未验证 提交 e2e1c57b 编写于 作者: Y Yuang Liu 提交者: GitHub

softmax mask fuse upper triangle (#33981)

* softmax mask fuse upper triangle

* cover not implemented cpu code
上级 bfbea8fd
/* 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/softmax_mask_fuse_upper_triangle_op.h"
#include "paddle/fluid/framework/generator.h"
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
using framework::Tensor;
class SoftmaxMaskFuseUpperTriangleOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X",
"SoftmaxMaskFuseUpperTriangle");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
"SoftmaxMaskFuseUpperTriangle");
auto x_dims = ctx->GetInputDim("X");
PADDLE_ENFORCE_EQ(
x_dims.size(), 4,
platform::errors::InvalidArgument("Input x must be in 4D dimension but "
"received the dimension of X is %d",
x_dims.size()));
ctx->SetOutputDim("Out", x_dims);
ctx->ShareLoD("X", "Out");
}
};
class SoftmaxMaskFuseUpperTriangleOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X",
"The input of softmax_mask_fuse_upper_triangle op, "
"which is the result of matmul(QK)/sqrt(dk).");
AddOutput("Out", "The result of softmax_mask_fuse_upper_triangle op.");
AddComment(R"DOC(
Softmax Mask Fuse Operator.
product = matmul(QK)/sqrt(dk)
output = softmax_mask_fuse_upper_triangle(product)
to get the final output.
)DOC");
}
};
class SoftmaxMaskFuseUpperTriangleOpGrad
: public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
framework::GradVarName("Out"),
"SoftmaxMaskFuseUpperTriangleGrad");
auto out_dims = ctx->GetInputDim(framework::GradVarName("Out"));
ctx->SetOutputDim(framework::GradVarName("X"), out_dims);
ctx->ShareLoD(framework::GradVarName("Out"), framework::GradVarName("X"));
}
};
template <typename T>
class SoftmaxMaskFuseUpperTriangleGradOpMaker
: public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
void Apply(GradOpPtr<T> op) const override {
op->SetType("softmax_mask_fuse_upper_triangle_grad");
op->SetInput("Softmax", this->Output("Out"));
op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(
softmax_mask_fuse_upper_triangle, ops::SoftmaxMaskFuseUpperTriangleOp,
ops::SoftmaxMaskFuseUpperTriangleOpMaker,
ops::SoftmaxMaskFuseUpperTriangleGradOpMaker<paddle::framework::OpDesc>,
ops::SoftmaxMaskFuseUpperTriangleGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(softmax_mask_fuse_upper_triangle_grad,
ops::SoftmaxMaskFuseUpperTriangleOpGrad);
REGISTER_OP_CPU_KERNEL(softmax_mask_fuse_upper_triangle,
ops::SoftmaxMaskFuseUpperTriangleCPUKernel<
paddle::platform::CPUDeviceContext, float>,
ops::SoftmaxMaskFuseUpperTriangleCPUKernel<
paddle::platform::CPUDeviceContext, double>);
/* 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. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class SoftmaxMaskFuseUpperTriangleCPUKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
PADDLE_ENFORCE_EQ(platform::is_gpu_place(ctx.GetPlace()), true,
platform::errors::Unimplemented(
"Softmax mask fuse op only supports GPU now."));
}
};
} // 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
import paddle.fluid.core as core
from op_test import OpTest
import paddle
import paddle.fluid as fluid
import paddle.incubate as incubate
paddle.enable_static()
def _get_softmax_upper(x, fp16=True):
x_lower = np.tril(x)
masked_x = np.where(x_lower == 0, -10000.0, x_lower).astype("float32")
max_value = np.max(masked_x, axis=-1, keepdims=True)
before_exp = masked_x - max_value
exp = np.exp(before_exp)
exp_sum = np.sum(exp, axis=-1, keepdims=True)
rst = exp / exp_sum
if fp16:
rst = rst.astype("float16")
return rst
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestSoftmaxMaskFuseOp(OpTest):
def setUp(self):
self.op_type = "softmax_mask_fuse_upper_triangle"
x = np.random.random((1, 1, 32, 32)).astype("float16")
self.inputs = {'X': x}
rst = _get_softmax_upper(x)
self.outputs = {'Out': rst}
def test_check_output(self):
self.check_output_with_place(core.CUDAPlace(0))
def test_check_grad(self):
self.check_grad_with_place(core.CUDAPlace(0), ["X"], "Out")
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestSoftmaxMaskFuseOp1(OpTest):
def setUp(self):
self.op_type = "softmax_mask_fuse_upper_triangle"
x = np.random.random((1, 1, 32, 32))
self.inputs = {'X': x}
rst = _get_softmax_upper(x)
self.outputs = {'Out': rst}
def test_check_output(self):
try:
self.check_output_with_place(core.CPUPlace())
except NotImplementedError:
pass
def test_check_grad(self):
try:
self.check_grad_with_place(core.CPUPlace(), ["X"], "Out")
except NotImplementedError:
pass
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestDropoutBiasFuseOp2(unittest.TestCase):
# test the python side API for softmax_mask_fuse op
def setUp(self):
np.random.seed(123)
self.dtypes = ['float16', 'float32']
def test_static(self):
for dtype in self.dtypes:
with fluid.program_guard(fluid.Program(), fluid.Program()):
input_x = fluid.data(
name="x", shape=[1, 1, 32, 32], dtype=dtype)
rst = incubate.softmax_mask_fuse_upper_triangle(input_x)
x_in_np = np.random.random((1, 1, 32, 32)).astype(dtype)
rst_np = _get_softmax_upper(x_in_np, dtype == 'float16')
exe = fluid.Executor(fluid.CUDAPlace(0))
fetches = exe.run(fluid.default_main_program(),
feed={"x": x_in_np},
fetch_list=[rst])
self.assertTrue(np.allclose(fetches[0], rst_np))
def test_dygraph(self):
for dtype in self.dtypes:
with fluid.dygraph.guard(fluid.CUDAPlace(0)):
x_in_np = np.random.random((1, 1, 32, 32)).astype(dtype)
rst_np = _get_softmax_upper(x_in_np, dtype == 'float16')
input_x = fluid.dygraph.to_variable(x_in_np)
rst = incubate.softmax_mask_fuse_upper_triangle(input_x)
self.assertTrue(np.allclose(rst, rst_np))
if __name__ == '__main__':
unittest.main()
...@@ -16,7 +16,8 @@ from .optimizer import LookAhead # noqa: F401 ...@@ -16,7 +16,8 @@ from .optimizer import LookAhead # noqa: F401
from .optimizer import ModelAverage # noqa: F401 from .optimizer import ModelAverage # noqa: F401
from .checkpoint import auto_checkpoint # noqa: F401 from .checkpoint import auto_checkpoint # noqa: F401
from ..fluid.layer_helper import LayerHelper # noqa: F401 from ..fluid.layer_helper import LayerHelper # noqa: F401
from .operators import softmax_mask_fuse_upper_triangle # noqa: F401
__all__ = [ # noqa __all__ = [ # noqa
'LookAhead', 'ModelAverage' 'LookAhead', 'ModelAverage', 'softmax_mask_fuse_upper_triangle'
] ]
# 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 .softmax_mask_fuse_upper_triangle import softmax_mask_fuse_upper_triangle # noqa: F401
# 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
from paddle.fluid.layer_helper import LayerHelper
from paddle.fluid.framework import in_dygraph_mode
from paddle.fluid import core
def softmax_mask_fuse_upper_triangle(x):
"""
Fuse softmax mask together without even give a mask.
Under GPT model, the mask is always be a upper triangle
so we can simply mask the upper triangle part of x to get the mask result
:param x: the input x (rst of QK)
:return: the result of softmax mask fuse (upper triangle)
"""
if in_dygraph_mode():
out = core.ops.softmax_mask_fuse_upper_triangle(x)
return out
helper = LayerHelper('softmax_mask_fuse_upper_triangle', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
type='softmax_mask_fuse_upper_triangle',
inputs={'X': [x]},
outputs={'Out': [out]})
return out
...@@ -146,6 +146,7 @@ packages=['paddle', ...@@ -146,6 +146,7 @@ packages=['paddle',
'paddle.incubate', 'paddle.incubate',
'paddle.incubate.optimizer', 'paddle.incubate.optimizer',
'paddle.incubate.checkpoint', 'paddle.incubate.checkpoint',
'paddle.incubate.operators',
'paddle.distributed.fleet', 'paddle.distributed.fleet',
'paddle.distributed.fleet.base', 'paddle.distributed.fleet.base',
'paddle.distributed.fleet.meta_optimizers', 'paddle.distributed.fleet.meta_optimizers',
......
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