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[Semi-auto] add elementwise spmd rule for auto parallel (PaddlePaddle…
…#54373) * add some basic functions * add elementwise rule for auto parallel * add unit test for elementwise rule * fix the lib name in spmd rule test cmake file * fix some bugs * add unit tests for elementwise spmd rule in python * bug fix * delete cpp unit test for elementwise spmd rule (use python ut now) * add cpp unit test for elementwise rule * use concrete op name in unit test * fix typo * fix code style * delete cpp unit test * add more details in log
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| @@ -1,9 +1,10 @@ | ||
| add_subdirectory(spmd_rules) | ||
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| cc_library( | ||
| op_dist_attr | ||
| SRCS dist_attr.cc | ||
| DEPS phi auto_parallel_proto proto_desc) | ||
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| cc_library(auto_parallel DEPS op_dist_attr spmd_rule) | ||
| cc_library(auto_parallel DEPS op_dist_attr spmd_rules) | ||
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| add_subdirectory(test) | ||
| add_subdirectory(spmd_rules) |
7 changes: 4 additions & 3 deletions
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paddle/fluid/distributed/auto_parallel/spmd_rules/CMakeLists.txt
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| file(GLOB SPMD_SRCS "*.cc") | ||
| file(GLOB spmd_srcs *.cc) | ||
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| cc_library( | ||
| spmd_rule | ||
| SRCS ${SPMD_SRCS} | ||
| spmd_rules | ||
| SRCS ${spmd_srcs} | ||
| DEPS phi) |
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140 changes: 140 additions & 0 deletions
140
paddle/fluid/distributed/auto_parallel/spmd_rules/elementwise_spmd_rule.cc
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| /* 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. */ | ||
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| #include "paddle/fluid/distributed/auto_parallel/spmd_rules/elementwise_spmd_rule.h" | ||
| #include "paddle/phi/core/distributed/auto_parallel/utils.h" | ||
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| namespace paddle { | ||
| namespace distributed { | ||
| namespace auto_parallel { | ||
| using phi::distributed::auto_parallel::str_join; | ||
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| std::pair<std::vector<TensorDistAttr>, std::vector<TensorDistAttr>> | ||
| ElementwiseSPMDRule::InferForward( | ||
| const std::vector<DistTensorSpec>& input_specs, | ||
| const paddle::framework::AttributeMap& attrs) { | ||
| // step0: Verify Input Args Based on Elementwise Logic | ||
| int64_t ninputs = input_specs.size(); | ||
| PADDLE_ENFORCE_GT( | ||
| ninputs, | ||
| 0, | ||
| phi::errors::InvalidArgument("The size of InputSpec in elementwise must " | ||
| "be greater than 0, but got [%d].", | ||
| ninputs)); | ||
| VerifySpecs(input_specs, "elementwise"); | ||
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| // step1: Build Einsum Notation | ||
| std::string alphabet = "abcdefghijklmnopqrstuvwxyz"; | ||
| std::vector<std::string> input_axes_vec; | ||
| int64_t max_ndim = 0; | ||
| for (int64_t i = 0; i < ninputs; ++i) { | ||
| int64_t ndim = input_specs[i].shape().size(); | ||
| if (ndim > max_ndim) { | ||
| max_ndim = ndim; | ||
| } | ||
| } | ||
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| // get einsum notation for each input, deal with broadcast | ||
| std::vector<int64_t> broadcast_axis_count(max_ndim, 0); | ||
| for (int64_t i = 0; i < ninputs; ++i) { | ||
| std::vector<int64_t> shape = input_specs[i].shape(); | ||
| int64_t ndim = shape.size(); | ||
| int64_t start_dim = max_ndim - ndim; | ||
| std::string axes_notation = GetBroadcastAxes(ndim, max_ndim, alphabet); | ||
| if (ninputs > 1) { | ||
| for (int64_t idim = 0; idim < max_ndim; idim++) { | ||
| // deal with the broadcast axes, record the | ||
| // input number at each broadcast axis | ||
| if (idim < start_dim) { | ||
| broadcast_axis_count[idim] += 1; | ||
| } else if (shape[idim - start_dim] == 1) { | ||
| broadcast_axis_count[idim] += 1; | ||
| // mark the broadcast axis to a special "1" | ||
| axes_notation[idim - start_dim] = '1'; | ||
| } | ||
| } | ||
| } | ||
| input_axes_vec.emplace_back(axes_notation); | ||
| } | ||
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| // get einsum notation for output | ||
| std::string output_axes = GetBroadcastAxes(max_ndim, max_ndim, alphabet); | ||
| for (int64_t idim = 0; idim < max_ndim; idim++) { | ||
| // if all inputs broadcast at this dimension, | ||
| // mark this axis in output as broadcast | ||
| if (broadcast_axis_count[idim] == ninputs) { | ||
| output_axes[idim] = '1'; | ||
| } | ||
| } | ||
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| // step2: Sharding Propogation | ||
| // step2.1: merge input shardings | ||
| std::vector<std::pair<std::string, std::vector<int64_t>>> axes_sharding_info; | ||
| axes_sharding_info = GetAxesDimsMappingPair(input_axes_vec, input_specs); | ||
| std::unordered_map<std::string, int64_t> axis_to_dim_map = | ||
| ShardingMergeForTensors(axes_sharding_info); | ||
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| // step2.2: infer output dimsmapping from merged input dimsmapping | ||
| std::vector<int64_t> output_dims_mapping = | ||
| GetDimsMappingForAxes(output_axes, axis_to_dim_map); | ||
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| // initialize output dist_attr's process_mesh, batch_dim and dynamic dims with | ||
| // input dist_attr. | ||
| TensorDistAttr output_dist_attr = | ||
| CopyTensorDistAttrForOutput(input_specs[0].dist_attr()); | ||
| output_dist_attr.set_dims_mapping(output_dims_mapping); | ||
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| std::vector<TensorDistAttr> new_input_dist_attrs; | ||
| std::vector<TensorDistAttr> output_dist_attrs; | ||
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| // step2.3: update inputs' dims mapping with merged one. | ||
| for (int64_t i = 0; i < ninputs; i++) { | ||
| const DistTensorSpec& spec = input_specs[i]; | ||
| TensorDistAttr dist_attr(spec.dist_attr()); | ||
| std::vector<int64_t> new_dims_mapping = | ||
| GetDimsMappingForAxes(input_axes_vec[i], axis_to_dim_map); | ||
| dist_attr.set_dims_mapping(new_dims_mapping); | ||
| new_input_dist_attrs.emplace_back(dist_attr); | ||
| } | ||
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| // step2.4: handle partial | ||
| // Step2.3.2 handle input tensor partial (TODO) | ||
| VLOG(4) << "ElementwiseSPMDRule InferForward:"; | ||
| for (int64_t i = 0; i < ninputs; i++) { | ||
| VLOG(4) << "Input" << std::to_string(i) << " shape: [" | ||
| << str_join(input_specs[i].shape()) << "] " | ||
| << "src_dims_mapping: [" << str_join(input_specs[i].dims_mapping()) | ||
| << "] " | ||
| << "dst_dims_mapping: [" | ||
| << str_join(new_input_dist_attrs[i].dims_mapping()) << "]"; | ||
| } | ||
| VLOG(4) << "Output dims_mapping: [" + str_join(output_dims_mapping) + "]\n\n"; | ||
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| output_dist_attrs.emplace_back(output_dist_attr); | ||
| return {new_input_dist_attrs, output_dist_attrs}; | ||
| } | ||
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| std::pair<std::vector<TensorDistAttr>, std::vector<TensorDistAttr>> | ||
| ElementwiseSPMDRule::InferBackward( | ||
| const std::vector<DistTensorSpec>& output_specs, | ||
| const paddle::framework::AttributeMap& attrs) { | ||
| PADDLE_THROW(phi::errors::Unimplemented( | ||
| "InferBackward of ElementwiseSPMDRule is NOT implemented yet.")); | ||
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| return {}; | ||
| } | ||
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| } // namespace auto_parallel | ||
| } // namespace distributed | ||
| } // namespace paddle |
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40
paddle/fluid/distributed/auto_parallel/spmd_rules/elementwise_spmd_rule.h
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| /* 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. */ | ||
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| #pragma once | ||
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| #include <iterator> | ||
| #include <map> | ||
| #include <string> | ||
| #include <vector> | ||
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| #include "paddle/fluid/distributed/auto_parallel/spmd_rules/common.h" | ||
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| namespace paddle { | ||
| namespace distributed { | ||
| namespace auto_parallel { | ||
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| class ElementwiseSPMDRule : public SPMDRuleBase { | ||
| public: | ||
| std::pair<std::vector<TensorDistAttr>, std::vector<TensorDistAttr>> | ||
| InferForward(const std::vector<DistTensorSpec>& input_specs, | ||
| const paddle::framework::AttributeMap& attrs) override; | ||
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| std::pair<std::vector<TensorDistAttr>, std::vector<TensorDistAttr>> | ||
| InferBackward(const std::vector<DistTensorSpec>& output_specs, | ||
| const paddle::framework::AttributeMap& attrs) override; | ||
| }; | ||
| } // namespace auto_parallel | ||
| } // namespace distributed | ||
| } // namespace paddle |
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