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int4 quantization cpu fix #193

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int4 quantization cpu fix #193

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8 changes: 6 additions & 2 deletions quantize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@

from model import Transformer

default_use_cuda = True if torch.cuda.is_available() else False

##### Quantization Primitives ######

def dynamically_quantize_per_channel(x, quant_min, quant_max, target_dtype):
Expand Down Expand Up @@ -530,6 +532,7 @@ def quantize(
mode: str = 'int8',
# following arguments only available when setting int4 quantization.
groupsize: int = 128,
use_cuda = default_use_cuda,
# following arguments only used for GPTQ
calibration_tasks: list = ["hellaswag"],
calibration_limit: int = 1000,
Expand Down Expand Up @@ -566,7 +569,7 @@ def quantize(
elif mode == 'int4':
print("Quantizing model weights for int4 weight-only affine per-channel groupwise quantization")
quant_handler = WeightOnlyInt4QuantHandler(model, groupsize)
quantized_state_dict = quant_handler.create_quantized_state_dict()
quantized_state_dict = quant_handler.create_quantized_state_dict(use_cuda)

dir_name = checkpoint_path.parent
base_name = checkpoint_path.name
Expand Down Expand Up @@ -610,6 +613,7 @@ def quantize(
parser.add_argument('--checkpoint_path', type=Path, default=Path("checkpoints/meta-llama/Llama-2-7b-chat-hf/model.pth"), help='Path to the model checkpoint to be quantized.')
parser.add_argument('--mode', '-q', type=str, default='int8', choices=['int8', 'int4', 'int4-gptq'], help='type of quantization to perform')
parser.add_argument('--groupsize', type=int, default=32, help='Group size for int4 quantization.')
parser.add_argument('--use_cuda', type=bool, default=default_use_cuda, help='Whether to use cuda for int4 quantization.')
parser.add_argument('--calibration_tasks', type=str, nargs='+', default=['wikitext'], help='tasks to do gptq calibration on, if doing gptq')
parser.add_argument('--calibration_limit', type=int, default=1000, help='number of samples to use for gptq calibration')
parser.add_argument('--calibration_seq_length', type=int, default=100, help='length of sequences to use for gptq calibration')
Expand All @@ -619,4 +623,4 @@ def quantize(
parser.add_argument('--label', type=str, default='_', help='label to add to output filename')

args = parser.parse_args()
quantize(args.checkpoint_path, args.mode, args.groupsize, args.calibration_tasks, args.calibration_limit, args.calibration_seq_length, args.pad_calibration_inputs, args.percdamp, args.blocksize, args.label)
quantize(args.checkpoint_path, args.mode, args.groupsize, args.use_cuda, args.calibration_tasks, args.calibration_limit, args.calibration_seq_length, args.pad_calibration_inputs, args.percdamp, args.blocksize, args.label)