wehub-resource-sync
371 lines
12 KiB
Python
371 lines
12 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License
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from __future__ import annotations
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from collections import defaultdict
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from typing import TYPE_CHECKING, TypedDict
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if TYPE_CHECKING:
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from paddle import Tensor
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from paddle._typing.dtype_like import _DTypeLiteral
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# _g_default_config[category][field] = default_value
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_g_default_config = defaultdict(dict)
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def get_category_default_config(category):
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return _g_default_config[category]
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def set_category_default_config(category, default_value):
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_g_default_config[category] = default_value
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def get_field_default_config(category, field):
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return _g_default_config[category][field]
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def set_field_default_config(category, field, default_value):
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_g_default_config[category][field] = default_value
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NOT_FOUND = "not_found"
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#########################################
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# base configuration
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#########################################
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BASE = "base"
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set_field_default_config(BASE, "auto_mode", "semi")
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set_field_default_config(BASE, "gradient_scale", True)
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set_field_default_config(BASE, "gradient_scale_using_allreduce_avg", False)
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set_field_default_config(BASE, "use_cache", True)
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set_field_default_config(BASE, "return_numpy", True)
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set_field_default_config(BASE, "all_ranks", False)
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set_field_default_config(BASE, "split_data", True)
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set_field_default_config(BASE, "seed", None)
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set_field_default_config(BASE, "reinit", False) # Only for debug
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if TYPE_CHECKING:
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class _BaseConfig(TypedDict, total=False): # noqa: PYI049
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auto_mode: str
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gradient_scale: bool
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gradient_scale_using_allreduce_avg: bool
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use_cache: bool
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return_numpy: bool
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all_ranks: bool
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split_data: bool
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seed: int | None
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reinit: bool
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#########################################
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# recompute configuration
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#########################################
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RECOMPUTE = "recompute"
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set_field_default_config(RECOMPUTE, "enable", False)
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set_field_default_config(RECOMPUTE, "checkpoints", [])
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set_field_default_config(RECOMPUTE, "no_recompute_segments", [])
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set_field_default_config(RECOMPUTE, "sr", 0)
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set_field_default_config(RECOMPUTE, "refined_ops_patterns", []) # List[Dict]
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set_field_default_config(RECOMPUTE, "enable_tuning", False)
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if TYPE_CHECKING:
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class _RefinedOpsPatterns(TypedDict, total=False):
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main_ops: list[str]
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num: int
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pre_ops: list[str]
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suf_ops: list[str]
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class _RecomputeConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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checkpoints: list[Tensor]
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no_recompute_segments: list[int]
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sr: int
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refined_ops_patterns: list[_RefinedOpsPatterns]
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enable_tuning: bool
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#########################################
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# AMP configuration
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#########################################
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AMP = "amp"
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set_field_default_config(AMP, "enable", False)
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set_field_default_config(AMP, "dtype", "float16")
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set_field_default_config(AMP, "level", "o1")
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set_field_default_config(AMP, "init_loss_scaling", 32768.0)
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set_field_default_config(AMP, "incr_every_n_steps", 1000)
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set_field_default_config(AMP, "decr_every_n_nan_or_inf", 2)
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set_field_default_config(AMP, "incr_ratio", 2.0)
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set_field_default_config(AMP, "decr_ratio", 0.8)
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set_field_default_config(AMP, "use_dynamic_loss_scaling", True)
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set_field_default_config(AMP, "custom_white_list", [])
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set_field_default_config(AMP, "custom_black_list", [])
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set_field_default_config(AMP, "custom_black_varnames", [])
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set_field_default_config(AMP, "use_fp16_guard", False)
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set_field_default_config(AMP, "use_bf16_guard", False)
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set_field_default_config(AMP, "use_master_grad", False)
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set_field_default_config(AMP, "use_promote", True)
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if TYPE_CHECKING:
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class _AMPConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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dtype: _DTypeLiteral
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level: str
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init_loss_scaling: float
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incr_every_n_steps: int
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decr_every_n_nan_or_inf: int
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incr_ratio: float
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decr_ratio: float
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use_dynamic_loss_scaling: bool
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custom_white_list: list[str]
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custom_black_list: list[str]
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custom_black_varnames: list[str]
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use_fp16_guard: bool
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use_bf16_guard: bool
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use_master_grad: bool
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use_promote: bool
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#########################################
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# sharding configuration
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#########################################
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SHARDING = "sharding"
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set_field_default_config(SHARDING, "enable", False)
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set_field_default_config(SHARDING, "stage", 1)
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set_field_default_config(SHARDING, "degree", 8)
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set_field_default_config(SHARDING, "enable_overlap", False)
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set_field_default_config(SHARDING, "param_comm_stream_num", 1)
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set_field_default_config(SHARDING, "grad_comm_stream_num", 1)
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set_field_default_config(SHARDING, "param_bucket_size_numel", 1)
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set_field_default_config(SHARDING, "grad_bucket_size_numel", 1)
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set_field_default_config(SHARDING, "enable_hierarchical_comm", False)
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set_field_default_config(SHARDING, "partition_algor", "greedy_even")
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set_field_default_config(SHARDING, "enable_tuning", False)
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set_field_default_config(SHARDING, "tuning_range", [])
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set_field_default_config(SHARDING, "release_gradients", False)
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set_field_default_config(SHARDING, "comm_buffer_size_MB", 256)
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set_field_default_config(SHARDING, "enable_tensor_fusion", False)
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set_field_default_config(SHARDING, "save_unbalanced_param", True)
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if TYPE_CHECKING:
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class _ShardingConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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stage: int
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degree: int
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enable_overlap: bool
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param_comm_stream_num: int
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grad_comm_stream_num: int
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param_bucket_size_numel: int
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grad_bucket_size_numel: int
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enable_hierarchical_comm: bool
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partition_algor: str
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enable_tuning: bool
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tuning_range: list[int] | tuple[int, int]
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#########################################
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# gradient merge configuration
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#########################################
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GRADIENT_MERGE = "gradient_merge"
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set_field_default_config(GRADIENT_MERGE, "enable", False)
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set_field_default_config(GRADIENT_MERGE, "k_steps", 1)
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set_field_default_config(GRADIENT_MERGE, "avg", True)
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if TYPE_CHECKING:
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class _GradientMergeConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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k_steps: int
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avg: bool
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#########################################
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# pipeline configuration
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#########################################
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PIPELINE = "pipeline"
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set_field_default_config(PIPELINE, "enable", False)
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set_field_default_config(PIPELINE, "schedule_mode", "1F1B")
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set_field_default_config(PIPELINE, "pp_degree", 1)
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set_field_default_config(PIPELINE, "vpp_degree", 1)
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set_field_default_config(PIPELINE, "vpp_seg_method", "")
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set_field_default_config(PIPELINE, "micro_batch_size", 1)
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set_field_default_config(PIPELINE, "accumulate_steps", 1)
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set_field_default_config(PIPELINE, "generation_batch_size", 1)
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set_field_default_config(PIPELINE, "enable_send_recv_overlap", False)
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set_field_default_config(PIPELINE, "job_schedule_profiler_start", -1)
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set_field_default_config(PIPELINE, "job_schedule_profiler_stop", -1)
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set_field_default_config(PIPELINE, "program_runtimes", [61, 72, 71, 34, 3])
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set_field_default_config(PIPELINE, "memory_limit_times", -1)
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set_field_default_config(PIPELINE, "split_backward", False)
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set_field_default_config(PIPELINE, "auto_parallel_sync_shared_params", False)
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if TYPE_CHECKING:
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class _PipelineConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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schedule_mode: str
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pp_degree: int
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vpp_degree: int
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vpp_seg_method: str
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micro_batch_size: int
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accumulate_steps: int
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generation_batch_size: int
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enable_send_recv_overlap: bool
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job_schedule_profiler_start: int
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job_schedule_profiler_stop: int
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split_backward: bool
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auto_parallel_sync_shared_params: bool
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#########################################
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# quantization configuration
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#########################################
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QAT = "qat"
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set_field_default_config(QAT, "enable", False)
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set_field_default_config(QAT, "channel_wise_abs_max", True)
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set_field_default_config(QAT, "weight_bits", 8)
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set_field_default_config(QAT, "activation_bits", 8)
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set_field_default_config(QAT, "not_quant_pattern", ['skip_quant'])
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set_field_default_config(QAT, "algo", None)
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set_field_default_config(QAT, "onnx_format", True)
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if TYPE_CHECKING:
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class _QATConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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channel_wise_abs_max: bool
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weight_bits: int
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activation_bits: int
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not_quant_pattern: list[str]
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algo: str | None
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onnx_format: bool
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#########################################
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# auto tuning configuration
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#########################################
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TUNING = "tuning"
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set_field_default_config(TUNING, "enable", False)
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set_field_default_config(TUNING, "profile_start_step", 1)
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set_field_default_config(TUNING, "profile_end_step", 1)
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set_field_default_config(TUNING, "run_after_tuning", True)
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set_field_default_config(TUNING, "debug", False)
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if TYPE_CHECKING:
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class _TuningConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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profile_start_step: int
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profile_end_step: int
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run_after_tuning: bool
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debug: bool
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#########################################
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# dataset configuration
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#########################################
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DATASET = "dataset"
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set_field_default_config(DATASET, "enable", False)
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set_field_default_config(DATASET, "num_shards", 1)
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if TYPE_CHECKING:
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class _DatasetConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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num_shards: int
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# #########################################
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# # offload configuration
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# #########################################
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FUSEDLINEARPROMOTION = "fused_linear_promotion"
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set_field_default_config(FUSEDLINEARPROMOTION, "enable", False)
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if TYPE_CHECKING:
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class _FusedLinearPromotionConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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#########################################
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# fused passes configuration
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#########################################
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FUSED_PASSES = "fused_passes"
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set_field_default_config(FUSED_PASSES, "enable", False)
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set_field_default_config(FUSED_PASSES, "fused_passes_list", [])
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if TYPE_CHECKING:
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class _FusedPassesConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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fused_passes_list: list[str]
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#########################################
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# data parallel configuration
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#########################################
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DP_OPTIMIZATION = "dp_optimization"
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set_field_default_config(DP_OPTIMIZATION, "enable", False)
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set_field_default_config(DP_OPTIMIZATION, "fuse_all_reduce_ops", True)
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set_field_default_config(DP_OPTIMIZATION, "fuse_grad_size_in_MB", 32)
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set_field_default_config(DP_OPTIMIZATION, "overlap_comm_cacl", True)
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set_field_default_config(
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DP_OPTIMIZATION, "gradient_sync_after_accumulate", False
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)
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if TYPE_CHECKING:
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class _DPOptimizationConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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fuse_all_reduce_ops: bool
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fuse_grad_size_in_MB: int
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overlap_comm_cacl: bool
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gradient_sync_after_accumulate: bool
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#########################################
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# model parallel configuration
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#########################################
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MP_OPTIMIZATION = "mp_optimization"
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set_field_default_config(
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MP_OPTIMIZATION, "allreduce_matmul_grad_overlapping", False
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)
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set_field_default_config(MP_OPTIMIZATION, "replace_with_c_embedding", False)
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set_field_default_config(
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MP_OPTIMIZATION, "replace_with_parallel_cross_entropy", False
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)
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if TYPE_CHECKING:
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class _MPOptimizationConfig(TypedDict, total=False): # noqa: PYI049
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allreduce_matmul_grad_overlapping: bool
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#########################################
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# sequence parallel configuration
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#########################################
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SP_OPTIMIZATION = "sp_optimization"
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set_field_default_config(SP_OPTIMIZATION, "enable", True)
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if TYPE_CHECKING:
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class _SPOptimizationConfig(TypedDict, total=False): # noqa: PYI049
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enable: bool
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