Unverified Commit 823df939 authored by Lysandre Debut's avatar Lysandre Debut Committed by GitHub
Browse files

Fix GPT-2 warnings (#11213)



* Fix GPT-2 warnings

* Update src/transformers/models/gpt2/modeling_gpt2.py
Co-authored-by: default avatarStas Bekman <stas00@users.noreply.github.com>
Co-authored-by: default avatarStas Bekman <stas00@users.noreply.github.com>
parent 0cd89d8c
...@@ -380,6 +380,16 @@ def load_tf2_weights_in_pytorch_model(pt_model, tf_weights, allow_missing_keys=F ...@@ -380,6 +380,16 @@ def load_tf2_weights_in_pytorch_model(pt_model, tf_weights, allow_missing_keys=F
missing_keys, unexpected_keys = pt_model.load_state_dict(new_pt_params_dict, strict=False) missing_keys, unexpected_keys = pt_model.load_state_dict(new_pt_params_dict, strict=False)
missing_keys += missing_keys_pt missing_keys += missing_keys_pt
# Some models may have keys that are not in the state by design, removing them before needlessly warning
# the user.
if pt_model._keys_to_ignore_on_load_missing is not None:
for pat in pt_model._keys_to_ignore_on_load_missing:
missing_keys = [k for k in missing_keys if re.search(pat, k) is None]
if pt_model._keys_to_ignore_on_load_unexpected is not None:
for pat in pt_model._keys_to_ignore_on_load_unexpected:
unexpected_keys = [k for k in unexpected_keys if re.search(pat, k) is None]
if len(unexpected_keys) > 0: if len(unexpected_keys) > 0:
logger.warning( logger.warning(
f"Some weights of the TF 2.0 model were not used when " f"Some weights of the TF 2.0 model were not used when "
......
...@@ -802,7 +802,7 @@ class GPT2Model(GPT2PreTrainedModel): ...@@ -802,7 +802,7 @@ class GPT2Model(GPT2PreTrainedModel):
GPT2_START_DOCSTRING, GPT2_START_DOCSTRING,
) )
class GPT2LMHeadModel(GPT2PreTrainedModel): class GPT2LMHeadModel(GPT2PreTrainedModel):
_keys_to_ignore_on_load_missing = [r"h\.\d+\.attn\.masked_bias", r"lm_head\.weight"] _keys_to_ignore_on_load_missing = [r"attn.masked_bias", r"attn.bias", r"lm_head.weight"]
def __init__(self, config): def __init__(self, config):
super().__init__(config) super().__init__(config)
......
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