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Remove deprecated (#8604)

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* Remove old deprecated arguments

Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Remove needless imports

* Fix tests

Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
This commit is contained in:
Sylvain Gugger
2020-11-17 15:11:29 -05:00
committed by GitHub
parent 3095ee9dab
commit dd52804f5f
37 changed files with 22 additions and 610 deletions
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19
src/transformers/models/ctrl/modeling_ctrl.py
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@@ -15,9 +15,6 @@
# limitations under the License.
""" PyTorch CTRL model."""
import warnings
import numpy as np
import torch
import torch.nn as nn
@@ -369,15 +366,7 @@ class CTRLModel(CTRLPreTrainedModel):
output_attentions=None,
output_hidden_states=None,
return_dict=None,
**kwargs,
):
if "past" in kwargs:
warnings.warn(
"The `past` argument is deprecated and will be removed in a future version, use `past_key_values` instead.",
FutureWarning,
)
past_key_values = kwargs.pop("past")
assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}."
output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
use_cache = use_cache if use_cache is not None else self.config.use_cache
@@ -542,7 +531,6 @@ class CTRLLMHeadModel(CTRLPreTrainedModel):
output_attentions=None,
output_hidden_states=None,
return_dict=None,
**kwargs,
):
r"""
labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`):
@@ -550,13 +538,6 @@ class CTRLLMHeadModel(CTRLPreTrainedModel):
``labels = input_ids`` Indices are selected in ``[-100, 0, ..., config.vocab_size]`` All labels set to
``-100`` are ignored (masked), the loss is only computed for labels in ``[0, ..., config.vocab_size]``
"""
if "past" in kwargs:
warnings.warn(
"The `past` argument is deprecated and will be removed in a future version, use `past_key_values` instead.",
FutureWarning,
)
past_key_values = kwargs.pop("past")
assert kwargs == {}, f"Unexpected keyword arguments: {list(kwargs.keys())}."
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
transformer_outputs = self.transformer(