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Fix saved model creation (#5468)

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* Fix TF Serving when output_hidden_states and output_attentions are True

* Add tests for saved model creation + bug fix for multiple choices models

* remove unused import

* Fix the input for several layers

* Fix test

* Fix conflict printing

* Apply style

* Fix XLM and Flaubert for TensorFlow

* Apply style

* Fix TF check version

* Apply style

* Trigger CI
This commit is contained in:
Julien Plu
2020-08-03 14:10:40 +02:00
committed by GitHub
parent 5a0dac53bf
commit 9996f697e3
19 changed files with 572 additions and 448 deletions
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57
tests/test_modeling_tf_common.py
View File

@@ -23,7 +23,7 @@ import unittest
from importlib import import_module
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import _tf_gpu_memory_limit, require_tf
from transformers.testing_utils import _tf_gpu_memory_limit, require_tf, slow
if is_tf_available():
@@ -130,6 +130,61 @@ class TFModelTesterMixin:
self.assert_outputs_same(after_outputs, outputs)
@slow
def test_saved_model_with_hidden_states_output(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.output_hidden_states = True
for model_class in self.all_model_classes:
inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
num_out = len(model(inputs_dict))
model._saved_model_inputs_spec = None
model._set_save_spec(inputs_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
tf.saved_model.save(model, tmpdirname)
model = tf.keras.models.load_model(tmpdirname)
outputs = model(inputs_dict)
hidden_states = [t.numpy() for t in outputs[-1]]
self.assertEqual(len(outputs), num_out)
self.assertEqual(len(hidden_states), self.model_tester.num_hidden_layers + 1)
self.assertListEqual(
list(hidden_states[0].shape[-2:]), [self.model_tester.seq_length, self.model_tester.hidden_size],
)
@slow
def test_saved_model_with_attentions_output(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.output_attentions = True
encoder_seq_length = (
self.model_tester.encoder_seq_length
if hasattr(self.model_tester, "encoder_seq_length")
else self.model_tester.seq_length
)
encoder_key_length = (
self.model_tester.key_length if hasattr(self.model_tester, "key_length") else encoder_seq_length
)
for model_class in self.all_model_classes:
inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
num_out = len(model(inputs_dict))
model._saved_model_inputs_spec = None
model._set_save_spec(inputs_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
tf.saved_model.save(model, tmpdirname)
model = tf.keras.models.load_model(tmpdirname)
outputs = model(inputs_dict)
attentions = [t.numpy() for t in outputs[-1]]
self.assertEqual(len(outputs), num_out)
self.assertEqual(len(attentions), self.model_tester.num_hidden_layers)
self.assertListEqual(
list(attentions[0].shape[-3:]),
[self.model_tester.num_attention_heads, encoder_seq_length, encoder_key_length],
)
def test_keras_save_load(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

8
tests/test_modeling_tf_xlnet.py
View File

@@ -342,11 +342,17 @@ class TFXLNetModelTester:
"attention_mask": multiple_choice_input_mask,
"token_type_ids": multiple_choice_token_type_ids,
}
(logits,) = model(inputs)
(logits, mems_1) = model(inputs)
result = {
"mems_1": [mem.numpy() for mem in mems_1],
"logits": logits.numpy(),
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_1"]),
[[self.seq_length, self.batch_size * self.num_choices, self.hidden_size]] * self.num_hidden_layers,
)
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()