diff --git a/src/axolotl/utils/models.py b/src/axolotl/utils/models.py index f3386cccf..41e89dbfb 100644 --- a/src/axolotl/utils/models.py +++ b/src/axolotl/utils/models.py @@ -640,9 +640,7 @@ def set_quantization_config(self) -> None: self.model_kwargs["quantization_config"] = BitsAndBytesConfig( **self.model_config.quantization_config ) - elif self.cfg.adapter == "qlora" and ( - "load_in_4bit" in self.model_kwargs and self.model_kwargs["load_in_4bit"] - ): + elif self.cfg.adapter == "qlora" and self.model_kwargs["load_in_4bit"]: bnb_config = { "load_in_4bit": True, "llm_int8_threshold": 6.0, @@ -665,9 +663,7 @@ def set_quantization_config(self) -> None: self.model_kwargs["quantization_config"] = BitsAndBytesConfig( **bnb_config, ) - elif self.cfg.adapter == "lora" and ( - "load_in_8bit" in self.model_kwargs and self.model_kwargs["load_in_8bit"] - ): + elif self.cfg.adapter == "lora" and self.model_kwargs["load_in_8bit"]: bnb_config = { "load_in_8bit": True, } @@ -680,10 +676,8 @@ def set_quantization_config(self) -> None: # no longer needed per https://github.com/huggingface/transformers/pull/26610 if "quantization_config" in self.model_kwargs or self.cfg.gptq: - if "load_in_8bit" in self.model_kwargs: - del self.model_kwargs["load_in_8bit"] - if "load_in_4bit" in self.model_kwargs: - del self.model_kwargs["load_in_4bit"] + self.model_kwargs.pop("load_in_8bit", None) + self.model_kwargs.pop("load_in_4bit", None) def set_attention_config(self) -> None: """ @@ -968,17 +962,10 @@ def prepare_model(self, qlora_fsdp) -> None: if is_deepspeed_zero3_enabled(): skip_prepare_model_for_kbit_training = True - is_load_in_8bit = ( - "load_in_8bit" in self.model_kwargs and self.model_kwargs["load_in_8bit"] - ) - is_load_in_4bit = ( - "load_in_4bit" in self.model_kwargs and self.model_kwargs["load_in_4bit"] - ) - if ( not skip_prepare_model_for_kbit_training and self.cfg.adapter in ["lora", "qlora"] - and (is_load_in_8bit or is_load_in_4bit) + and (self.cfg.load_in_8bit or self.cfg.load_in_4bit) ): LOG.info("converting PEFT model w/ prepare_model_for_kbit_training") self.model = prepare_model_for_kbit_training( @@ -1116,16 +1103,10 @@ def load_model(self) -> Tuple[PreTrainedModel, Optional[PeftConfig]]: # --------------------------------------------------------- # put model to accelerator # --------------------------------------------------------- - is_load_in_8bit = ( - "load_in_8bit" in self.model_kwargs and self.model_kwargs["load_in_8bit"] - ) - is_load_in_4bit = ( - "load_in_4bit" in self.model_kwargs and self.model_kwargs["load_in_4bit"] - ) if ( self.cfg.ddp - and not is_load_in_8bit - and not (self.cfg.rl and is_load_in_4bit) + and not self.cfg.load_in_8bit + and not (self.cfg.rl and self.cfg.load_in_4bit) and not skip_move_to_device ): # TODO revaldate this conditional diff --git a/tests/e2e/multigpu/test_llama.py b/tests/e2e/multigpu/test_llama.py index 14e3f733e..8087e08e3 100644 --- a/tests/e2e/multigpu/test_llama.py +++ b/tests/e2e/multigpu/test_llama.py @@ -14,7 +14,7 @@ from axolotl.utils.dict import DictDefault -from ..utils import with_temp_dir +from ..utils import is_hopper, with_temp_dir LOG = logging.getLogger("axolotl.tests.e2e.multigpu") os.environ["WANDB_DISABLED"] = "true" @@ -59,7 +59,7 @@ def test_lora_ddp(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -116,7 +116,7 @@ def test_lora_ddp_packed(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 50, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -144,6 +144,146 @@ def test_lora_ddp_packed(self, temp_dir): ] ) + @pytest.mark.skipif(is_hopper(), reason="h100 doesn't support 8-bit lora") + @with_temp_dir + def test_dpo_lora_ddp(self, temp_dir): + # pylint: disable=duplicate-code + cfg = DictDefault( + { + "base_model": "TinyLlama/TinyLlama_v1.1", + "tokenizer_type": "LlamaTokenizer", + "sequence_len": 2048, + "sample_packing": False, + "eval_sample_packing": False, + "pad_to_sequence_len": True, + "load_in_8bit": True, + "adapter": "lora", + "lora_r": 8, + "lora_alpha": 16, + "lora_dropout": 0.05, + "lora_target_linear": True, + "val_set_size": 0.05, + "special_tokens": { + "unk_token": "", + "bos_token": "", + "eos_token": "", + }, + "rl": "dpo", + "chat_template": "llama3", + "datasets": [ + { + "path": "fozziethebeat/alpaca_messages_2k_dpo_test", + "type": "chat_template.default", + "field_messages": "conversation", + "field_chosen": "chosen", + "field_rejected": "rejected", + "message_field_role": "role", + "message_field_content": "content", + "roles": { + "system": ["system"], + "user": ["user"], + "assistant": ["assistant"], + }, + }, + ], + "num_epochs": 1, + "max_steps": 15, + "micro_batch_size": 4, + "gradient_accumulation_steps": 4, + "output_dir": temp_dir, + "warmup_steps": 0, + "learning_rate": 0.00001, + "optimizer": "adamw_8bit", + "lr_scheduler": "cosine", + "flash_attention": True, + } + ) + + # write cfg to yaml file + Path(temp_dir).mkdir(parents=True, exist_ok=True) + with open(Path(temp_dir) / "config.yaml", "w", encoding="utf-8") as fout: + fout.write(yaml.dump(cfg.to_dict(), Dumper=yaml.Dumper)) + + execute_subprocess_async( + [ + "accelerate", + "launch", + "--num-processes", + "2", + "-m", + "axolotl.cli.train", + str(Path(temp_dir) / "config.yaml"), + ] + ) + + @with_temp_dir + def test_dpo_qlora_ddp(self, temp_dir): + # pylint: disable=duplicate-code + cfg = DictDefault( + { + "base_model": "HuggingFaceTB/SmolLM-135M", + "sequence_len": 2048, + "sample_packing": False, + "eval_sample_packing": False, + "pad_to_sequence_len": True, + "load_in_4bit": True, + "adapter": "qlora", + "lora_r": 8, + "lora_alpha": 16, + "lora_dropout": 0.05, + "lora_target_linear": True, + "val_set_size": 0.05, + "special_tokens": { + "pad_token": "<|endoftext|>", + }, + "rl": "dpo", + "chat_template": "chatml", + "datasets": [ + { + "path": "fozziethebeat/alpaca_messages_2k_dpo_test", + "type": "chat_template.default", + "field_messages": "conversation", + "field_chosen": "chosen", + "field_rejected": "rejected", + "message_field_role": "role", + "message_field_content": "content", + "roles": { + "system": ["system"], + "user": ["user"], + "assistant": ["assistant"], + }, + }, + ], + "num_epochs": 1, + "max_steps": 15, + "micro_batch_size": 4, + "gradient_accumulation_steps": 4, + "output_dir": temp_dir, + "warmup_steps": 0, + "learning_rate": 0.00001, + "optimizer": "adamw_8bit", + "lr_scheduler": "cosine", + "flash_attention": True, + } + ) + + # write cfg to yaml file + Path(temp_dir).mkdir(parents=True, exist_ok=True) + with open(Path(temp_dir) / "config.yaml", "w", encoding="utf-8") as fout: + fout.write(yaml.dump(cfg.to_dict(), Dumper=yaml.Dumper)) + + execute_subprocess_async( + [ + "accelerate", + "launch", + "--num-processes", + "2", + "-m", + "axolotl.cli.train", + str(Path(temp_dir) / "config.yaml"), + ] + ) + @with_temp_dir def test_fsdp(self, temp_dir): # pylint: disable=duplicate-code @@ -165,7 +305,7 @@ def test_fsdp(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -231,7 +371,7 @@ def test_fsdp_packed(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -307,7 +447,7 @@ def test_fsdp_qlora_prequant_packed(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -373,7 +513,7 @@ def test_ds_zero3_packed(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, @@ -432,7 +572,7 @@ def test_ds_zero3_qlora_packed(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "micro_batch_size": 4, "gradient_accumulation_steps": 4, "output_dir": temp_dir, diff --git a/tests/e2e/multigpu/test_qwen2.py b/tests/e2e/multigpu/test_qwen2.py index 2513be69e..393ab7d70 100644 --- a/tests/e2e/multigpu/test_qwen2.py +++ b/tests/e2e/multigpu/test_qwen2.py @@ -47,7 +47,7 @@ def test_qlora_fsdp_dpo(self, temp_dir): }, ], "num_epochs": 1, - "max_steps": 100, + "max_steps": 15, "warmup_steps": 20, "micro_batch_size": 4, "gradient_accumulation_steps": 2, diff --git a/tests/e2e/patched/test_4d_multipack_llama.py b/tests/e2e/patched/test_4d_multipack_llama.py index d74d09723..a26c5d962 100644 --- a/tests/e2e/patched/test_4d_multipack_llama.py +++ b/tests/e2e/patched/test_4d_multipack_llama.py @@ -13,7 +13,7 @@ from axolotl.utils.config import normalize_config from axolotl.utils.dict import DictDefault -from ..utils import require_torch_2_1_1, with_temp_dir +from ..utils import require_torch_2_3_1, with_temp_dir LOG = logging.getLogger("axolotl.tests.e2e") os.environ["WANDB_DISABLED"] = "true" @@ -24,7 +24,7 @@ class Test4dMultipackLlama(unittest.TestCase): Test case for Llama models using 4d attention with multipack """ - @require_torch_2_1_1 + @require_torch_2_3_1 @with_temp_dir def test_sdp_lora_packing(self, temp_dir): # pylint: disable=duplicate-code diff --git a/tests/e2e/utils.py b/tests/e2e/utils.py index 837b4734f..c15ca3d79 100644 --- a/tests/e2e/utils.py +++ b/tests/e2e/utils.py @@ -9,6 +9,8 @@ from importlib.metadata import version from pathlib import Path +import torch + def with_temp_dir(test_func): @wraps(test_func) @@ -35,13 +37,18 @@ def most_recent_subdir(path): return subdir -def require_torch_2_1_1(test_case): +def require_torch_2_3_1(test_case): """ - Decorator marking a test that requires torch >= 2.1.1 + Decorator marking a test that requires torch >= 2.3.1 """ - def is_min_2_1_1(): + def is_min_2_3_1(): torch_version = version("torch") - return torch_version >= "2.1.1" + return torch_version >= "2.3.1" + + return unittest.skipUnless(is_min_2_3_1(), "test torch 2.3.1")(test_case) + - return unittest.skipUnless(is_min_2_1_1(), "test torch 2.1.1")(test_case) +def is_hopper(): + compute_capability = torch.cuda.get_device_capability() + return compute_capability == (9, 0)