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Model output test (#6155)

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* Use return_dict=True in all tests

* Formatting
This commit is contained in:
Sylvain Gugger
2020-07-31 09:44:37 -04:00
committed by GitHub
parent 86caab1e0b
commit d951c14ae4
26 changed files with 320 additions and 765 deletions
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26
tests/test_modeling_openai.py
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@@ -85,9 +85,10 @@ class OpenAIGPTModelTester:
# hidden_dropout_prob=self.hidden_dropout_prob,
# attention_probs_dropout_prob=self.attention_probs_dropout_prob,
n_positions=self.max_position_embeddings,
n_ctx=self.max_position_embeddings
n_ctx=self.max_position_embeddings,
# type_vocab_size=self.type_vocab_size,
# initializer_range=self.initializer_range
return_dict=True,
)
head_mask = ids_tensor([self.num_hidden_layers, self.num_attention_heads], 2)
@@ -110,13 +111,12 @@ class OpenAIGPTModelTester:
model.to(torch_device)
model.eval()
model(input_ids, token_type_ids=token_type_ids, head_mask=head_mask)
model(input_ids, token_type_ids=token_type_ids)
(sequence_output,) = model(input_ids)
result = model(input_ids, token_type_ids=token_type_ids, head_mask=head_mask)
result = model(input_ids, token_type_ids=token_type_ids)
result = model(input_ids)
result = {"sequence_output": sequence_output}
self.parent.assertListEqual(
list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size],
list(result["last_hidden_state"].size()), [self.batch_size, self.seq_length, self.hidden_size],
)
def create_and_check_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
@@ -124,13 +124,10 @@ class OpenAIGPTModelTester:
model.to(torch_device)
model.eval()
loss, lm_logits = model(input_ids, token_type_ids=token_type_ids, labels=input_ids)
result = {"loss": loss, "lm_logits": lm_logits}
result = model(input_ids, token_type_ids=token_type_ids, labels=input_ids)
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
list(result["logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)
def create_and_check_double_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
@@ -138,11 +135,8 @@ class OpenAIGPTModelTester:
model.to(torch_device)
model.eval()
loss, lm_logits, mc_logits = model(input_ids, token_type_ids=token_type_ids, labels=input_ids)
result = {"loss": loss, "lm_logits": lm_logits}
self.parent.assertListEqual(list(result["loss"].size()), [])
result = model(input_ids, token_type_ids=token_type_ids, labels=input_ids)
self.parent.assertListEqual(list(result["lm_loss"].size()), [])
self.parent.assertListEqual(
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)