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[Use cache] Align logic of use_cache with output_attentions and output_hidden_states (#5194)

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* fix use cache

* add bart use cache

* fix bart

* finish bart
This commit is contained in:
Patrick von Platen
2020-06-24 16:09:17 +02:00
committed by GitHub
parent 64c393ee74
commit c2a26ec8a6
13 changed files with 90 additions and 21 deletions
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1
tests/test_modeling_bart.py
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@@ -153,6 +153,7 @@ class BARTModelTest(ModelTesterMixin, unittest.TestCase):
def test_advanced_inputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.use_cache = False
inputs_dict["input_ids"][:, -2:] = config.pad_token_id
decoder_input_ids, decoder_attn_mask, causal_mask = _prepare_bart_decoder_inputs(
config, inputs_dict["input_ids"]

9
tests/test_modeling_gpt2.py
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@@ -168,7 +168,14 @@ class GPT2ModelTester:
model.eval()
# first forward pass
output, past = model(input_ids, token_type_ids=token_type_ids)
outputs = model(input_ids, token_type_ids=token_type_ids, use_cache=True)
outputs_use_cache_conf = model(input_ids, token_type_ids=token_type_ids)
outputs_no_past = model(input_ids, token_type_ids=token_type_ids, use_cache=False)
self.parent.assertTrue(len(outputs) == len(outputs_use_cache_conf))
self.parent.assertTrue(len(outputs) == len(outputs_no_past) + 1)
output, past = outputs
# create hypothetical next token and extent to next_input_ids
next_tokens = ids_tensor((self.batch_size, 1), config.vocab_size)

9
tests/test_modeling_t5.py
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@@ -193,7 +193,14 @@ class T5ModelTester:
model.eval()
# first forward pass
output, past_key_value_states = model(input_ids, use_cache=True)
outputs = model(input_ids, use_cache=True)
outputs_use_cache_conf = model(input_ids)
outputs_no_past = model(input_ids, use_cache=False)
self.parent.assertTrue(len(outputs) == len(outputs_use_cache_conf))
self.parent.assertTrue(len(outputs) == len(outputs_no_past) + 1)
output, past_key_value_states = outputs
# create hypothetical next token and extent to next_input_ids
next_tokens = ids_tensor((self.batch_size, 1), config.vocab_size)

1
tests/test_modeling_tf_common.py
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@@ -126,6 +126,7 @@ class TFModelTesterMixin:
if "T5" in main_layer_class.__name__:
# Take the same values than in TFT5ModelTester for this shared layer
shared = TFSharedEmbeddings(99, 32, name="shared")
config.use_cache = False
main_layer = main_layer_class(config, embed_tokens=shared)
else:
main_layer = main_layer_class(config)

9
tests/test_modeling_tf_gpt2.py
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@@ -143,7 +143,14 @@ class TFGPT2ModelTester:
model = TFGPT2Model(config=config)
# first forward pass
output, past = model(input_ids, token_type_ids=token_type_ids)
outputs = model(input_ids, token_type_ids=token_type_ids, use_cache=True)
outputs_use_cache_conf = model(input_ids, token_type_ids=token_type_ids)
outputs_no_past = model(input_ids, token_type_ids=token_type_ids, use_cache=False)
self.parent.assertTrue(len(outputs) == len(outputs_use_cache_conf))
self.parent.assertTrue(len(outputs) == len(outputs_no_past) + 1)
output, past = outputs
# create hypothetical next token and extent to next_input_ids
next_tokens = ids_tensor((self.batch_size, 1), config.vocab_size)

10
tests/test_modeling_tf_t5.py
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@@ -135,7 +135,15 @@ class TFT5ModelTester:
self.batch_size = 1
# first forward pass
_, past_key_value_states = model(input_ids, use_cache=True)
outputs = model(input_ids, use_cache=True)
outputs_use_cache_conf = model(input_ids)
outputs_no_past = model(input_ids, use_cache=False)
self.parent.assertTrue(len(outputs) == len(outputs_use_cache_conf))
self.parent.assertTrue(len(outputs) == len(outputs_no_past) + 1)
output, past_key_value_states = outputs
# create hypothetical next token and extent to next_input_ids
next_tokens = ids_tensor((self.batch_size, 1), config.vocab_size)