Fixes
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@@ -436,7 +436,7 @@ class TFCTRLModel(TFCTRLPreTrainedModel):
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def call(self, inputs, **kwargs):
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r"""
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Return:
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:obj:`tuple(tf.Tensor)` comprising various elements depending on the configuration (config) and inputs:
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:obj:`tuple(tf.Tensor)` comprising various elements depending on the configuration (:class:`~transformers.CTRLConfig`) and inputs:
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last_hidden_state (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`):
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Sequence of hidden-states at the last layer of the model.
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past (:obj:`List[tf.Tensor]` of length :obj:`config.n_layers` with each tensor of shape :obj:`(2, batch_size, num_heads, sequence_length, embed_size_per_head)`):
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@@ -509,7 +509,7 @@ class TFCTRLLMHeadModel(TFCTRLPreTrainedModel):
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def call(self, inputs, **kwargs):
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r"""
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Return:
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:obj:`tuple(tf.Tensor)` comprising various elements depending on the configuration (:obj:`~transformers.GPT2Config`) and inputs:
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:obj:`tuple(tf.Tensor)` comprising various elements depending on the configuration (:class:`~transformers.CTRLConfig`) and inputs:
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prediction_scores (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`):
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Prediction scores of the language modeling head (scores for each vocabulary token before SoftMax).
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past (:obj:`List[tf.Tensor]` of length :obj:`config.n_layers` with each tensor of shape :obj:`(2, batch_size, num_heads, sequence_length, embed_size_per_head)`):
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