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[NPU] add Increment op (PaddlePaddle#31563)
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* add increment

* fix

* update test increment op inplace

* update increment op

* increment b = 2

Co-authored-by: oyjxer <1728722986@qq.com>
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2 people authored and frankwhzhang committed Apr 12, 2021
1 parent ee43974 commit 8c4b97c
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77 changes: 77 additions & 0 deletions paddle/fluid/operators/increment_op_npu.cc
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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.


#include "paddle/fluid/operators/increment_op.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/operators/npu_op_runner.h"

namespace paddle {
namespace framework {
class OpDesc;
class Variable;
} // namespace framework
namespace imperative {
class OpBase;
} // namespace imperative
} // namespace paddle

namespace paddle {
namespace operators {


template <typename DeviceContext, typename T>
class IncrementalNPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* x_tensor = context.Input<framework::Tensor>("X");
auto* out_tensor = context.Output<framework::Tensor>("Out");
float step = context.Attr<float>("step");
out_tensor->mutable_data<T>(context.GetPlace());

Tensor step_tensor(x_tensor->type());
std::vector<T> step_vec;
step_vec.push_back(static_cast<T>(step));
framework::TensorFromVector(
step_vec,
context.device_context(),
&step_tensor);

auto runner = NpuOpRunner("Add",
{*x_tensor, step_tensor},
{*out_tensor},
{});

auto stream =
context.template device_context<paddle::platform::NPUDeviceContext>()
.stream();
runner.Run(stream);
}
};

} // namespace operators
} // namespace paddle


namespace plat = paddle::platform;
namespace ops = paddle::operators;

REGISTER_OP_NPU_KERNEL(
increment,
ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, float>,
ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, double>,
ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, int>,
ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, int64_t>,
ops::IncrementalNPUKernel<paddle::platform::NPUDeviceContext, plat::float16>)

85 changes: 85 additions & 0 deletions paddle/fluid/operators/increment_op_npu_test.cc
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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. */

#ifndef _WIN32
#include <unistd.h>
#endif

#include <string>
#include <thread> // NOLINT
#include <vector>

#include "gtest/gtest.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/operators/dropout_op.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/string/printf.h"

namespace f = paddle::framework;
namespace p = paddle::platform;
namespace m = paddle::operators::math;

USE_OP(increment);
USE_OP_DEVICE_KERNEL(increment, NPU);

template <typename T>
void Compare(f::Scope* scope, const p::DeviceContext& ctx,
std::string op_type) {
// init
auto x = scope->Var("X");
auto tensor_x = x->GetMutable<f::LoDTensor>();

std::vector<T> init;
init.push_back(static_cast<T>(1.0));

TensorFromVector(init, ctx, tensor_x);
tensor_x->Resize({1});

ctx.Wait();

auto place = ctx.GetPlace();
auto out = scope->Var("Out");
auto tensor_out = out->GetMutable<f::LoDTensor>();

f::AttributeMap attr_input = { {"step", static_cast<float>(2.0)} };
auto op = f::OpRegistry::CreateOp("increment", {{"X", {"X"}}},
{{"Out", {"Out"}}},
attr_input);

op->Run(*scope, place);

std::vector<T> out_vec;
TensorToVector(*tensor_out, ctx, &out_vec);

ctx.Wait();

EXPECT_EQ((uint32_t)out_vec.size(), (uint32_t)1);
EXPECT_EQ(out_vec[0], static_cast<T>(3.0));
}


TEST(increment, NPU_fp32) {
f::Scope scope;
p::NPUDeviceContext ctx(p::NPUPlace(0));
Compare<float>(&scope, ctx, "increment");
}

TEST(increment, NPU_fp64) {
f::Scope scope;
p::NPUDeviceContext ctx(p::NPUPlace(0));
Compare<float>(&scope, ctx, "increment");
}

116 changes: 116 additions & 0 deletions python/paddle/fluid/tests/unittests/npu/test_increment_op_npu.py
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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.

from __future__ import print_function

import numpy as np
import unittest
import sys
sys.path.append("..")
from op_test import OpTest
import paddle
import paddle.fluid as fluid
from paddle.fluid import core

paddle.enable_static()
SEED = 2021

NPUPlace = 5


@unittest.skipIf(not paddle.is_compiled_with_npu(),
"core is not compiled with NPU")
class TestIncrement(OpTest):
def setUp(self):
self.set_npu()
self.place = paddle.NPUPlace(NPUPlace)
self.op_type = "increment"
self.init_dtype()

self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(np.array([1]).astype(self.dtype)), }

self.attrs = {"Step": 1}
self.outputs = {'Out': np.array([2])}

def set_npu(self):
self.__class__.use_npu = True
self.__class__.no_need_check_grad = True

def init_dtype(self):
self.dtype = np.int64

def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)


@unittest.skipIf(not paddle.is_compiled_with_npu(),
"core is not compiled with NPU")
class TestIncrementFP16(OpTest):
def setUp(self):
self.set_npu()
self.place = paddle.NPUPlace(NPUPlace)
self.op_type = "increment"
self.init_dtype()

self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(np.array([1]).astype(self.dtype)), }
self.pre_input_id = id(self.inputs['X'])

self.attrs = {"Step": 1}
self.outputs = {'Out': np.array([2])}

def set_npu(self):
self.__class__.use_npu = True

def init_dtype(self):
self.dtype = np.float16

def test_check_output(self):
self.check_output_with_place(self.place, check_dygraph=False)


@unittest.skipIf(not paddle.is_compiled_with_npu(),
"core is not compiled with NPU")
class TestIncrementInplace(unittest.TestCase):
def test_npu(self):
main_prog = paddle.static.Program()
startup_prog = paddle.static.Program()
main_prog.random_seed = SEED
startup_prog.random_seed = SEED
np.random.seed(SEED)

a_np = np.array([1]).astype('float32')

with paddle.static.program_guard(main_prog, startup_prog):
a = paddle.static.data(name="a", shape=[1], dtype='float32')
b = fluid.layers.increment(a)

place = paddle.NPUPlace(NPUPlace)

exe = paddle.static.Executor(place)
exe.run(startup_prog)

b_value = exe.run(
main_prog,
feed={"a": a_np,},
fetch_list=[b])

print('input a id is : {}'.format(id(a)))
print('input b id is : {}'.format(id(b)))

self.assertEqual(id(a), id(b))
self.assertEqual(b_value[0], 2)


if __name__ == '__main__':
unittest.main()

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