Feat/all tmp (#1219)
* Update save.py Check whether path is in /tmp dir for Kaggle environment * Update save.py Move temporary_location to /tmp in Kaggle * Enhance Kaggle environment support in save and tokenizer utilities --------- Co-authored-by: dendarrion <37800703+dendarrion@users.noreply.github.com> Co-authored-by: Erland366 <erland.pg366@gmail.com>
This commit is contained in:
Daniel Han
GitHub
parent
8e30e2e646
commit
09f667a533
2 changed files with 48 additions and 25 deletions
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@ -49,6 +49,7 @@ __all__ = [
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keynames = "\n" + "\n".join(os.environ.keys())
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IS_COLAB_ENVIRONMENT = "\nCOLAB_" in keynames
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IS_KAGGLE_ENVIRONMENT = "\nKAGGLE_" in keynames
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KAGGLE_TMP = "/tmp"
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del keynames
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# Weights
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@ -447,13 +448,20 @@ def unsloth_save_model(
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if push_to_hub and "/" in save_directory:
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# +1 solves absolute path issues
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username = save_directory[:save_directory.find("/")]
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new_save_directory = save_directory[save_directory.find("/")+1:]
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logger.warning_once(
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f"Unsloth: You are pushing to hub, but you passed your HF username = {username}.\n"\
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f"We shall truncate {save_directory} to {new_save_directory}"
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)
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new_save_directory = save_directory
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username = new_save_directory[:new_save_directory.find("/")]
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new_save_directory = new_save_directory[new_save_directory.find("/")+1:]
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if IS_KAGGLE_ENVIRONMENT:
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new_save_directory = os.path.join(KAGGLE_TMP, new_save_directory[new_save_directory.find("/")+1:])
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logger.warning_once(
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"Unsloth: You are pushing to hub in Kaggle environment.\n"\
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f"To save memory, we shall move {save_directory} to {new_save_directory}"
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)
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else:
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logger.warning_once(
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f"Unsloth: You are pushing to hub, but you passed your HF username = {username}.\n"\
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f"We shall truncate {save_directory} to {new_save_directory}"
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)
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save_pretrained_settings["save_directory"] = new_save_directory
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tokenizer_save_settings ["save_directory"] = new_save_directory
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@ -507,6 +515,10 @@ def unsloth_save_model(
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f"{round(max_ram/1024/1024/1024, 2)} out of "\
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f"{round(psutil.virtual_memory().total/1024/1024/1024, 2)} RAM for saving.")
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# Move temporary_location to /tmp in Kaggle
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if IS_KAGGLE_ENVIRONMENT:
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temporary_location = os.path.join(KAGGLE_TMP, temporary_location)
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# Max directory for disk saving
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if not os.path.exists(temporary_location):
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os.makedirs(temporary_location)
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@ -708,7 +720,7 @@ def unsloth_save_model(
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print("Done.")
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if push_to_hub and hasattr(model, "config"):
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print(f"Saved merged model to https://huggingface.co/{username}/{save_directory.lstrip('/')}")
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print(f"Saved merged model to https://huggingface.co/{username}/{save_directory.lstrip('/').split('/')[-1]}")
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pass
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save_pretrained_settings["state_dict"] = None
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@ -1108,14 +1120,17 @@ def save_to_gguf(
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# Check if quantization succeeded!
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if not os.path.isfile(final_location):
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if IS_KAGGLE_ENVIRONMENT:
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raise RuntimeError(
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f"Unsloth: Quantization failed for {final_location}\n"\
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"You are in a Kaggle environment, which might be the reason this is failing.\n"\
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"Kaggle only provides 20GB of disk space. Merging to 16bit for 7b models use 16GB of space.\n"\
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"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
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"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
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"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
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)
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if not Path(final_location).resolve().is_relative_to(Path('/tmp').resolve()):
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raise RuntimeError(
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f"Unsloth: Quantization failed for {final_location}\n"\
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"You are in a Kaggle environment, which might be the reason this is failing.\n"\
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"Kaggle only provides 20GB of disk space in the working directory.\n"\
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"Merging to 16bit for 7b models use 16GB of space.\n"\
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"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
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"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
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"You can try saving it to the `/tmp` directory for larger disk space.\n"\
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"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
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)
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else:
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raise RuntimeError(
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f"Unsloth: Quantization failed for {final_location}\n"\
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@ -1156,14 +1171,17 @@ def save_to_gguf(
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# Check if quantization succeeded!
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if not os.path.isfile(final_location):
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if IS_KAGGLE_ENVIRONMENT:
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raise RuntimeError(
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f"Unsloth: Quantization failed for {final_location}\n"\
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"You are in a Kaggle environment, which might be the reason this is failing.\n"\
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"Kaggle only provides 20GB of disk space. Merging to 16bit for 7b models use 16GB of space.\n"\
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"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
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"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
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"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
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)
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if not Path(final_location).resolve().is_relative_to(Path('/tmp').resolve()):
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raise RuntimeError(
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f"Unsloth: Quantization failed for {final_location}\n"\
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"You are in a Kaggle environment, which might be the reason this is failing.\n"\
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"Kaggle only provides 20GB of disk space in the working directory.\n"\
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"Merging to 16bit for 7b models use 16GB of space.\n"\
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"This means using `model.{save_pretrained/push_to_hub}_merged` works, but\n"\
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"`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"\
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"You can try saving it to the `/tmp` directory for larger disk space.\n"\
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"I suggest you to save the 16bit model first, then use manual llama.cpp conversion."
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)
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else:
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raise RuntimeError(
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"Unsloth: Quantization failed! You might have to compile llama.cpp yourself, then run this again.\n"\
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@ -64,6 +64,7 @@ IGNORED_TOKENIZER_NAMES = frozenset(
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keynames = "\n" + "\n".join(os.environ.keys())
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IS_COLAB_ENVIRONMENT = "\nCOLAB_" in keynames
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IS_KAGGLE_ENVIRONMENT = "\nKAGGLE_" in keynames
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KAGGLE_TMP = "/tmp"
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del keynames
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@ -470,8 +471,12 @@ def _load_correct_tokenizer(
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cache_dir = "huggingface_tokenizers_cache",
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fix_tokenizer = True,
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):
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if IS_COLAB_ENVIRONMENT or IS_KAGGLE_ENVIRONMENT:
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if IS_COLAB_ENVIRONMENT:
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cache_dir = cache_dir
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elif IS_KAGGLE_ENVIRONMENT:
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# /tmp of Kaggle seems has a 80GB limit!
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# Let's utilize them
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cache_dir = os.path.join(KAGGLE_TMP, cache_dir)
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else:
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cache_dir = None
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pass
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