Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Remove calibration args from generate.py #1258

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Remove calibration args from generate.py #1258

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 4 additions & 8 deletions torchao/_models/llama/generate.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -163,8 +163,6 @@ def main(
temperature: float = 0.8,
checkpoint_path: Path = Path("checkpoints/meta-Transformer/Transformer-2-7b-chat-hf/model.pth"),
quantization: Optional[str] = None,
calibration_limit: int = 10,
calibration_seq_length: int = 256,
kv_cache_quantization: bool = False,
cache_size: Optional[int] = None,
linear_causal_mask: bool=False,
Expand Down Expand Up @@ -254,16 +252,16 @@ def main(
quant_dtype = getattr(torch, quant_dtype, torch.uint8)
model=model.to(device)
# get calibration data
insert_awq_observer_(model, calibration_limit, calibration_seq_length, quant_dtype=quant_dtype, group_size=group_size)
insert_awq_observer_(model, 1, 256, quant_dtype=quant_dtype, group_size=group_size)
TransformerEvalWrapper(
model=model.to(device),
tokenizer=tokenizer,
max_seq_length=calibration_seq_length,
max_seq_length=256,
input_prep_func=prepare_inputs_for_model,
device=device,
).run_eval(
tasks=['wikitext'],
limit=calibration_limit,
limit=1,
)
is_observed_linear = lambda m, fqn: isinstance(m, AWQObservedLinear)
use_hqq = "hqq" in quantization
Expand Down Expand Up @@ -477,8 +475,6 @@ def callback(x):
+'embed-int8wo'
)
)
parser.add_argument("--calibration_limit", type=int, default=10, help="Number of calibration examples")
parser.add_argument("--calibration_seq_length", type=int, default=256, help="Sequence length for calibration")
parser.add_argument('--kv_cache_quantization', action='store_true', help='Whether to quantize the KV cache')
parser.add_argument('--cache_size', type=int, default=None, help='Force size of cache to be a certain number of tokens, if not set, will use max_new_tokens+prompt_size')
parser.add_argument('--linear_causal_mask', action='store_true', help='Whether to use the memory efficient, but slightly less fast, linear causal mask (important for long context lengths)')
Expand All @@ -494,5 +490,5 @@ def callback(x):
args = parser.parse_args()
main(
args.prompt, args.interactive, args.num_samples, args.max_new_tokens, args.batch_size, args.top_k,
args.temperature, args.checkpoint_path, args.quantization, args.calibration_limit, args.calibration_seq_length, args.kv_cache_quantization, args.cache_size, args.linear_causal_mask, args.save, args.compile, args.compile_prefill, args.profile, args.memory_profile, args.device, args.precision, args.write_result
args.temperature, args.checkpoint_path, args.quantization, args.kv_cache_quantization, args.cache_size, args.linear_causal_mask, args.save, args.compile, args.compile_prefill, args.profile, args.memory_profile, args.device, args.precision, args.write_result
)
Loading