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

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

* There is already a condition check within the function. This outer one is not necessary

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>

---------

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
This commit is contained in:
Wing Lian
2024-08-16 10:41:51 -04:00
committed by GitHub
parent 68a3c7678a
commit 803fed3e90
3 changed files with 19 additions and 2 deletions

View File

@@ -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

View File

@@ -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

View File

@@ -390,6 +390,14 @@ def calculate_total_num_steps(cfg, train_dataset, update=True):
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
@@ -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: