dnrops
/
transformers
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

update tests

This commit is contained in:
thomwolf 2019-01-28 17:16:02 +01:00
parent b12616fd8e
commit a45a9cc0e1
1 changed files with 14 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

27
tests/modeling_openai_test.py
View File

@ -88,13 +88,13 @@ class OpenAIGPTModelTest(unittest.TestCase):
total_voc = self.n_ctx + self.n_special + self.vocab_size
token_type_ids = OpenAIGPTModelTest.ids_tensor([self.batch_size, self.n_choices, self.seq_length], total_voc)
multiple_choice_labels = None
mc_labels = None
lm_labels = None
multiple_choice_token_mask = None
mc_token_mask = None
if self.use_labels:
multiple_choice_labels = OpenAIGPTModelTest.ids_tensor([self.batch_size], self.type_sequence_label_size)
mc_labels = OpenAIGPTModelTest.ids_tensor([self.batch_size], self.type_sequence_label_size)
lm_labels = OpenAIGPTModelTest.ids_tensor([self.batch_size, self.n_choices, self.seq_length], self.num_labels)
multiple_choice_token_mask = OpenAIGPTModelTest.ids_tensor([self.batch_size, self.n_choices, self.seq_length], 2).float()
mc_token_mask = OpenAIGPTModelTest.ids_tensor([self.batch_size, self.n_choices, self.seq_length], 2).float()
config = OpenAIGPTConfig(
vocab_size_or_config_json_file=self.vocab_size,
@ -110,10 +110,10 @@ class OpenAIGPTModelTest(unittest.TestCase):
initializer_range=self.initializer_range)
return (config, input_ids, token_type_ids, position_ids,
multiple_choice_labels, lm_labels, multiple_choice_token_mask)
mc_labels, lm_labels, mc_token_mask)
def create_openai_model(self, config, input_ids, token_type_ids, position_ids,
multiple_choice_labels, lm_labels, multiple_choice_token_mask):
mc_labels, lm_labels, mc_token_mask):
model = OpenAIGPTModel(config)
hidden_states = model(input_ids, position_ids, token_type_ids)
outputs = {
@ -128,7 +128,7 @@ class OpenAIGPTModelTest(unittest.TestCase):
def create_openai_lm_head(self, config, input_ids, token_type_ids, position_ids,
multiple_choice_labels, lm_labels, multiple_choice_token_mask):
mc_labels, lm_labels, mc_token_mask):
model = OpenAIGPTLMHeadModel(config)
loss = model(input_ids, position_ids, token_type_ids, lm_labels)
lm_logits = model(input_ids, position_ids, token_type_ids)
@ -150,15 +150,16 @@ class OpenAIGPTModelTest(unittest.TestCase):
[])
def create_openai_double_heads(self, config, input_ids, token_type_ids, position_ids,
multiple_choice_labels, lm_labels, multiple_choice_token_mask):
mc_labels, lm_labels, mc_token_mask):
model = OpenAIGPTDoubleHeadsModel(config)
loss = model(input_ids, multiple_choice_token_mask, position_ids,
token_type_ids, lm_labels, multiple_choice_labels)
lm_logits, multiple_choice_logits = model(input_ids, multiple_choice_token_mask, position_ids, token_type_ids)
loss = model(input_ids, mc_token_mask,
lm_labels=lm_labels, mc_labels=mc_labels,
token_type_ids=token_type_ids, position_ids=position_ids)
lm_logits, mc_logits = model(input_ids, mc_token_mask, position_ids=position_ids, token_type_ids=token_type_ids)
outputs = {
"loss": loss,
"lm_logits": lm_logits,
"multiple_choice_logits": multiple_choice_logits,
"mc_logits": mc_logits,
}
return outputs
@ -168,7 +169,7 @@ class OpenAIGPTModelTest(unittest.TestCase):
list(result["lm_logits"].size()),
[self.batch_size, self.n_choices, self.seq_length, total_voc])
self.parent.assertListEqual(
list(result["multiple_choice_logits"].size()),
list(result["mc_logits"].size()),
[self.batch_size, self.n_choices])
def check_openai_double_heads_loss_output(self, result):