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logging improvements (#1808) [skip ci]

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* logging improvements

* fix sort
This commit is contained in:
Wing Lian
2024-08-06 10:31:50 -04:00
committed by GitHub
parent 35d5e59d78
commit c56e0a79a5
3 changed files with 10 additions and 5 deletions
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7
src/axolotl/utils/data/sft.py
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@@ -187,7 +187,12 @@ def load_tokenized_prepared_datasets(
else: else:
if cfg.push_dataset_to_hub: if cfg.push_dataset_to_hub:
LOG.info("Unable to find prepared dataset in Huggingface hub") LOG.info("Unable to find prepared dataset in Huggingface hub")
LOG.info(f"Unable to find prepared dataset in {prepared_ds_path}") if cfg.is_preprocess:
LOG.info(
f"Skipping prepared dataset in {prepared_ds_path} for pre-processing..."
)
else:
LOG.info(f"Unable to find prepared dataset in {prepared_ds_path}")
LOG.info("Loading raw datasets...") LOG.info("Loading raw datasets...")
if not cfg.is_preprocess: if not cfg.is_preprocess:
LOG.warning( LOG.warning(

6
src/axolotl/utils/distributed.py
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@@ -153,11 +153,11 @@ def compute_and_broadcast(fn): # pylint: disable=invalid-name
if is_main_process(): if is_main_process():
value_scalar = fn() value_scalar = fn()
value_tensor = torch.tensor( value_tensor = torch.tensor(
value_scalar, device=torch.cuda.current_device() value_scalar, device=torch.cuda.current_device(), dtype=torch.float32
).float() )
else: else:
value_tensor = torch.tensor( value_tensor = torch.tensor(
0.0, device=torch.cuda.current_device() 0.0, device=torch.cuda.current_device(), dtype=torch.float32
) # Placeholder tensor ) # Placeholder tensor
# Broadcast the tensor to all processes. # Broadcast the tensor to all processes.

2
src/axolotl/utils/models.py
View File

@@ -1022,7 +1022,7 @@ def load_lora(model, cfg, inference=False, config_only=False):
if cfg.lora_target_linear: if cfg.lora_target_linear:
linear_names = find_all_linear_names(model) linear_names = find_all_linear_names(model)
LOG.info(f"found linear modules: {repr(linear_names)}") LOG.info(f"found linear modules: {repr(sorted(linear_names))}")
lora_target_modules = list(set(lora_target_modules + linear_names)) lora_target_modules = list(set(lora_target_modules + linear_names))
lora_config_kwargs = {} lora_config_kwargs = {}