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@@ -23,14 +23,14 @@ |
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from torch import nn |
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from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss |
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-from ...activations import ACT2FN, gelu |
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-from ...file_utils import ( |
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+from transformers.activations import ACT2FN, gelu |
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+from transformers.file_utils import ( |
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add_code_sample_docstrings, |
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add_start_docstrings, |
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add_start_docstrings_to_model_forward, |
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replace_return_docstrings, |
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) |
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-from ...modeling_outputs import ( |
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+from transformers.modeling_outputs import ( |
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BaseModelOutputWithPastAndCrossAttentions, |
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BaseModelOutputWithPoolingAndCrossAttentions, |
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CausalLMOutputWithCrossAttentions, |
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@@ -40,14 +40,14 @@ |
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SequenceClassifierOutput, |
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TokenClassifierOutput, |
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) |
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-from ...modeling_utils import ( |
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+from transformers.modeling_utils import ( |
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PreTrainedModel, |
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apply_chunking_to_forward, |
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find_pruneable_heads_and_indices, |
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prune_linear_layer, |
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) |
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-from ...utils import logging |
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-from .configuration_roberta import RobertaConfig |
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+from transformers.utils import logging |
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+from transformers.models.roberta.configuration_roberta import RobertaConfig |
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logger = logging.get_logger(__name__) |
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@@ -183,6 +183,24 @@ |
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self.is_decoder = config.is_decoder |
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+ def get_attn(self): |
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+ return self.attn |
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+ |
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+ def save_attn(self, attn): |
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+ self.attn = attn |
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+ |
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+ def save_attn_cam(self, cam): |
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+ self.attn_cam = cam |
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+ |
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+ def get_attn_cam(self): |
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+ return self.attn_cam |
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+ |
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+ def save_attn_gradients(self, attn_gradients): |
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+ self.attn_gradients = attn_gradients |
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+ |
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+ def get_attn_gradients(self): |
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+ return self.attn_gradients |
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+ |
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def transpose_for_scores(self, x): |
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new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size) |
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x = x.view(*new_x_shape) |
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