remove dynamic module loader monkeypatch as this was fixed upstream (#1914)
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83
examples/deepseek-v2/qlora-fsdp-2_5.yaml
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83
examples/deepseek-v2/qlora-fsdp-2_5.yaml
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@@ -0,0 +1,83 @@
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base_model: axolotl-quants/DeepSeek-V2.5-bnb-nf4-bf16
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trust_remote_code: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rms_norm: true
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liger_swiglu: true
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liger_fused_linear_cross_entropy: true
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chat_template: deepseek_v2
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datasets:
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- path: mlabonne/FineTome-100k
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type: chat_template
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split: train
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.0
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output_dir: ./outputs/out
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sequence_len: 4096
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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adapter: qlora
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lora_r: 256
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lora_alpha: 256
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lora_target_linear: true
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peft_use_rslora: true
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gradient_accumulation_steps: 1
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micro_batch_size: 8
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num_epochs: 1
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 2e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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evals_per_epoch: 2
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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special_tokens:
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fsdp:
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- full_shard
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- auto_wrap
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fsdp_config:
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fsdp_limit_all_gathers: true
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fsdp_sync_module_states: true
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fsdp_offload_params: true
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fsdp_use_orig_params: false
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fsdp_cpu_ram_efficient_loading: true
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_transformer_layer_cls_to_wrap: DeepseekV2DecoderLayer
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_sharding_strategy: FULL_SHARD
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@@ -1,11 +1,11 @@
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--extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
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packaging==23.2
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peft==0.12.0
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transformers==4.44.2
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transformers @ git+https://github.com/huggingface/transformers.git@0963229e287501bed52ae1dabc17922524de6992
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tokenizers>=0.19.1
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bitsandbytes==0.43.3
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accelerate==0.34.2
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datasets==2.20.0
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datasets==2.21.0
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deepspeed==0.14.4
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pydantic==2.6.3
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addict
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@@ -1,51 +0,0 @@
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"""Patch transformers.dynamic_module_utils.get_class_in_module to avoid reloading models from disk"""
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import importlib
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import os
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import sys
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import typing
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from pathlib import Path
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from transformers.file_utils import HF_MODULES_CACHE
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def _patched_get_class_in_module(
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class_name: str, module_path: typing.Union[str, os.PathLike]
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) -> typing.Type:
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"""
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Import a module on the cache directory for modules and extract a class from it.
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Args:
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class_name (`str`): The name of the class to import.
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module_path (`str` or `os.PathLike`): The path to the module to import.
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Returns:
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`typing.Type`: The class looked for.
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"""
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name = os.path.normpath(module_path)
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if name.endswith(".py"):
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name = name[:-3]
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name = name.replace(os.path.sep, ".")
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module_spec = importlib.util.spec_from_file_location(
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name, location=Path(HF_MODULES_CACHE) / module_path
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)
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module = sys.modules.get(name)
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if module is None:
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module = importlib.util.module_from_spec(module_spec)
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# insert it into sys.modules before any loading begins
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sys.modules[name] = module
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# load in initial case only
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module_spec.loader.exec_module(module)
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return getattr(module, class_name)
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def patch_transformers_dynamic_module_utils():
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"""
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Recently, transformers started reloading modeling code from disk for models marked trust_remote_code=True.
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This causes monkey-patches for multipack and liger to be removed.
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We replace the original function with a version that does not reload the module from disk.
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See https://github.com/huggingface/transformers/pull/30370#pullrequestreview-2264361581
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"""
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import transformers
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transformers.dynamic_module_utils.get_class_in_module = _patched_get_class_in_module
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@@ -43,9 +43,6 @@ from axolotl.monkeypatch.multipack import (
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SUPPORTED_MULTIPACK_MODEL_TYPES,
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patch_for_multipack,
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)
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from axolotl.monkeypatch.transformers_dynamic_module_utils import (
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patch_transformers_dynamic_module_utils,
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)
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from axolotl.prompt_tokenizers import LLAMA_DEFAULT_EOS_TOKEN
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from axolotl.utils.bench import log_gpu_memory_usage
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from axolotl.utils.chat_templates import chat_templates
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@@ -57,8 +54,6 @@ from axolotl.utils.model_shard_quant import load_sharded_model, load_sharded_mod
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LOG = logging.getLogger("axolotl")
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patch_transformers_dynamic_module_utils()
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# copied from accelerator.FullyShardedDataParallelPlugin
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def get_module_class_from_name(module, name):
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