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118 changes: 118 additions & 0 deletions paddle/fluid/operators/shard_index_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/shard_index_op.h"
#include "paddle/fluid/operators/npu_op_runner.h"

namespace paddle {
namespace operators {

using LoDTensor = framework::LoDTensor;
using Tensor = framework::Tensor;
template <typename T>
class ShardIndexNPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
VLOG(4) << "start kernel";
auto* in = context.Input<LoDTensor>("X");
auto* out = context.Output<LoDTensor>("Out");
int index_num = context.Attr<int>("index_num");
int nshards = context.Attr<int>("nshards");
int shard_id = context.Attr<int>("shard_id");
int ignore_value = context.Attr<int>("ignore_value");

PADDLE_ENFORCE_GT(
index_num, 0,
platform::errors::InvalidArgument(
"The value 'index_num' for Op(shard_index) must be greater than 0, "
"but the value given is %d.",
index_num));
PADDLE_ENFORCE_GT(nshards, 0,
platform::errors::InvalidArgument(
"The value 'nshard' for Op(shard_index) must be "
"greater than 0, but the value given is %d.",
nshards));
PADDLE_ENFORCE_GE(
shard_id, 0,
platform::errors::InvalidArgument(
"The value 'shard_id' for Op(shard_index) must be greater or "
"equal to 0, but the value given is %d.",
shard_id));
PADDLE_ENFORCE_LT(
shard_id, nshards,
platform::errors::InvalidArgument(
"The value 'shard_id' for Op(shard_index) must be less than "
"nshards (%d), but the value given is %d.",
nshards, shard_id));

int shard_size = (index_num + nshards - 1) / nshards;

auto place = context.GetPlace();
out->Resize(in->dims());
out->set_lod(in->lod());
out->mutable_data<T>(place);

Tensor tmp(in->type());
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后面换个名吧,shard_size_tensor或者tmp_shard_size

tmp.mutable_data<T>(framework::DDim({1}), place);
FillNpuTensorWithConstant(&tmp, shard_size);

Tensor condition(framework::proto::VarType::BOOL);
condition.mutable_data<bool>(in->dims(), place);

Tensor tmp2(in->type());
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这个名字也换一下,mod_out、out_mod啥的

tmp2.mutable_data<T>(in->dims(), place);

Tensor tmp3(in->type());
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same

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好的

tmp3.mutable_data<T>(in->dims(), place);

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

NpuOpRunner runner;
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NpuOpRunner("Mod", {*in, tmp}, {tmp2}).Run(stream);
可以换个好看点的写法

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好的

runner.AddInputs({*in, tmp});
runner.AddOutputs({tmp2});
runner.SetType("Mod");
runner.Run(stream);

NpuOpRunner runner1;
runner1.AddInputs({*in, tmp});
runner1.AddOutputs({tmp3});
runner1.SetType("FloorDiv");
runner1.Run(stream);

FillNpuTensorWithConstant(&tmp, shard_id);
NpuOpRunner runner2;
runner2.AddInputs({tmp3, tmp});
runner2.AddOutputs({condition});
runner2.SetType("Equal");
runner2.Run(stream);

Tensor tmp4(in->type());
tmp4.mutable_data<T>(in->dims(), place);
FillNpuTensorWithConstant(&tmp4, ignore_value);
tmp4.Resize(in->dims());

NpuOpRunner runner3;
runner3.AddInputs({condition, tmp2, tmp4});
runner3.AddOutputs({*out});
runner3.SetType("Select");
runner3.Run(stream);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_NPU_KERNEL(shard_index, ops::ShardIndexNPUKernel<int>,
ops::ShardIndexNPUKernel<int64_t>);
84 changes: 84 additions & 0 deletions python/paddle/fluid/tests/unittests/npu/test_shard_index_op.py
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# Copyright (c) 2019 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 unittest
import numpy as np
import math
import sys
sys.path.append("..")
from op_test import OpTest
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.framework as framework
from paddle.fluid.framework import Program, program_guard
import paddle
paddle.enable_static()
SEED = 2021


def common_setup(self, index_num, nshards, shard_id, ignore_value):
self.__class__.use_npu = True
self.__class__.op_type = "shard_index"

self.op_type = 'shard_index'
x_lod = [[i for i in range(10)]]
N = sum(x_lod[0])
x = [np.random.randint(0, index_num - 1) for i in range(N)]
x = np.array(x).astype('int32').reshape([N, 1])

shard_size = (index_num + nshards - 1) // nshards
out = np.zeros(shape=x.shape).astype('int32')
for i in range(N):
if x[i] // shard_size == shard_id:
out[i] = x[i] % shard_size
else:
out[i] = ignore_value

self.inputs = {'X': (x, x_lod)}
self.attrs = {
'index_num': index_num,
'nshards': nshards,
'shard_id': shard_id,
'ignore_value': ignore_value
}
self.outputs = {'Out': (out, x_lod)}


class TestShardIndexShardId0Op(OpTest):
def setUp(self):
common_setup(self, 20, 2, 0, -1)

def test_check_output(self):
return self.check_output_with_place(place=paddle.NPUPlace(0))


class TestShardIndexShardId1Op(TestShardIndexShardId0Op):
def setUp(self):
common_setup(self, 20, 2, 1, -1)


class TestShardIndexIgnoreValueOp(TestShardIndexShardId0Op):
def setUp(self):
common_setup(self, 20, 2, 0, -2)


class TestShardIndexNotEvenlyDividedOp(TestShardIndexShardId0Op):
def setUp(self):
common_setup(self, 15, 2, 1, -1)


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