未验证 提交 59d50468 编写于 作者: Z zhaoying9105 提交者: GitHub

[MLU] add exp and exp_grad kernel (#43852)

上级 52d43ca2
......@@ -208,6 +208,54 @@ class LogMLUKernel : public framework::OpKernel<T> {
}
};
template <typename T>
class ExpMLUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* input = ctx.Input<Tensor>("X");
auto* output = ctx.Output<Tensor>("Out");
output->mutable_data<T>(ctx.GetPlace());
MLUCnnlTensorDesc input_desc(*input);
MLUCnnlTensorDesc output_desc(*output);
cnnlComputationPreference_t prefer = CNNL_COMPUTATION_HIGH_PRECISION;
MLUCnnl::Exp(ctx,
prefer,
input_desc.get(),
GetBasePtr(input),
output_desc.get(),
GetBasePtr(output));
}
};
template <typename T>
class ExpGradMLUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* out = ctx.Input<Tensor>("Out");
auto* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
dx->mutable_data<T>(ctx.GetPlace());
MLUCnnlTensorDesc dout_desc(*dout);
MLUCnnlTensorDesc dx_desc(*dx);
MLUCnnlTensorDesc out_desc(*out);
MLUCnnlOpTensorDesc op_tensor_desc(
CNNL_OP_TENSOR_MUL, ToCnnlDataType<T>(), CNNL_NOT_PROPAGATE_NAN);
MLUCnnl::OpTensor(ctx,
op_tensor_desc.get(),
dout_desc.get(),
GetBasePtr(dout),
out_desc.get(),
GetBasePtr(out),
dx_desc.get(),
GetBasePtr(dx),
ToCnnlDataType<T>());
}
};
} // namespace operators
} // namespace paddle
......@@ -303,3 +351,11 @@ REGISTER_OP_MLU_KERNEL(
log10,
ops::LogMLUKernel<CNNL_LOG_10, float>,
ops::LogMLUKernel<CNNL_LOG_10, paddle::platform::float16>);
REGISTER_OP_MLU_KERNEL(exp,
ops::ExpMLUKernel<float>,
ops::ExpMLUKernel<paddle::platform::float16>);
REGISTER_OP_MLU_KERNEL(exp_grad,
ops::ExpGradMLUKernel<float>,
ops::ExpGradMLUKernel<paddle::platform::float16>);
# 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 unittest
import sys
sys.path.append("..")
from op_test import OpTest
import paddle
import paddle.fluid as fluid
paddle.enable_static()
SEED = 2021
class TestExp(OpTest):
def setUp(self):
self.set_mlu()
self.op_type = "exp"
self.place = paddle.MLUPlace(0)
self.init_dtype()
np.random.seed(SEED)
x = np.random.rand(20, 5).astype(self.dtype)
out = np.exp(x)
self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
self.attrs = {}
self.outputs = {'Out': out}
def set_mlu(self):
self.__class__.use_mlu = True
def init_dtype(self):
self.dtype = np.float32
def test_check_output(self):
self.check_output_with_place(self.place)
def test_check_grad(self):
self.check_grad_with_place(self.place, ['X'], 'Out')
class TestExpFp16(OpTest):
def setUp(self):
self.set_mlu()
self.op_type = "exp"
self.place = paddle.MLUPlace(0)
self.init_dtype()
np.random.seed(SEED)
x = np.random.rand(20, 5).astype(self.dtype)
out = np.exp(x)
self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
self.attrs = {}
self.outputs = {'Out': out}
def set_mlu(self):
self.__class__.use_mlu = True
self.__class__.no_need_check_grad = True
def init_dtype(self):
self.dtype = np.float16
def test_check_output(self):
self.check_output_with_place(self.place)
class TestExpNeg(OpTest):
def setUp(self):
self.set_mlu()
self.op_type = "exp"
self.place = paddle.MLUPlace(0)
self.init_dtype()
np.random.seed(SEED)
x = np.random.random([20, 5]).astype(self.dtype)
x -= 1
out = np.exp(x)
self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
self.attrs = {}
self.outputs = {'Out': out}
def set_mlu(self):
self.__class__.use_mlu = True
def init_dtype(self):
self.dtype = np.float32
def test_check_output(self):
self.check_output_with_place(self.place)
if __name__ == '__main__':
unittest.main()
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