parent
252f1e4a34
commit
d918ccded3
@ -0,0 +1,111 @@
|
||||
/* Copyright (c) 2016 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. */
|
||||
|
||||
#include "paddle/framework/data_type.h"
|
||||
#include "paddle/framework/op_registry.h"
|
||||
#include "paddle/operators/detail/safe_ref.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace operators {
|
||||
|
||||
struct FillOpVisitor {
|
||||
FillOpVisitor(framework::LoDTensor *tensor, const std::vector<float> &value)
|
||||
: tensor_(tensor), value_(value) {}
|
||||
|
||||
template <typename T>
|
||||
void operator()() const {
|
||||
platform::CPUPlace cpu;
|
||||
auto *data = tensor_->mutable_data<T>(cpu);
|
||||
std::transform(value_.data(), value_.data() + tensor_->numel(), data,
|
||||
[](float dat) { return static_cast<T>(dat); });
|
||||
}
|
||||
|
||||
framework::LoDTensor *tensor_;
|
||||
const std::vector<float> &value_;
|
||||
};
|
||||
|
||||
class FillOp : public framework::OperatorBase {
|
||||
public:
|
||||
FillOp(const std::string &type, const framework::VariableNameMap &inputs,
|
||||
const framework::VariableNameMap &outputs,
|
||||
const framework::AttributeMap &attrs)
|
||||
: OperatorBase(type, inputs, outputs, attrs) {}
|
||||
void Run(const framework::Scope &scope,
|
||||
const platform::DeviceContext &dev_ctx) const override {
|
||||
auto &out =
|
||||
detail::Ref(detail::Ref(scope.FindVar(Output("Out")),
|
||||
"Cannot find variable %s", Output("Out"))
|
||||
.GetMutable<framework::LoDTensor>());
|
||||
out.Resize(framework::make_ddim(Attr<std::vector<int>>("shape")));
|
||||
auto dtype = static_cast<framework::DataType>(Attr<int>("dtype"));
|
||||
platform::CPUPlace cpu;
|
||||
auto force_cpu = Attr<bool>("force_cpu");
|
||||
out.mutable_data(force_cpu ? cpu : dev_ctx.GetPlace(),
|
||||
framework::ToTypeIndex(dtype));
|
||||
|
||||
framework::LoDTensor tensor;
|
||||
|
||||
if (force_cpu || platform::is_cpu_place(dev_ctx.GetPlace())) {
|
||||
tensor.ShareDataWith(out);
|
||||
} else {
|
||||
// Always make tensor in CPU memory.
|
||||
tensor.Resize(out.dims());
|
||||
tensor.mutable_data(cpu, framework::ToTypeIndex(dtype));
|
||||
}
|
||||
|
||||
framework::VisitDataType(
|
||||
dtype, FillOpVisitor(&tensor, Attr<std::vector<float>>("value")));
|
||||
|
||||
if (!force_cpu && platform::is_gpu_place(dev_ctx.GetPlace())) {
|
||||
// Copy tensor to out
|
||||
framework::CopyFrom(tensor, dev_ctx.GetPlace(), dev_ctx, &out);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
class FillOpMaker : public framework::OpProtoAndCheckerMaker {
|
||||
public:
|
||||
FillOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
|
||||
: OpProtoAndCheckerMaker(proto, op_checker) {
|
||||
AddComment(R"DOC(Fill operator
|
||||
|
||||
Fill an tensor with `value` and `shape`. The type of the tensor is specify by
|
||||
`dtype`.
|
||||
)DOC");
|
||||
AddOutput("Out", "(LoDTensor) The output tensor.");
|
||||
AddAttr<std::vector<float>>(
|
||||
"value", "The float values of tensor, which are flatten in row major");
|
||||
AddAttr<std::vector<int>>("shape", "The shape of output tensor");
|
||||
AddAttr<int>("dtype", "The data type of output tensor, Default is float")
|
||||
.SetDefault(framework::DataType::FP32);
|
||||
AddAttr<bool>("force_cpu",
|
||||
"Whether the output tensor must be at CPU memory or not. "
|
||||
"Default is false.")
|
||||
.SetDefault(false);
|
||||
}
|
||||
};
|
||||
|
||||
class FillOpInferShape : public framework::InferShapeBase {
|
||||
public:
|
||||
void operator()(framework::InferShapeContext *context) const override {
|
||||
context->SetOutputDim(
|
||||
"Out",
|
||||
framework::make_ddim(context->Attrs().Get<std::vector<int>>("shape")));
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace operators
|
||||
} // namespace paddle
|
||||
namespace ops = paddle::operators;
|
||||
REGISTER_OPERATOR(fill, ops::FillOp, ops::FillOpInferShape, ops::FillOpMaker);
|
@ -0,0 +1,24 @@
|
||||
import unittest
|
||||
import numpy as np
|
||||
from op_test import OpTest
|
||||
import paddle.v2.fluid.core as core
|
||||
|
||||
|
||||
class TestFillOp(OpTest):
|
||||
def setUp(self):
|
||||
self.op_type = "fill"
|
||||
val = np.random.random(size=[100, 200])
|
||||
self.inputs = {}
|
||||
self.attrs = {
|
||||
'value': val.flatten().tolist(),
|
||||
'shape': [100, 200],
|
||||
'dtype': int(core.DataType.FP64)
|
||||
}
|
||||
self.outputs = {'Out': val.astype('float64')}
|
||||
|
||||
def test_check_output(self):
|
||||
self.check_output()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
Loading…
Reference in new issue