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Cleaning TensorFlow models (#5229)

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* Cleaning TensorFlow models

Update all classes


stylr

* Don't average loss
This commit is contained in:
Lysandre Debut
2020-06-24 11:37:20 -04:00
committed by GitHub
parent 609e0c583f
commit cf10d4cfdd
13 changed files with 483 additions and 126 deletions
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42
tests/test_modeling_tf_distilbert.py
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@@ -24,11 +24,14 @@ from .utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers.modeling_tf_distilbert import (
TFDistilBertModel,
TFDistilBertForMaskedLM,
TFDistilBertForQuestionAnswering,
TFDistilBertForSequenceClassification,
TFDistilBertForTokenClassification,
TFDistilBertForMultipleChoice,
)
@@ -147,6 +150,35 @@ class TFDistilBertModelTester:
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_labels])
def create_and_check_distilbert_for_multiple_choice(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_choices = self.num_choices
model = TFDistilBertForMultipleChoice(config)
multiple_choice_inputs_ids = tf.tile(tf.expand_dims(input_ids, 1), (1, self.num_choices, 1))
multiple_choice_input_mask = tf.tile(tf.expand_dims(input_mask, 1), (1, self.num_choices, 1))
inputs = {
"input_ids": multiple_choice_inputs_ids,
"attention_mask": multiple_choice_input_mask,
}
(logits,) = model(inputs)
result = {
"logits": logits.numpy(),
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
def create_and_check_distilbert_for_token_classification(
self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_labels = self.num_labels
model = TFDistilBertForTokenClassification(config)
inputs = {"input_ids": input_ids, "attention_mask": input_mask}
(logits,) = model(inputs)
result = {
"logits": logits.numpy(),
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.seq_length, self.num_labels])
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()
(config, input_ids, input_mask, sequence_labels, token_labels, choice_labels) = config_and_inputs
@@ -163,6 +195,8 @@ class TFDistilBertModelTest(TFModelTesterMixin, unittest.TestCase):
TFDistilBertForMaskedLM,
TFDistilBertForQuestionAnswering,
TFDistilBertForSequenceClassification,
TFDistilBertForTokenClassification,
TFDistilBertForMultipleChoice,
)
if is_tf_available()
else None
@@ -194,6 +228,14 @@ class TFDistilBertModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_distilbert_for_sequence_classification(*config_and_inputs)
def test_for_multiple_choice(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_distilbert_for_multiple_choice(*config_and_inputs)
def test_for_token_classification(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_distilbert_for_token_classification(*config_and_inputs)
# @slow
# def test_model_from_pretrained(self):
# for model_name in list(DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: