未验证 提交 bdac9ff6 编写于 作者: J jakpiase 提交者: GitHub

Added softplus FP32 FWD OneDNN kernel (#36382)

* added softplus

* refactored softplus op

* deleted unnecessary file

* added missing file

* added formatting

* disabled tests if GPU is used

* added reviewer suggestion

* unified softplus kernel
上级 4c0ad772
......@@ -13,6 +13,7 @@
limitations under the License. */
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/operators/mkldnn/softplus_mkldnn_op.h"
#include "paddle/fluid/platform/mkldnn_reuse.h"
namespace paddle {
......@@ -169,6 +170,13 @@ struct GeluMKLDNNGradFunctor : public BaseActivationFunctor<T> {
}
};
template <typename T>
struct SoftplusMKLDNNFunctor : public BaseActivationFunctor<T> {
void operator()(const framework::ExecutionContext &ctx) const {
custom_softplus_eltwise_forward<T>(ctx);
}
};
template <typename T>
using ReluMKLDNNFunctor =
MKLDNNActivationFunc<T, mkldnn::algorithm::eltwise_relu>;
......@@ -272,3 +280,8 @@ REGISTER_ACTIVATION_MKLDNN_BF16_KERNEL(gelu, GeluMKLDNNFunctor,
GeluMKLDNNGradFunctor);
REGISTER_ACTIVATION_MKLDNN_BF16_KERNEL(sigmoid, SigmoidMKLDNNFunctor,
SigmoidMKLDNNGradFunctor);
namespace ops = paddle::operators;
REGISTER_OP_KERNEL(
softplus, MKLDNN, paddle::platform::CPUPlace,
ops::MKLDNNActivationKernel<ops::SoftplusMKLDNNFunctor<float>>);
/* 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/platform/mkldnn_reuse.h"
namespace paddle {
namespace operators {
using paddle::framework::Tensor;
template <typename T>
class SoftplusMKLDNNHandler
: public platform::MKLDNNHandlerNoCachingT<T, dnnl::binary> {
public:
SoftplusMKLDNNHandler(const Tensor* x, const float beta,
const mkldnn::engine engine, platform::Place cpu_place)
: platform::MKLDNNHandlerNoCachingT<T, dnnl::binary>(engine, cpu_place) {
auto x_tz = framework::vectorize(x->dims());
auto x_md =
dnnl::memory::desc(x_tz, platform::MKLDNNGetDataType<T>(), x->format());
auto beta_tz = std::vector<int64_t>(x_tz.size(), 1);
auto beta_md = dnnl::memory::desc(beta_tz, platform::MKLDNNGetDataType<T>(),
x->format());
dnnl::post_ops post_ops;
post_ops.append_eltwise(1.0f, dnnl::algorithm::eltwise_soft_relu, 0.0f,
0.0f);
if (beta != 1.0f) {
post_ops.append_eltwise(1.0f, dnnl::algorithm::eltwise_linear,
1.0f / beta, 0.0f);
}
dnnl::primitive_attr attrs;
attrs.set_post_ops(post_ops);
this->AcquireForwardPrimitiveDescriptor(attrs, dnnl::algorithm::binary_mul,
x_md, beta_md, x_md);
}
std::shared_ptr<mkldnn::memory> AcquireBetaMemory(const float* beta) {
return this->AcquireMemoryFromPrimitive(
this->fwd_pd_->src1_desc(), platform::to_void_cast<float>(beta));
}
};
template <typename T>
void custom_softplus_eltwise_forward(const framework::ExecutionContext& ctx) {
const auto& dev_ctx =
ctx.template device_context<platform::MKLDNNDeviceContext>();
const auto& mkldnn_engine = dev_ctx.GetEngine();
const auto* x = ctx.Input<Tensor>("X");
auto* out = ctx.Output<Tensor>("Out");
bool is_inplaced = x->IsSharedBufferWith(*out);
const float beta = ctx.Attr<float>("beta");
SoftplusMKLDNNHandler<T> handler(x, beta, mkldnn_engine, ctx.GetPlace());
auto src_memory_p = handler.AcquireSrcMemory(x);
auto beta_memory_p = handler.AcquireBetaMemory(&beta);
auto dst_memory_p =
is_inplaced ? src_memory_p : handler.AcquireDstMemory(out);
auto binary_p = handler.AcquireForwardPrimitive();
auto& astream = paddle::platform::MKLDNNDeviceContext::tls().get_stream();
const std::unordered_map<int, dnnl::memory> args = {
{DNNL_ARG_SRC_0, *src_memory_p},
{DNNL_ARG_SRC_1, *beta_memory_p},
{DNNL_ARG_DST, *dst_memory_p}};
binary_p->execute(astream, args);
astream.wait();
out->set_layout(framework::DataLayout::kMKLDNN);
out->set_format(platform::GetMKLDNNFormat(*dst_memory_p));
}
} // namespace operators
} // namespace paddle
# 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 unittest
import numpy as np
from paddle.fluid.tests.unittests.op_test import OpTest, OpTestTool
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid.framework import _current_expected_place
def ref_softplus(x, beta, threshold):
x_beta = beta * x
out = np.select([x_beta <= threshold, x_beta > threshold],
[np.log(1 + np.exp(x_beta)) / beta, x])
return out
@OpTestTool.skip_if(not (isinstance(_current_expected_place(), core.CPUPlace)),
"GPU is not supported")
class TestSoftplusOneDNNOp(OpTest):
def setUp(self):
self.op_type = "softplus"
self.beta = 1
self.threshold = 20
self.config()
self.attrs = {'use_mkldnn': True, 'beta': self.beta}
self.inputs = {'X': np.random.random(self.x_shape).astype(np.float32)}
self.outputs = {
'Out': ref_softplus(self.inputs['X'], self.beta, self.threshold)
}
def config(self):
self.x_shape = (10, 10)
def test_check_output(self):
self.check_output()
class TestSoftplus4DOneDNNOp(TestSoftplusOneDNNOp):
def config(self):
self.x_shape = (10, 5, 4, 2)
class TestSoftplus6DOneDNNOp(TestSoftplusOneDNNOp):
def config(self):
self.x_shape = (3, 2, 2, 5, 4, 2)
class TestSoftplus6DExtendedFunctorOneDNNOp(TestSoftplusOneDNNOp):
def config(self):
self.x_shape = (3, 5, 2, 5, 4, 2)
self.beta = 2.5
class TestSoftplus3DExtendedFunctorOneDNNOp(TestSoftplusOneDNNOp):
def config(self):
self.x_shape = (20, 4, 2)
self.beta = 0.4
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
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