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[T5 failing CI] Fix generate test (#11770)

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* fix_torch_device_generate_test

* remove @
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Patrick von Platen 2021-05-19 10:31:17 +01:00 committed by GitHub
parent 680d181ce8
commit 43891be19b
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2 changed files with 15 additions and 8 deletions
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10
tests/test_generation_utils.py
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@ -1084,9 +1084,13 @@ class GenerationTesterMixin:
continue continue
head_masking = { head_masking = {
"head_mask": torch.zeros(config.encoder_layers, config.encoder_attention_heads), "head_mask": torch.zeros(config.encoder_layers, config.encoder_attention_heads, device=torch_device),
"decoder_head_mask": torch.zeros(config.decoder_layers, config.decoder_attention_heads), "decoder_head_mask": torch.zeros(
"cross_attn_head_mask": torch.zeros(config.decoder_layers, config.decoder_attention_heads), config.decoder_layers, config.decoder_attention_heads, device=torch_device
),
"cross_attn_head_mask": torch.zeros(
config.decoder_layers, config.decoder_attention_heads, device=torch_device
),
} }
signature = inspect.signature(model.forward) signature = inspect.signature(model.forward)

13
tests/test_modeling_t5.py
View File

@ -605,19 +605,22 @@ class T5ModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
config = config_and_inputs[0] config = config_and_inputs[0]
max_length = config_and_inputs[1].shape[-1] + 3 max_length = config_and_inputs[1].shape[-1] + 3
model = T5ForConditionalGeneration(config) model = T5ForConditionalGeneration(config).eval()
model.to(torch_device)
head_masking = { head_masking = {
"head_mask": torch.zeros(config.num_layers, config.num_heads), "head_mask": torch.zeros(config.num_layers, config.num_heads, device=torch_device),
"decoder_head_mask": torch.zeros(config.num_decoder_layers, config.num_heads), "decoder_head_mask": torch.zeros(config.num_decoder_layers, config.num_heads, device=torch_device),
"cross_attn_head_mask": torch.zeros(config.num_decoder_layers, config.num_heads), "cross_attn_head_mask": torch.zeros(config.num_decoder_layers, config.num_heads, device=torch_device),
} }
for attn_name, (name, mask) in zip(attention_names, head_masking.items()): for attn_name, (name, mask) in zip(attention_names, head_masking.items()):
head_masks = {name: mask} head_masks = {name: mask}
# Explicitly pass decoder_head_mask as it is required from T5 model when head_mask specified # Explicitly pass decoder_head_mask as it is required from T5 model when head_mask specified
if name == "head_mask": if name == "head_mask":
head_masks["decoder_head_mask"] = torch.ones(config.num_decoder_layers, config.num_heads) head_masks["decoder_head_mask"] = torch.ones(
config.num_decoder_layers, config.num_heads, device=torch_device
)
out = model.generate( out = model.generate(
config_and_inputs[1], config_and_inputs[1],