ceos/unsloth
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

spaces

Browse source
This commit is contained in:
Daniel Han-Chen 2024-02-18 18:25:19 +11:00
commit dcbbab3c22
2 changed files with 6 additions and 6 deletions
Download patch file Download diff file Expand all files Collapse all files

6
unsloth/models/llama.py
View file

@ -992,7 +992,7 @@ class FastLlamaModel:
logger.warning_once(debug_info)"""
debug_info = debug_info.split('\n')
debug_info = "\n".join([debug_info[0]] + [spaces + x for x in debug_info[1:]])
debug_info = "\n".join([debug_info[0]] + [spaces + x.lstrip("\t ") for x in debug_info[1:]])
inner_training_loop = inner_training_loop.replace(original_debug, debug_info)
debug_info = """n_total_devices = total_train_batch_size // \\
@ -1006,7 +1006,7 @@ class FastLlamaModel:
)
debug_info ="""
debug_info = debug_info.split('\n')
debug_info = "\n".join([debug_info[0]] + [spaces + x.lstrip('\t ') for x in debug_info[1:]])
debug_info = "\n".join([debug_info[0]] + [spaces + x.lstrip("\t ") for x in debug_info[1:]])
inner_training_loop = inner_training_loop.replace("debug_info =", debug_info, 1)
front_spaces = re.match(r"[\t\s]{1,}", inner_training_loop).group(0)
@ -1039,7 +1039,7 @@ class FastLlamaModel:
divisor = n_total_devices / 2 / 2
ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
check_batches = check_batches.split('\n')
check_batches = "\n".join([check_batches[0]] + [front_spaces + x.lstrip('\t ') for x in check_batches[1:]])
check_batches = "\n".join([check_batches[0]] + [front_spaces + x.lstrip("\t ") for x in check_batches[1:]])
inner_training_loop = inner_training_loop.replace(
"train_dataloader = self.get_train_dataloader()",
check_batches, 1,

6
unsloth/models/mistral.py
View file

@ -397,7 +397,7 @@ class FastMistralModel(FastLlamaModel):
logger.warning_once(debug_info)"""
debug_info = debug_info.split('\n')
debug_info = "\n".join([debug_info[0]] + [spaces + x for x in debug_info[1:]])
debug_info = "\n".join([debug_info[0]] + [spaces + x.lstrip("\t ") for x in debug_info[1:]])
inner_training_loop = inner_training_loop.replace(original_debug, debug_info)
debug_info = """n_total_devices = total_train_batch_size // \\
@ -411,7 +411,7 @@ class FastMistralModel(FastLlamaModel):
)
debug_info ="""
debug_info = debug_info.split('\n')
debug_info = "\n".join([debug_info[0]] + [spaces + x for x in debug_info[1:]])
debug_info = "\n".join([debug_info[0]] + [spaces + x.lstrip("\t ") for x in debug_info[1:]])
inner_training_loop = inner_training_loop.replace("debug_info =", debug_info, 1)
front_spaces = re.match(r"[\t\s]{1,}", inner_training_loop).group(0)
@ -444,7 +444,7 @@ class FastMistralModel(FastLlamaModel):
divisor = n_total_devices / 2 / 2
ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
check_batches = check_batches.split('\n')
check_batches = "\n".join([check_batches[0]] + [front_spaces + x for x in check_batches[1:]])
check_batches = "\n".join([check_batches[0]] + [front_spaces + x.lstrip("\t ") for x in check_batches[1:]])
inner_training_loop = inner_training_loop.replace(
"train_dataloader = self.get_train_dataloader()",
check_batches, 1,