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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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75
tests/test_modeling_xlm.py
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@@ -113,6 +113,7 @@ class XLMModelTester:
use_proj=self.use_proj,
num_labels=self.num_labels,
bos_token_id=self.bos_token_id,
return_dict=True,
)
return (
@@ -145,15 +146,11 @@ class XLMModelTester:
model = XLMModel(config=config)
model.to(torch_device)
model.eval()
outputs = model(input_ids, lengths=input_lengths, langs=token_type_ids)
outputs = model(input_ids, langs=token_type_ids)
outputs = model(input_ids)
sequence_output = outputs[0]
result = {
"sequence_output": sequence_output,
}
result = model(input_ids, lengths=input_lengths, langs=token_type_ids)
result = model(input_ids, langs=token_type_ids)
result = model(input_ids)
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_xlm_lm_head(
@@ -172,13 +169,7 @@ class XLMModelTester:
model.to(torch_device)
model.eval()
loss, logits = model(input_ids, token_type_ids=token_type_ids, labels=token_labels)
result = {
"loss": loss,
"logits": logits,
}
result = model(input_ids, token_type_ids=token_type_ids, labels=token_labels)
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(list(result["logits"].size()), [self.batch_size, self.seq_length, self.vocab_size])
@@ -201,13 +192,7 @@ class XLMModelTester:
outputs = model(input_ids)
outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels)
loss, start_logits, end_logits = outputs
result = {
"loss": loss,
"start_logits": start_logits,
"end_logits": end_logits,
}
result = outputs
self.parent.assertListEqual(list(result["start_logits"].size()), [self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].size()), [self.batch_size, self.seq_length])
self.check_loss_output(result)
@@ -228,10 +213,9 @@ class XLMModelTester:
model.to(torch_device)
model.eval()
outputs = model(input_ids)
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = outputs
result = model(input_ids)
outputs = model(
result_with_labels = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
@@ -240,7 +224,7 @@ class XLMModelTester:
p_mask=input_mask,
)
outputs = model(
result_with_labels = model(
input_ids,
start_positions=sequence_labels,
end_positions=sequence_labels,
@@ -248,22 +232,13 @@ class XLMModelTester:
is_impossible=is_impossible_labels,
)
(total_loss,) = outputs
(total_loss,) = result_with_labels.to_tuple()
outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels)
result_with_labels = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels)
(total_loss,) = outputs
(total_loss,) = result_with_labels.to_tuple()
result = {
"loss": total_loss,
"start_top_log_probs": start_top_log_probs,
"start_top_index": start_top_index,
"end_top_log_probs": end_top_log_probs,
"end_top_index": end_top_index,
"cls_logits": cls_logits,
}
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(list(result_with_labels["loss"].size()), [])
self.parent.assertListEqual(
list(result["start_top_log_probs"].size()), [self.batch_size, model.config.start_n_top]
)
@@ -295,14 +270,8 @@ class XLMModelTester:
model.to(torch_device)
model.eval()
(logits,) = model(input_ids)
loss, logits = model(input_ids, labels=sequence_labels)
result = {
"loss": loss,
"logits": logits,
}
result = model(input_ids)
result = model(input_ids, labels=sequence_labels)
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(list(result["logits"].size()), [self.batch_size, self.type_sequence_label_size])
@@ -323,11 +292,7 @@ class XLMModelTester:
model.to(torch_device)
model.eval()
loss, logits = model(input_ids, attention_mask=input_mask, labels=token_labels)
result = {
"loss": loss,
"logits": logits,
}
result = model(input_ids, attention_mask=input_mask, labels=token_labels)
self.parent.assertListEqual(list(result["logits"].size()), [self.batch_size, self.seq_length, self.num_labels])
self.check_loss_output(result)
@@ -350,16 +315,12 @@ class XLMModelTester:
multiple_choice_inputs_ids = input_ids.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
multiple_choice_token_type_ids = token_type_ids.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
multiple_choice_input_mask = input_mask.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
loss, logits = model(
result = model(
multiple_choice_inputs_ids,
attention_mask=multiple_choice_input_mask,
token_type_ids=multiple_choice_token_type_ids,
labels=choice_labels,
)
result = {
"loss": loss,
"logits": logits,
}
self.parent.assertListEqual(list(result["logits"].size()), [self.batch_size, self.num_choices])
self.check_loss_output(result)