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Test suite testing the tie_weights function as well as the resize_token_embeddings function.

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Patched an issue relating to the tied weights I had introduced with the TorchScript addition.
Byte order mark management in TSV glue reading.
This commit is contained in:
LysandreJik
2019-07-11 22:09:16 -04:00
parent bd404735a7
commit 6c2ee16c04
5 changed files with 81 additions and 7 deletions
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4
pytorch_transformers/modeling_gpt2.py
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@@ -566,7 +566,7 @@ class GPT2LMHeadModel(GPT2PreTrainedModel):
if self.config.torchscript:
self.lm_head.weight = nn.Parameter(input_embeddings.clone())
else:
self.lm_head.weight = input_embeddings # Tied weights
self.lm_head = self.transformer.wte # Tied weights
def forward(self, input_ids, position_ids=None, token_type_ids=None, lm_labels=None, past=None, head_mask=None):
"""
@@ -662,7 +662,7 @@ class GPT2DoubleHeadsModel(GPT2PreTrainedModel):
if self.config.torchscript:
self.lm_head.weight = nn.Parameter(input_embeddings.clone())
else:
self.lm_head.weight = input_embeddings # Tied weights
self.lm_head = self.transformer.wte # Tied weights
def forward(self, input_ids, mc_token_ids=None, lm_labels=None, mc_labels=None, token_type_ids=None,
position_ids=None, past=None, head_mask=None):