Open bash99 opened 1 month ago
I was able to get pass this error by manually setting in aphrodite/kv_quant/calibrate.py
:
LAYER_TYPE_MAP = {
'InternLMForCausalLM': 'InternLMDecoderLayer',
'QWenLMHeadModel': 'QWenBlock',
'Qwen2ForCausalLM': 'Qwen2DecoderLayer',
'BaiChuanForCausalLM': 'DecoderLayer',
'LlamaForCausalLM': 'LlamaDecoderLayer',
}
NORM_TYPE_MAP = {
'InternLMForCausalLM': 'InternLMRMSNorm',
'QWenLMHeadModel': 'RMSNorm',
'Qwen2ForCausalLM': 'Qwen2RMSNorm',
'BaiChuanForCausalLM': 'RMSNorm',
'LlamaForCausalLM': 'LlamaRMSNorm',
}
But now I get the following errors, letting me think that I didn't put the right params, or some other Qwen2 params are not properly set in the code :
Loading checkpoint shards: 50%|████████████████████████████████████████████████████████████████████████████████████ | 2/4 [00:00<00:00, 9.18it/s]
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.14.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.14.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.14.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.14.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.15.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.16.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.17.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.18.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.19.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.20.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.21.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.22.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.23.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.24.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.25.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.26.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.self_attn.o_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.mlp.gate_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.mlp.up_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.mlp.down_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.input_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.layers.27.post_attention_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for model.norm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:2047: UserWarning: for lm_head.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 11.91it/s]
Loading calibrate dataset ... Token indices sequence length is longer than the specified maximum sequence length for this model (2518423 > 131072). Running this sequence through the model will result in indexing errors
Traceback (most recent call last):
File "/PROJECT_PATH/aphrodite-engine/aphrodite/kv_quant/calibrate.py", line 114, in <module>
fire.Fire(calibrate)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/fire/core.py", line 143, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/fire/core.py", line 477, in _Fire
component, remaining_args = _CallAndUpdateTrace(
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/fire/core.py", line 693, in _CallAndUpdateTrace
component = fn(*varargs, **kwargs)
File "/PROJECT_PATH/aphrodite-engine/a
phrodite/kv_quant/calibrate.py", line 105, in calibrate
calib_ctx.calibrate(all_data)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/aphrodite/kv_quant/calibration.py", line 299, in calibrate
_ = model(data.to(self.device))
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1034, in forward
layer_outputs = decoder_layer(
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/PROJECT_PATH/.venv/lib/python3.10/site-packages/aphrodite/kv_quant/calibration.py", line 187, in _forward
key, value = out.pop(-1)
TypeError: cannot unpack non-iterable NoneType object
Your current environment
🐛 Describe the bug
Run calibrate script as below
And I got this error