Traceback (most recent call last):
File "/data/manxue.jj/anaconda3/envs/py310_torch201/bin/lmdeploy", line 8, in <module>
sys.exit(run())
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/cli/entrypoint.py", line 37, in run
args.run(args)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/cli/lite.py", line 137, in auto_awq
auto_awq(**kwargs)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/apis/auto_awq.py", line 96, in auto_awq
vl_model, model, tokenizer, work_dir = calibrate(model,
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/apis/calibrate.py", line 235, in calibrate
calib_ctx.calibrate(all_data)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/quantization/calibration.py", line 315, in calibrate
_ = model(data.to(self.device))
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/manxue.jj/.cache/huggingface/modules/transformers_modules/trained/modeling_internlm2.py", line 929, in forward
layer_outputs = decoder_layer(
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/quantization/calibration.py", line 505, in _forward
auto_scale_block(mod, batch_kwargs[i], self.w_bits,
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/quantization/calibration.py", line 407, in auto_scale_block
_auto_get_scale(
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/quantization/calibration.py", line 400, in _auto_get_scale
best_ratio = _search_module_scale(module2inspect, layers, inp.value,
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/lmdeploy/lite/quantization/calibration.py", line 352, in _search_module_scale
org_out = block(x, **kwargs)
File "/data/manxue.jj/anaconda3/envs/py310_torch201/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
TypeError: InternLM2MLP.forward() missing 1 required positional argument: 'im_mask'
Checklist
Describe the bug
尝试对internlm_xcomposer_vl_7b做量化时,report以下错误: TypeError: InternLM2MLP.forward() missing 1 required positional argument: 'im_mask'
Reproduction
lmdeploy lite auto_awq \ $HF_MODEL \ --calib-dataset 'ptb' \ --calib-samples 128 \ --calib-seqlen 2048 \ --batch-size 1 \ --w-bits 4 \ --w-group-size 128 \ --search-scale False \ --work-dir $WORK_DIR
Environment
Error traceback