upgrade peft==0.16.0 and datasets==4.0.0 (#2917) [skip ci]
* upgrade peft to 0.16.0 * upgrade datasets to 4.0.0 * refactor dupes from merge/rebase * fix check for fsdp1 + sharded_state_dict * use full state dict for ci
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@@ -12,11 +12,11 @@ liger-kernel==0.6.0
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packaging==23.2
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huggingface_hub>=0.33.0
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peft==0.15.2
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peft==0.16.0
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transformers==4.53.2
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tokenizers>=0.21.1
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accelerate==1.8.1
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datasets==3.6.0
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datasets==4.0.0
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deepspeed>=0.17.0
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trl==0.19.1
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hf_xet==1.1.2
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@@ -865,6 +865,7 @@ class OptimizationValidationMixin:
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and hasattr(self, "save_safetensors")
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and self.save_safetensors
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and self.fsdp_config.get("state_dict_type", "") == "SHARDED_STATE_DICT"
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and str(getattr(self, "fsdp_version", "1")) != "2"
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):
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raise ValueError(
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"FSDP SHARDED_STATE_DICT not compatible with save_safetensors"
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@@ -391,7 +391,10 @@ class TestMultiGPULlama:
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@pytest.mark.parametrize(
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"fsdp_state_dict_type",
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["FULL_STATE_DICT", "SHARDED_STATE_DICT"],
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[
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"FULL_STATE_DICT",
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# "SHARDED_STATE_DICT", # not supported since intermediate checkpoints fail with fsdp1
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],
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)
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def test_fsdp_packed(self, temp_dir, fsdp_state_dict_type):
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# pylint: disable=duplicate-code
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@@ -413,7 +416,8 @@ class TestMultiGPULlama:
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},
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],
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"num_epochs": 1,
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"max_steps": 2,
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"max_steps": 3,
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"save_steps": 2,
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"micro_batch_size": 2,
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"gradient_accumulation_steps": 2,
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# "gradient_checkpointing": True,
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@@ -597,7 +601,7 @@ class TestMultiGPULlama:
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"fsdp_use_orig_params": False,
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"fsdp_cpu_ram_efficient_loading": True,
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"fsdp_transformer_layer_cls_to_wrap": "LlamaDecoderLayer",
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"fsdp_state_dict_type": "SHARDED_STATE_DICT",
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"fsdp_state_dict_type": "FULL_STATE_DICT",
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"fsdp_auto_wrap_policy": "TRANSFORMER_BASED_WRAP",
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},
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"use_tensorboard": True,
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