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Added softplus FP32 FWD OneDNN kernel #36382

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20 changes: 20 additions & 0 deletions paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc
Original file line number Diff line number Diff line change
Expand Up @@ -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 {
Expand Down Expand Up @@ -169,6 +170,20 @@ struct GeluMKLDNNGradFunctor : public BaseActivationFunctor<T> {
}
};

template <typename T>
struct SoftplusMKLDNNFunctor : public BaseActivationFunctor<T> {
void operator()(const framework::ExecutionContext &ctx) const {
const float beta = ctx.Attr<float>("beta");
// if beta is equal to 1.0f then we can simply use oneDNN's soft_relu but if
// it has other value, we have to fuse binary + eltwise + binary
if (beta == 1.0f) {
eltwise_forward<T>(ctx, mkldnn::algorithm::eltwise_soft_relu);
} else {
custom_softplus_eltwise_forward<T>(ctx);
}
}
};

template <typename T>
using ReluMKLDNNFunctor =
MKLDNNActivationFunc<T, mkldnn::algorithm::eltwise_relu>;
Expand Down Expand Up @@ -272,3 +287,8 @@ 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>>);
91 changes: 91 additions & 0 deletions paddle/fluid/operators/mkldnn/softplus_mkldnn_op.h
Original file line number Diff line number Diff line change
@@ -0,0 +1,91 @@
/* 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);
post_ops.append_binary(dnnl::algorithm::binary_div, beta_md);
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},
{DNNL_ARG_ATTR_MULTIPLE_POST_OP(1) | DNNL_ARG_SRC_1, *beta_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
Original file line number Diff line number Diff line change
@@ -0,0 +1,77 @@
# 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
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import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core


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()