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【Hackathon 5th No.50】 为 Paddle 新增 slice 的 spmd 切分推导规则 (#57866)
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* Add spmd segmentation and derivation rules for slice for Paddle

* fix bugs

* fix bugs

* add unit test code

* modified:   test/auto_parallel/spmd_rules/CMakeLists.txt

* test

* fix bugs

* fix bugs
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WintersMontagne10335 authored Oct 27, 2023
1 parent b07737a commit b83ce89
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6 changes: 6 additions & 0 deletions paddle/phi/infermeta/spmd_rules/rules.h
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Expand Up @@ -25,6 +25,7 @@ limitations under the License. */
#include "paddle/phi/infermeta/spmd_rules/reduction.h"
#include "paddle/phi/infermeta/spmd_rules/replicated.h"
#include "paddle/phi/infermeta/spmd_rules/reshape.h"
#include "paddle/phi/infermeta/spmd_rules/slice.h"
#include "paddle/phi/infermeta/spmd_rules/softmax.h"
#include "paddle/phi/infermeta/spmd_rules/split.h"
#include "paddle/phi/infermeta/spmd_rules/transpose.h"
Expand Down Expand Up @@ -517,6 +518,11 @@ PD_REGISTER_SPMD_RULE(
PD_INFER_SPMD(phi::distributed::SplitWithNumInferSpmd),
PD_INFER_SPMD(phi::distributed::SplitWithNumInferSpmdReverse));

// slice rule
PD_REGISTER_SPMD_RULE(slice,
PD_INFER_SPMD(phi::distributed::SliceInferSpmd),
PD_INFER_SPMD(phi::distributed::SliceInferSpmdReverse));

// transpose rule
PD_REGISTER_SPMD_RULE(
transpose,
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176 changes: 176 additions & 0 deletions paddle/phi/infermeta/spmd_rules/slice.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,176 @@
/* Copyright (c) 2023 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/phi/infermeta/spmd_rules/slice.h"

#include "glog/logging.h"

#include "paddle/phi/core/distributed/auto_parallel/dist_attr.h"
#include "paddle/phi/core/distributed/auto_parallel/inferspmd_utils.h"
#include "paddle/phi/core/distributed/auto_parallel/utils.h"
#include "paddle/phi/infermeta/spmd_rules/utils.h"

namespace phi {
namespace distributed {

using phi::distributed::auto_parallel::str_join;

SpmdInfo SliceInferSpmd(const DistMetaTensor& input,
const std::vector<int64_t>& axes,
const std::vector<int>& starts,
const std::vector<int>& ends,
const std::vector<int64_t>& infer_flags,
const std::vector<int64_t>& decrease_axis) {
auto input_shape = phi::vectorize(input.dims());
int input_ndim = input_shape.size();
auto input_dist_attr_src = input.dist_attr();
std::vector<int64_t> input_dims_mapping = input_dist_attr_src.dims_mapping();
PADDLE_ENFORCE_EQ(
input_ndim,
input_dims_mapping.size(),
phi::errors::InvalidArgument("The Tensor Input's rank [%d] and Input's "
"dims_mapping size [%d] are not matched.",
input_ndim,
input_dims_mapping.size()));

std::string alphabet = "abcdefghijklmnopqrstuvwxyz";
std::string input_axes = alphabet.substr(0, input_ndim);
std::string special_axes = alphabet.substr(input_ndim);

for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
input_axes[axis] = special_axes[i];
}

std::string out_axes(input_axes);

for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
out_axes[axis] = '1';
}

std::unordered_map<std::string, int64_t> axis_to_dim_map =
ShardingMergeForTensors({{input_axes, input_dims_mapping}});

std::vector<int64_t> out_dims_mapping =
GetDimsMappingForAxes(out_axes, axis_to_dim_map);

TensorDistAttr out_dist_attr =
CopyTensorDistAttrForOutput(input_dist_attr_src);
out_dist_attr.set_dims_mapping(out_dims_mapping);

TensorDistAttr input_dist_attr_dst(input_dist_attr_src);
for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
input_dims_mapping[axis] = -1;
}
input_dist_attr_dst.set_dims_mapping(input_dims_mapping);

VLOG(4) << "SliceInferSpmd:";
VLOG(4) << "Einsum Notation: " << input_axes << "-->" << out_axes;
VLOG(4) << "Input shape: [" << str_join(input_shape) << "] "
<< "src_dims_mapping: ["
<< str_join(input_dist_attr_src.dims_mapping()) << "] "
<< "dst_dims_mapping: [" << str_join(input_dims_mapping) << "]";
VLOG(4) << "Output"
<< " dims_mapping: [" << str_join(out_dims_mapping) << "]";
VLOG(4) << std::endl;

return {{input_dist_attr_dst}, {out_dist_attr}};
}

SpmdInfo SliceInferSpmdReverse(const DistMetaTensor& input,
const DistMetaTensor& output,
const std::vector<int64_t>& axes,
const std::vector<int>& starts,
const std::vector<int>& ends,
const std::vector<int64_t>& infer_flags,
const std::vector<int64_t>& decrease_axis) {
auto output_shape = phi::vectorize(output.dims());
int out_ndim = output_shape.size();
auto out_dist_attr = output.dist_attr();
int out_dims_mapping_size = out_dist_attr.dims_mapping().size();
auto input_shape = phi::vectorize(input.dims());
int input_ndim = input_shape.size();
auto input_dist_attr = input.dist_attr();
std::vector<int64_t> input_dims_mapping = input_dist_attr.dims_mapping();

PADDLE_ENFORCE_EQ(
input_ndim,
out_ndim,
phi::errors::InvalidArgument("The Tensor Input's rank [%d] is not equal "
"to the Tensor Output's rank [%d]",
input_ndim,
out_ndim));

PADDLE_ENFORCE_EQ(
out_ndim,
out_dims_mapping_size,
phi::errors::InvalidArgument("The Tensor Output's rank [%d] and Its "
"dims_mapping size [%d] are not matched.",
out_ndim,
out_dims_mapping_size));

std::string alphabet = "abcdefghijklmnopqrstuvwxyz";
std::string input_axes = alphabet.substr(0, input_ndim);
std::string special_axes = alphabet.substr(input_ndim);

for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
input_axes[axis] = special_axes[i];
}

std::string out_axes(input_axes);

for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
out_axes[axis] = special_axes[i];
}

std::vector<std::pair<std::string, std::vector<int64_t>>> axes_sharding_info;
std::vector<int64_t> out_dims_mapping = output.dist_attr().dims_mapping();
axes_sharding_info.emplace_back(std::make_pair(out_axes, out_dims_mapping));

std::unordered_map<std::string, int64_t> axis_to_dim_map =
ShardingMergeForTensors(axes_sharding_info);

input_dims_mapping = GetDimsMappingForAxes(input_axes, axis_to_dim_map, true);
for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
input_dims_mapping[axis] = -1;
}
input_dist_attr.set_dims_mapping(input_dims_mapping);
out_dims_mapping = GetDimsMappingForAxes(out_axes, axis_to_dim_map, true);
for (int i = 0; i < static_cast<int>(axes.size()); i++) {
int axis = axes[i] < 0 ? axes[i] + input_ndim : axes[i];
out_dims_mapping[axis] = -1;
}
out_dist_attr.set_dims_mapping(out_dims_mapping);

VLOG(4) << "SliceInferSpmdReverse:";
VLOG(4) << "Einsum Notation: " << input_axes << "-->" << out_axes;
VLOG(4) << "Output"
<< " shape: [" << str_join(phi::vectorize(output.dims())) << "] "
<< "src_dims_mapping: ["
<< str_join(output.dist_attr().dims_mapping()) << "] "
<< "dst_dims_mapping: [" << str_join(out_dist_attr.dims_mapping())
<< "]";
VLOG(4) << "Input shape: [" << str_join(input_shape) << "] "
<< "dims_mapping: [" << str_join(input_dims_mapping) << "]\n\n";

return {{input_dist_attr}, {out_dist_attr}};
}

} // namespace distributed
} // namespace phi
44 changes: 44 additions & 0 deletions paddle/phi/infermeta/spmd_rules/slice.h
Original file line number Diff line number Diff line change
@@ -0,0 +1,44 @@
/* Copyright (c) 2023 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 <iterator>
#include <map>
#include <string>
#include <vector>

#include "paddle/phi/core/distributed/auto_parallel/dist_meta_tensor.h"
#include "paddle/phi/core/distributed/type_defs.h"

namespace phi {
namespace distributed {

SpmdInfo SliceInferSpmd(const DistMetaTensor& input,
const std::vector<int64_t>& axes,
const std::vector<int>& starts,
const std::vector<int>& ends,
const std::vector<int64_t>& infer_flags,
const std::vector<int64_t>& decrease_axis);

SpmdInfo SliceInferSpmdReverse(const DistMetaTensor& input,
const DistMetaTensor& output,
const std::vector<int64_t>& axes,
const std::vector<int>& starts,
const std::vector<int>& ends,
const std::vector<int64_t>& infer_flags,
const std::vector<int64_t>& decrease_axis);

} // namespace distributed
} // namespace phi
1 change: 1 addition & 0 deletions test/auto_parallel/spmd_rules/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@ if(WITH_DISTRIBUTE)
py_test_modules(test_default_data_parallel_rule MODULES
test_default_data_parallel_rule)
py_test_modules(test_layer_norm_rule MODULES test_layer_norm_rule)
py_test_modules(test_slice_rule MODULES test_slice_rule)
py_test_modules(test_flatten_rule MODULES test_flatten_rule)
# End of unittests WITH single card WITHOUT timeout

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