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new api trunc, test=develop #33371
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new api trunc, test=develop #33371
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35aebd5
new api trunc, test=develop
zhangbo9674 cd716f2
new api trunc, test=develop
zhangbo9674 33cc89b
new api paddle.trunc, test=develop
zhangbo9674 b577296
new api paddle.trunc, test=develop
zhangbo9674 9a6272b
new api paddle.trunc, test=develop
zhangbo9674 de107a3
new api paddle.trunc, test=develop
zhangbo9674 58b19cb
new api paddle.trunc, test=develop
zhangbo9674 b7b5803
new api paddle.trunc, test=develop
zhangbo9674 f76b32e
new api paddle.trunc, test=develop
zhangbo9674 8158a58
new api paddle.trunc, test=develop
zhangbo9674 feaeaa4
Merge branch 'develop' of https://github.com/zhangbo9674/Paddle into …
zhangbo9674 b7f18f9
new api paddle.trunc, test=develop
zhangbo9674 2783560
new api paddle.trunc, test=develop
zhangbo9674 df79e49
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
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/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
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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 | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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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. */ | ||
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#include "paddle/fluid/operators/trunc_op.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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class TruncOp : public framework::OperatorWithKernel { | ||
public: | ||
using framework::OperatorWithKernel::OperatorWithKernel; | ||
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void InferShape(framework::InferShapeContext *ctx) const override { | ||
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "trunc"); | ||
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "trunc"); | ||
auto input_dims = ctx->GetInputDim("X"); | ||
ctx->SetOutputDim("Out", input_dims); | ||
ctx->ShareLoD("X", /*->*/ "Out"); | ||
} | ||
}; | ||
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class TruncOpMaker : public framework::OpProtoAndCheckerMaker { | ||
public: | ||
void Make() override { | ||
AddInput("X", "(Tensor), The input tensor of trunc op."); | ||
AddOutput("Out", "(Tensor), The output tensor of trunc op."); | ||
AddComment(R"DOC( | ||
Trunc Operator. | ||
Returns a new tensor with the truncated integer values of input. | ||
$$out = trunc(x)$$ | ||
)DOC"); | ||
} | ||
}; | ||
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class TruncGradOp : public framework::OperatorWithKernel { | ||
public: | ||
using framework::OperatorWithKernel::OperatorWithKernel; | ||
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void InferShape(framework::InferShapeContext *ctx) const override { | ||
OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input", | ||
framework::GradVarName("Out"), "TruncGrad"); | ||
OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")), "Output", | ||
framework::GradVarName("X"), "TruncGrad"); | ||
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auto dout_dims = ctx->GetInputDim(framework::GradVarName("Out")); | ||
ctx->SetOutputDim(framework::GradVarName("X"), dout_dims); | ||
} | ||
}; | ||
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template <typename T> | ||
class TruncGradOpMaker : public framework::SingleGradOpMaker<T> { | ||
public: | ||
using framework::SingleGradOpMaker<T>::SingleGradOpMaker; | ||
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void Apply(GradOpPtr<T> retv) const override { | ||
retv->SetType("trunc_grad"); | ||
retv->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); | ||
retv->SetAttrMap(this->Attrs()); | ||
retv->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); | ||
} | ||
}; | ||
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} // namespace operators | ||
} // namespace paddle | ||
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namespace ops = paddle::operators; | ||
REGISTER_OPERATOR(trunc, ops::TruncOp, ops::TruncOpMaker, | ||
ops::TruncGradOpMaker<paddle::framework::OpDesc>, | ||
ops::TruncGradOpMaker<paddle::imperative::OpBase>); | ||
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REGISTER_OPERATOR(trunc_grad, ops::TruncGradOp); | ||
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REGISTER_OP_CPU_KERNEL(trunc, ops::TruncKernel<float>, ops::TruncKernel<double>, | ||
ops::TruncKernel<int>, ops::TruncKernel<int64_t>); | ||
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REGISTER_OP_CPU_KERNEL(trunc_grad, ops::TruncGradKernel<float>, | ||
ops::TruncGradKernel<double>, ops::TruncGradKernel<int>, | ||
ops::TruncGradKernel<int64_t>); |
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/* Copyright (c) 2021 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 | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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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. */ | ||
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#include "paddle/fluid/operators/trunc_op.h" | ||
#include "paddle/fluid/platform/cuda_primitives.h" | ||
#include "paddle/fluid/platform/gpu_info.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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using platform::PADDLE_CUDA_NUM_THREADS; | ||
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template <typename T> | ||
class TruncFunctor { | ||
public: | ||
__device__ TruncFunctor(const T x) : x_(x) {} | ||
__device__ T operator()() { return trunc(x_); } | ||
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public: | ||
const T x_; | ||
}; | ||
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template <> | ||
class TruncFunctor<int> { | ||
public: | ||
__device__ TruncFunctor(const int x) : x_(x) {} | ||
__device__ int operator()() { return x_; } | ||
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public: | ||
const int x_; | ||
}; | ||
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template <> | ||
class TruncFunctor<int64_t> { | ||
public: | ||
__device__ TruncFunctor(const int64_t x) : x_(x) {} | ||
__device__ int64_t operator()() { return x_; } | ||
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public: | ||
const int64_t x_; | ||
}; | ||
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template <typename T> | ||
__global__ void Trunc(const T* x, T* out, int64_t N) { | ||
CUDA_KERNEL_LOOP(index, N) { | ||
TruncFunctor<T> functor(x[index]); | ||
out[index] = functor(); | ||
} | ||
} | ||
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template <typename T> | ||
__global__ void TruncGrad(T* dx, int64_t N) { | ||
CUDA_KERNEL_LOOP(index, N) { dx[index] = static_cast<T>(0.0); } | ||
} | ||
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template <typename T> | ||
class TruncCUDAKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& context) const override { | ||
auto* x = context.Input<Tensor>("X"); | ||
auto* out = context.Output<Tensor>("Out"); | ||
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const auto* x_data = x->data<T>(); | ||
auto* out_data = out->mutable_data<T>(context.GetPlace()); | ||
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int64_t numel = x->numel(); | ||
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int theads = PADDLE_CUDA_NUM_THREADS; | ||
int blocks = (numel + theads - 1) / theads; | ||
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Trunc<<<blocks, theads>>>(x_data, out_data, numel); | ||
} | ||
}; | ||
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template <typename T> | ||
class TruncCUDAGradKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& context) const override { | ||
auto* dout = context.Input<Tensor>(framework::GradVarName("Out")); | ||
auto* dx = context.Output<Tensor>(framework::GradVarName("X")); | ||
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const auto* dout_data = dout->data<T>(); | ||
auto* dx_data = dx->mutable_data<T>(context.GetPlace()); | ||
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int64_t numel = dout->numel(); | ||
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int theads = PADDLE_CUDA_NUM_THREADS; | ||
int blocks = (numel + theads - 1) / theads; | ||
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TruncGrad<<<blocks, theads>>>(dx_data, numel); | ||
} | ||
}; | ||
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} // namespace operators | ||
} // namespace paddle | ||
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namespace ops = paddle::operators; | ||
REGISTER_OP_CUDA_KERNEL(trunc, ops::TruncCUDAKernel<float>, | ||
ops::TruncCUDAKernel<double>, ops::TruncCUDAKernel<int>, | ||
ops::TruncCUDAKernel<int64_t>); | ||
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REGISTER_OP_CUDA_KERNEL(trunc_grad, ops::TruncCUDAGradKernel<float>, | ||
ops::TruncCUDAGradKernel<double>, | ||
ops::TruncCUDAGradKernel<int>, | ||
ops::TruncCUDAGradKernel<int64_t>); |
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@@ -0,0 +1,55 @@ | ||
/* Copyright (c) 2021 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 | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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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. */ | ||
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#pragma once | ||
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#include <math.h> | ||
#include "paddle/fluid/framework/op_registry.h" | ||
#include "paddle/fluid/framework/operator.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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using Tensor = framework::Tensor; | ||
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template <typename T> | ||
class TruncKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& context) const override { | ||
const Tensor* x = context.Input<Tensor>("X"); | ||
Tensor* out = context.Output<Tensor>("Out"); | ||
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size_t numel = x->numel(); | ||
const T* x_data = x->data<T>(); | ||
T* out_data = out->mutable_data<T>(context.GetPlace()); | ||
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for (size_t i = 0; i < numel; i++) { | ||
out_data[i] = trunc(x_data[i]); | ||
} | ||
} | ||
}; | ||
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template <typename T> | ||
class TruncGradKernel : public framework::OpKernel<T> { | ||
public: | ||
void Compute(const framework::ExecutionContext& context) const override { | ||
auto* dx = context.Output<Tensor>(framework::GradVarName("X")); | ||
T* dx_data = dx->mutable_data<T>(context.GetPlace()); | ||
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int numel = dx->numel(); | ||
memset(dx_data, 0.0, numel * sizeof(T)); | ||
} | ||
}; | ||
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} // namespace operators | ||
} // namespace paddle |
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# Copyright (c) 2021 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. | ||
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from __future__ import print_function | ||
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import unittest | ||
import numpy as np | ||
from op_test import OpTest | ||
import paddle | ||
import paddle.fluid.core as core | ||
import paddle.fluid as fluid | ||
from paddle.fluid import Program, program_guard | ||
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paddle.enable_static() | ||
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class TestTruncOp(OpTest): | ||
def setUp(self): | ||
self.op_type = "trunc" | ||
self.dtype = np.float64 | ||
np.random.seed(2021) | ||
self.inputs = {'X': np.random.random((20, 20)).astype(self.dtype)} | ||
self.outputs = {'Out': (np.trunc(self.inputs['X']))} | ||
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def init_dtype_type(self): | ||
self.dtype = np.float64 | ||
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def test_check_output(self): | ||
self.check_output() | ||
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def test_check_grad(self): | ||
self.check_grad(['X'], 'Out', numeric_grad_delta=1e-5) | ||
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class TestFloatTruncOp(TestTruncOp): | ||
def init_dtype_type(self): | ||
self.dtype = np.float32 | ||
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class TestIntTruncOp(TestTruncOp): | ||
def init_dtype_type(self): | ||
self.dtype = np.int32 | ||
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class TestTruncAPI(unittest.TestCase): | ||
def setUp(self): | ||
self.shape = [20, 20] | ||
self.x = np.random.random((20, 20)).astype(np.float32) | ||
self.place = paddle.CPUPlace() | ||
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def test_api_static(self): | ||
paddle.enable_static() | ||
with paddle.static.program_guard(paddle.static.Program()): | ||
x = paddle.fluid.data('X', self.shape) | ||
out = paddle.trunc(x) | ||
exe = paddle.static.Executor(self.place) | ||
res = exe.run(feed={'X': self.x}, fetch_list=[out]) | ||
out_ref = np.trunc(self.x) | ||
for out in res: | ||
self.assertEqual(np.allclose(out, out_ref, rtol=1e-08), True) | ||
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def test_api_dygraph(self): | ||
paddle.disable_static(self.place) | ||
x_tensor = paddle.to_tensor(self.x) | ||
out = paddle.trunc(x_tensor) | ||
out_ref = np.trunc(self.x) | ||
self.assertEqual(np.allclose(out.numpy(), out_ref, rtol=1e-08), True) | ||
paddle.enable_static() | ||
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def test_errors(self): | ||
with paddle.static.program_guard(paddle.static.Program()): | ||
x = paddle.fluid.data('X', [20, 20], 'bool') | ||
self.assertRaises(TypeError, paddle.trunc, x) | ||
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if __name__ == "__main__": | ||
unittest.main() |
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You can register NoNeedBufferVars for X@GRAD to save memory, see https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/07_new_op/op_notes_cn.html#id6 for details.
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Done, thanks!