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update sklearn versrion, torch compile env vars, don't worry about failure on preprocess load model #1821

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Aug 16, 2024
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update sklearn versrion, torch compile env vars, don't worry about failure on preprocess load model #1821

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3b22fb8
update sklearn versrion, torch compile env vars, don't worry about fa…
winglian Aug 9, 2024
7f59dac
There is already a condition check within the function. This outer on…
winglian Aug 16, 2024
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2 changes: 1 addition & 1 deletion requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ numpy>=1.24.4
# qlora things
evaluate==0.4.1
scipy
scikit-learn==1.2.2
scikit-learn==1.4.2
pynvml
art
fschat @ git+https://github.com/lm-sys/FastChat.git@27a05b04a35510afb1d767ae7e5990cbd278f8fe
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9 changes: 8 additions & 1 deletion src/axolotl/cli/preprocess.py
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Expand Up @@ -82,7 +82,14 @@ def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs):
# "copying from a non-meta parameter in the checkpoint to a meta parameter in the current model"
warnings.simplefilter("ignore")
with init_empty_weights(include_buffers=True):
AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
# fmt: off
try:
AutoModelForCausalLM.from_pretrained(
model_name, trust_remote_code=True
)
except Exception as exc: # pylint: disable=broad-exception-caught,unused-variable # nosec B110 # noqa F841
pass
# fmt: on

LOG.info(
Fore.GREEN
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10 changes: 10 additions & 0 deletions src/axolotl/utils/trainer.py
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Expand Up @@ -390,6 +390,14 @@ def calc_sample_packing_eff_est(estimates: List[float]):
return total_num_steps


def setup_torch_compile_env(cfg):
if cfg.torch_compile:
if not cfg.torch_compile_backend:
os.environ["ACCELERATE_DYNAMO_BACKEND"] = "INDUCTOR"
else:
os.environ["ACCELERATE_DYNAMO_BACKEND"] = cfg.torch_compile_backend.upper()


def setup_deepspeed_env(cfg, stage=None):
os.environ["ACCELERATE_USE_DEEPSPEED"] = "true"
os.environ["ACCELERATE_DEEPSPEED_CONFIG_FILE"] = cfg.deepspeed
Expand Down Expand Up @@ -434,6 +442,8 @@ def prepare_optim_env(cfg):
stage = deepspeed_config.get("zero_optimization", {}).get("stage", None)
setup_deepspeed_env(cfg, stage=stage)

setup_torch_compile_env(cfg)

if (cfg.bf16 == "auto" and is_torch_bf16_gpu_available()) or cfg.bf16 is True:
os.environ["ACCELERATE_MIXED_PRECISION"] = "bf16"
elif cfg.fp16:
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