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Merged
danielhanchen merged 4 commits into from
Oct 30, 2024
Merged

Feat/all tmp #1219

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1d895fe
Update save.py
dendarrion Oct 27, 2024
d9b2fe6
Update save.py
dendarrion Oct 28, 2024
5c09140
Enhance Kaggle environment support in save and tokenizer utilities
Erland366 Oct 29, 2024
d612145
Merge branch 'main' of https://github.com/unslothai/unsloth into feat…
Erland366 Oct 29, 2024
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66 changes: 42 additions & 24 deletions unsloth/save.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,6 +49,7 @@
keynames = "\n" + "\n".join(os.environ.keys())
IS_COLAB_ENVIRONMENT = "\nCOLAB_" in keynames
IS_KAGGLE_ENVIRONMENT = "\nKAGGLE_" in keynames
KAGGLE_TMP = "/tmp"
del keynames

# Weights
Expand Down Expand Up @@ -447,13 +448,20 @@ def unsloth_save_model(
if push_to_hub and "/" in save_directory:

# +1 solves absolute path issues
username = save_directory[:save_directory.find("/")]
new_save_directory = save_directory[save_directory.find("/")+1:]

logger.warning_once(
f"Unsloth: You are pushing to hub, but you passed your HF username = {username}.\n"\
f"We shall truncate {save_directory} to {new_save_directory}"
)
new_save_directory = save_directory
username = new_save_directory[:new_save_directory.find("/")]
new_save_directory = new_save_directory[new_save_directory.find("/")+1:]
if IS_KAGGLE_ENVIRONMENT:
new_save_directory = os.path.join(KAGGLE_TMP, new_save_directory[new_save_directory.find("/")+1:])
logger.warning_once(
"Unsloth: You are pushing to hub in Kaggle environment.\n"\
f"To save memory, we shall move {save_directory} to {new_save_directory}"
)
else:
logger.warning_once(
f"Unsloth: You are pushing to hub, but you passed your HF username = {username}.\n"\
f"We shall truncate {save_directory} to {new_save_directory}"
)

save_pretrained_settings["save_directory"] = new_save_directory
tokenizer_save_settings ["save_directory"] = new_save_directory
Expand Down Expand Up @@ -507,6 +515,10 @@ def unsloth_save_model(
f"{round(max_ram/1024/1024/1024, 2)} out of "\
f"{round(psutil.virtual_memory().total/1024/1024/1024, 2)} RAM for saving.")

# Move temporary_location to /tmp in Kaggle
if IS_KAGGLE_ENVIRONMENT:
temporary_location = os.path.join(KAGGLE_TMP, temporary_location)

# Max directory for disk saving
if not os.path.exists(temporary_location):
os.makedirs(temporary_location)
Expand Down Expand Up @@ -708,7 +720,7 @@ def unsloth_save_model(
print("Done.")

if push_to_hub and hasattr(model, "config"):
print(f"Saved merged model to https://huggingface.co/{username}/{save_directory.lstrip('/')}")
print(f"Saved merged model to https://huggingface.co/{username}/{save_directory.lstrip('/').split('/')[-1]}")
pass

save_pretrained_settings["state_dict"] = None
Expand Down Expand Up @@ -1108,14 +1120,17 @@ def save_to_gguf(
# Check if quantization succeeded!
if not os.path.isfile(final_location):
if IS_KAGGLE_ENVIRONMENT:
raise RuntimeError(
f"Unsloth: Quantization failed for {final_location}\n"\
"You are in a Kaggle environment, which might be the reason this is failing.\n"\
"Kaggle only provides 20GB of disk space. Merging to 16bit for 7b models use 16GB of space.\n"\
"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
)
if not Path(final_location).resolve().is_relative_to(Path('/tmp').resolve()):
raise RuntimeError(
f"Unsloth: Quantization failed for {final_location}\n"\
"You are in a Kaggle environment, which might be the reason this is failing.\n"\
"Kaggle only provides 20GB of disk space in the working directory.\n"\
"Merging to 16bit for 7b models use 16GB of space.\n"\
"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
"You can try saving it to the `/tmp` directory for larger disk space.\n"\
"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
)
else:
raise RuntimeError(
f"Unsloth: Quantization failed for {final_location}\n"\
Expand Down Expand Up @@ -1156,14 +1171,17 @@ def save_to_gguf(
# Check if quantization succeeded!
if not os.path.isfile(final_location):
if IS_KAGGLE_ENVIRONMENT:
raise RuntimeError(
f"Unsloth: Quantization failed for {final_location}\n"\
"You are in a Kaggle environment, which might be the reason this is failing.\n"\
"Kaggle only provides 20GB of disk space. Merging to 16bit for 7b models use 16GB of space.\n"\
"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
)
if not Path(final_location).resolve().is_relative_to(Path('/tmp').resolve()):
raise RuntimeError(
f"Unsloth: Quantization failed for {final_location}\n"\
"You are in a Kaggle environment, which might be the reason this is failing.\n"\
"Kaggle only provides 20GB of disk space in the working directory.\n"\
"Merging to 16bit for 7b models use 16GB of space.\n"\
"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
"You can try saving it to the `/tmp` directory for larger disk space.\n"\
"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
)
else:
raise RuntimeError(
"Unsloth: Quantization failed! You might have to compile llama.cpp yourself, then run this again.\n"\
Expand Down
7 changes: 6 additions & 1 deletion unsloth/tokenizer_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@
keynames = "\n" + "\n".join(os.environ.keys())
IS_COLAB_ENVIRONMENT = "\nCOLAB_" in keynames
IS_KAGGLE_ENVIRONMENT = "\nKAGGLE_" in keynames
KAGGLE_TMP = "/tmp"
del keynames


Expand Down Expand Up @@ -470,8 +471,12 @@ def _load_correct_tokenizer(
cache_dir = "huggingface_tokenizers_cache",
fix_tokenizer = True,
):
if IS_COLAB_ENVIRONMENT or IS_KAGGLE_ENVIRONMENT:
if IS_COLAB_ENVIRONMENT:
cache_dir = cache_dir
elif IS_KAGGLE_ENVIRONMENT:
# /tmp of Kaggle seems has a 80GB limit!
# Let's utilize them
cache_dir = os.path.join(KAGGLE_TMP, cache_dir)
else:
cache_dir = None
pass
Expand Down