(
|
|
const std::vector<const framework::Tensor*>& list_tensor) {
|
|
std::vector<T> vec_new_data;
|
|
for (size_t i = 0; i < list_tensor.size(); ++i) {
|
|
auto tensor = list_tensor[i];
|
|
PADDLE_ENFORCE_EQ(tensor->dims(), framework::make_ddim({1}),
|
|
platform::errors::InvalidArgument(
|
|
"The shape of Tensor in list must be [1]. "
|
|
"But received its shape "
|
|
"is [%s]",
|
|
tensor->dims()));
|
|
|
|
if (tensor->type() == framework::proto::VarType::INT32) {
|
|
if (!platform::is_cpu_place(tensor->place())) {
|
|
framework::Tensor temp;
|
|
TensorCopySync(*tensor, platform::CPUPlace(), &temp);
|
|
vec_new_data.push_back(static_cast<T>(*temp.data<int>()));
|
|
} else {
|
|
vec_new_data.push_back(static_cast<T>(*tensor->data<int>()));
|
|
}
|
|
} else if (tensor->type() == framework::proto::VarType::INT64) {
|
|
if (!platform::is_cpu_place(tensor->place())) {
|
|
framework::Tensor temp;
|
|
TensorCopySync(*tensor, platform::CPUPlace(), &temp);
|
|
// NOTE: Converting int64 to int32 may cause data overflow.
|
|
vec_new_data.push_back(static_cast<T>(*temp.data<int64_t>()));
|
|
} else {
|
|
vec_new_data.push_back(static_cast<T>(*tensor->data<int64_t>()));
|
|
}
|
|
} else {
|
|
PADDLE_THROW(platform::errors::InvalidArgument(
|
|
"The dtype of Tensor in list must be int32 or int64, but received: "
|
|
"%s",
|
|
tensor->type()));
|
|
}
|
|
}
|
|
return vec_new_data;
|
|
}
|
|
|
|
inline framework::DDim GetShape(const framework::ExecutionContext& ctx) {
|
|
// 1. shape is a Tensor
|
|
if (ctx.HasInput("ShapeTensor")) {
|
|
auto* shape_tensor = ctx.Input<framework::LoDTensor>("ShapeTensor");
|
|
auto vec_shape = GetDataFromTensor<int>(shape_tensor);
|
|
return framework::make_ddim(vec_shape);
|
|
}
|
|
|
|
// 2. shape is a list/tuple containing Tensor
|
|
auto shape_tensor_list = ctx.MultiInput<framework::Tensor>("ShapeTensorList");
|
|
if (shape_tensor_list.size() > 0) {
|
|
auto vec_shape = GetDataFromTensorList(shape_tensor_list);
|
|
return framework::make_ddim(vec_shape);
|
|
}
|
|
|
|
// 3. shape is a list/tuple without containing Tensor
|
|
auto vec_shape = ctx.Attr<std::vector<int64_t>>("shape");
|
|
return framework::make_ddim(vec_shape);
|
|
}
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|