未验证 提交 d1c1d731 编写于 作者: Z zn 提交者: GitHub

[MLU]add reduce op mlu kernel (#41028)

上级 649948a6
/* Copyright (c) 2022 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/collective/c_reduce_op.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_MLU_KERNEL(c_reduce_max,
ops::CReduceOpMLUKernel<ops::kRedMax, float>,
ops::CReduceOpMLUKernel<ops::kRedMax, plat::float16>,
ops::CReduceOpMLUKernel<ops::kRedMax, int>,
ops::CReduceOpMLUKernel<ops::kRedMax, int16_t>,
ops::CReduceOpMLUKernel<ops::kRedMax, int8_t>,
ops::CReduceOpMLUKernel<ops::kRedMax, uint8_t>)
/* Copyright (c) 2022 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/collective/c_reduce_op.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_MLU_KERNEL(c_reduce_min,
ops::CReduceOpMLUKernel<ops::kRedMin, float>,
ops::CReduceOpMLUKernel<ops::kRedMin, plat::float16>,
ops::CReduceOpMLUKernel<ops::kRedMin, int>,
ops::CReduceOpMLUKernel<ops::kRedMin, int16_t>,
ops::CReduceOpMLUKernel<ops::kRedMin, int8_t>,
ops::CReduceOpMLUKernel<ops::kRedMin, uint8_t>)
......@@ -47,6 +47,10 @@ limitations under the License. */
#include "paddle/fluid/platform/device/npu/hccl_helper.h"
#endif
#if defined(PADDLE_WITH_CNCL)
#include "paddle/fluid/platform/device/mlu/cncl_helper.h"
#endif
namespace paddle {
namespace operators {
......@@ -331,6 +335,68 @@ class CReduceOpCUDAKernel : public framework::OpKernel<T> {
}
};
template <ReduceType red_type, typename T>
class CReduceOpMLUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
#if defined(PADDLE_WITH_CNCL)
auto in = ctx.Input<framework::LoDTensor>("X");
auto out = ctx.Output<framework::LoDTensor>("Out");
auto place = ctx.GetPlace();
cnclDataType_t dtype =
platform::ToCNCLDataType(framework::TransToProtoVarType(in->dtype()));
int64_t numel = in->numel();
const void* sendbuff = in->data();
out->Resize(in->dims());
void* recvbuff = out->mutable_data<T>(place);
int rid = ctx.Attr<int>("ring_id");
int root = ctx.Attr<int>("root_id");
auto comm = paddle::platform::CNCLCommContext::Instance().Get(rid, place);
mluStream stream = nullptr;
if (ctx.Attr<bool>("use_calc_stream")) {
auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
stream = static_cast<platform::MLUDeviceContext*>(dev_ctx)->stream();
} else {
stream = comm->stream();
}
cnclReduceOp_t cncl_red_type = cnclSum;
switch (red_type) {
case kRedSum:
cncl_red_type = cnclSum;
break;
case kRedMax:
cncl_red_type = cnclMax;
break;
case kRedMin:
cncl_red_type = cnclMin;
break;
case kRedProd:
cncl_red_type = cnclProd;
break;
default:
PADDLE_THROW(platform::errors::InvalidArgument(
"Invalid reduce type: %d", red_type));
}
PADDLE_ENFORCE_MLU_SUCCESS(cnclReduce(sendbuff, recvbuff, numel, dtype,
cncl_red_type, root, comm->comm(),
stream));
#else
PADDLE_THROW(platform::errors::PreconditionNotMet(
"PaddlePaddle should compile with MLU."));
#endif
}
};
class CReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() {
......
/* Copyright (c) 2022 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/collective/c_reduce_op.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_MLU_KERNEL(c_reduce_prod,
ops::CReduceOpMLUKernel<ops::kRedProd, float>,
ops::CReduceOpMLUKernel<ops::kRedProd, plat::float16>,
ops::CReduceOpMLUKernel<ops::kRedProd, int>,
ops::CReduceOpMLUKernel<ops::kRedProd, int16_t>,
ops::CReduceOpMLUKernel<ops::kRedProd, int8_t>,
ops::CReduceOpMLUKernel<ops::kRedProd, uint8_t>)
/* Copyright (c) 2022 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/collective/c_reduce_op.h"
namespace ops = paddle::operators;
namespace plat = paddle::platform;
REGISTER_OP_MLU_KERNEL(c_reduce_sum,
ops::CReduceOpMLUKernel<ops::kRedSum, float>,
ops::CReduceOpMLUKernel<ops::kRedSum, plat::float16>,
ops::CReduceOpMLUKernel<ops::kRedSum, int>,
ops::CReduceOpMLUKernel<ops::kRedSum, int16_t>,
ops::CReduceOpMLUKernel<ops::kRedSum, int8_t>,
ops::CReduceOpMLUKernel<ops::kRedSum, uint8_t>)
......@@ -26,6 +26,10 @@ if (WITH_MLU)
set_tests_properties(test_collective_allreduce_min PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_allreduce_prod PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_allgather PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_reduce_sum PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_reduce_max PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_reduce_min PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_reduce_prod PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_broadcast_api_mlu PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_allreduce_api_mlu PROPERTIES TIMEOUT 120)
set_tests_properties(test_collective_allgather_api_mlu PROPERTIES TIMEOUT 120)
......
# Copyright (c) 2022 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 argparse
import os
import sys
import signal
import time
import socket
from contextlib import closing
from six import string_types
import math
import paddle
import paddle.fluid as fluid
import paddle.fluid.profiler as profiler
import paddle.fluid.unique_name as nameGen
from paddle.fluid import core
import unittest
from multiprocessing import Process
import paddle.fluid.layers as layers
from functools import reduce
from test_collective_api_base_mlu import TestCollectiveAPIRunnerBase, runtime_main
paddle.enable_static()
class TestCollectiveReduceAPI(TestCollectiveAPIRunnerBase):
def __init__(self):
self.global_ring_id = 0
def get_model(self, main_prog, startup_program, rank):
with fluid.program_guard(main_prog, startup_program):
tindata = layers.data(
name="tindata", shape=[10, 1000], dtype='float32')
paddle.distributed.reduce(tindata, dst=0)
return [tindata]
if __name__ == "__main__":
runtime_main(TestCollectiveReduceAPI, "reduce")
# Copyright (c) 2022 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 argparse
import os
import sys
import signal
import time
import socket
from contextlib import closing
from six import string_types
import math
import paddle
import paddle.fluid as fluid
import paddle.fluid.profiler as profiler
import paddle.fluid.unique_name as nameGen
from paddle.fluid import core
import unittest
from multiprocessing import Process
import paddle.fluid.layers as layers
from functools import reduce
from test_collective_base_mlu import TestCollectiveRunnerBase, runtime_main
paddle.enable_static()
class TestCollectiveReduce(TestCollectiveRunnerBase):
def __init__(self):
self.global_ring_id = 0
def get_model(self, main_prog, startup_program, col_type):
ring_id = 0
rootid = 1
with fluid.program_guard(main_prog, startup_program):
tindata = layers.data(
name="tindata", shape=[10, 1000], dtype='float32')
toutdata = main_prog.current_block().create_var(
name="outof" + col_type,
dtype='float32',
type=core.VarDesc.VarType.LOD_TENSOR,
persistable=False,
stop_gradient=False)
main_prog.global_block().append_op(
type="c_" + col_type,
inputs={'X': tindata},
attrs={'ring_id': ring_id,
'root_id': rootid},
outputs={'Out': toutdata})
main_prog.global_block().append_op(
type="c_sync_comm_stream",
inputs={'X': toutdata},
outputs={'Out': toutdata},
attrs={'ring_id': ring_id})
return toutdata
if __name__ == "__main__":
runtime_main(TestCollectiveReduce)
......@@ -219,6 +219,9 @@ class TestDistBase(unittest.TestCase):
self.assertTrue(
np.allclose(
tr1_out, need_result, rtol=1e-05, atol=1e-05))
elif col_type == "reduce":
need_result = input1 + input2
self.assertTrue(np.allclose(tr0_out, need_result))
elif col_type == "allgather":
need_result = np.vstack((input1, input2))
tr_out0 = np.vstack((tr0_out[0], tr0_out[1]))
......
......@@ -295,6 +295,18 @@ class TestDistBase(unittest.TestCase):
self.assertTrue(
np.allclose(
tr1_out, need_result, rtol=1e-05, atol=1e-05))
elif col_type == "reduce_sum":
need_result = input1 + input2
self.assertTrue(np.allclose(tr1_out, need_result))
elif col_type == "reduce_prod":
need_result = input1 * input2
self.assertTrue(np.allclose(tr1_out, need_result))
elif col_type == "reduce_max":
need_result = np.maximum(input1, input2)
self.assertTrue(np.allclose(tr1_out, need_result))
elif col_type == "reduce_min":
need_result = np.minimum(input1, input2)
self.assertTrue(np.allclose(tr1_out, need_result))
elif col_type == "allgather":
need_result = np.vstack((input1, input2))
self.assertTrue(np.allclose(tr0_out, need_result))
......
# Copyright (c) 2022 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 paddle
from test_collective_api_base_mlu import TestDistBase
paddle.enable_static()
class TestCollectiveReduceAPI(TestDistBase):
def _setup_config(self):
pass
def test_reduce_cncl_fp16(self):
self.check_with_place("collective_reduce_api.py", "reduce", "float16")
def test_reduce_cncl_fp32(self):
self.check_with_place("collective_reduce_api.py", "reduce", "float32")
def test_reduce_cncl_int32(self):
self.check_with_place("collective_reduce_api.py", "reduce", "int32")
if __name__ == '__main__':
unittest.main()
# Copyright (c) 2022 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 sys
import unittest
import numpy as np
import paddle
from test_collective_base_mlu import TestDistBase
paddle.enable_static()
class TestCReduceOp(TestDistBase):
def _setup_config(self):
pass
def test_reduce_max_fp32(self):
self.check_with_place("collective_reduce_op.py", "reduce_max",
"float32")
def test_reduce_max_fp16(self):
self.check_with_place("collective_reduce_op.py", "reduce_max",
"float16")
def test_reduce_max_int32(self):
self.check_with_place("collective_reduce_op.py", "reduce_max", "int32")
def test_reduce_max_int16(self):
self.check_with_place("collective_reduce_op.py", "reduce_max", "int16")
def test_reduce_max_int8(self):
self.check_with_place("collective_reduce_op.py", "reduce_max", "int8")
def test_reduce_max_uint8(self):
self.check_with_place("collective_reduce_op.py", "reduce_max", "uint8")
if __name__ == '__main__':
unittest.main()
# Copyright (c) 2022 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 sys
import unittest
import numpy as np
import paddle
from test_collective_base_mlu import TestDistBase
paddle.enable_static()
class TestCReduceOp(TestDistBase):
def _setup_config(self):
pass
def test_reduce_min_fp32(self):
self.check_with_place("collective_reduce_op.py", "reduce_min",
"float32")
def test_reduce_min_fp16(self):
self.check_with_place("collective_reduce_op.py", "reduce_min",
"float16")
def test_reduce_min_int32(self):
self.check_with_place("collective_reduce_op.py", "reduce_min", "int32")
def test_reduce_min_int16(self):
self.check_with_place("collective_reduce_op.py", "reduce_min", "int16")
def test_reduce_min_int8(self):
self.check_with_place("collective_reduce_op.py", "reduce_min", "int8")
def test_reduce_min_uint8(self):
self.check_with_place("collective_reduce_op.py", "reduce_min", "uint8")
if __name__ == '__main__':
unittest.main()
# Copyright (c) 2022 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 sys
import unittest
import numpy as np
import paddle
from test_collective_base_mlu import TestDistBase
paddle.enable_static()
class TestCReduceOp(TestDistBase):
def _setup_config(self):
pass
def test_reduce_prod_fp32(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod",
"float32")
def test_reduce_prod_fp16(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod",
"float16")
def test_reduce_prod_int32(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod", "int32")
def test_reduce_prod_int16(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod", "int16")
def test_reduce_prod_int8(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod", "int8")
def test_reduce_prod_uint8(self):
self.check_with_place("collective_reduce_op.py", "reduce_prod", "uint8")
if __name__ == '__main__':
unittest.main()
# Copyright (c) 2022 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 sys
import unittest
import numpy as np
import paddle
from test_collective_base_mlu import TestDistBase
paddle.enable_static()
class TestCReduceOp(TestDistBase):
def _setup_config(self):
pass
def test_reduce_sum_fp32(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum",
"float32")
def test_reduce_sum_fp16(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum",
"float16")
def test_reduce_sum_int32(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum", "int32")
def test_reduce_sum_int16(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum", "int16")
def test_reduce_sum_int8(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum", "int8")
def test_reduce_sum_uint8(self):
self.check_with_place("collective_reduce_op.py", "reduce_sum", "uint8")
if __name__ == '__main__':
unittest.main()
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