SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

[WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… (#5614)

Browse Source 
* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests

* AutoModels


Tiny tweaks

* Style

* Final changes before merge

* Re-order for simpler review

* Final fixes

* Addressing @sgugger's comments

* Test MultipleChoice
This commit is contained in:
Lysandre Debut
2020-07-29 14:26:26 -04:00
committed by GitHub
parent 8a8ae27617
commit 3f94170a10
12 changed files with 652 additions and 21 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
tests/test_modeling_tf_xlm.py
View File

@@ -32,6 +32,7 @@ if is_tf_available():
TFXLMForSequenceClassification,
TFXLMForQuestionAnsweringSimple,
TFXLMForTokenClassification,
TFXLMForMultipleChoice,
TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
)
@@ -91,6 +92,7 @@ class TFXLMModelTester:
sequence_labels = ids_tensor([self.batch_size], self.type_sequence_label_size)
token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels)
is_impossible_labels = ids_tensor([self.batch_size], 2, dtype=tf.float32)
choice_labels = ids_tensor([self.batch_size], self.num_choices)
config = XLMConfig(
vocab_size=self.vocab_size,
@@ -120,6 +122,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
)
@@ -132,6 +135,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = TFXLMModel(config=config)
@@ -157,6 +161,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = TFXLMWithLMHeadModel(config)
@@ -181,6 +186,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = TFXLMForQuestionAnsweringSimple(config)
@@ -206,6 +212,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
model = TFXLMForSequenceClassification(config)
@@ -229,6 +236,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
config.num_labels = self.num_labels
@@ -240,6 +248,32 @@ class TFXLMModelTester:
}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.seq_length, self.num_labels])
def create_and_check_xlm_for_multiple_choice(
self,
config,
input_ids,
token_type_ids,
input_lengths,
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
):
config.num_choices = self.num_choices
model = TFXLMForMultipleChoice(config=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))
multiple_choice_token_type_ids = tf.tile(tf.expand_dims(token_type_ids, 1), (1, self.num_choices, 1))
inputs = {
"input_ids": multiple_choice_inputs_ids,
"attention_mask": multiple_choice_input_mask,
"token_type_ids": multiple_choice_token_type_ids,
}
(logits,) = model(inputs)
result = {"logits": logits.numpy()}
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()
(
@@ -250,6 +284,7 @@ class TFXLMModelTester:
sequence_labels,
token_labels,
is_impossible_labels,
choice_labels,
input_mask,
) = config_and_inputs
inputs_dict = {
@@ -265,13 +300,13 @@ class TFXLMModelTester:
class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
all_model_classes = (
# TODO The multiple choice model is missing and should be added.
(
TFXLMModel,
TFXLMWithLMHeadModel,
TFXLMForSequenceClassification,
TFXLMForQuestionAnsweringSimple,
TFXLMForTokenClassification,
TFXLMForMultipleChoice,
)
if is_tf_available()
else ()
@@ -307,6 +342,10 @@ class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_xlm_for_token_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_xlm_for_multiple_choice(*config_and_inputs)
@slow
def test_model_from_pretrained(self):
for model_name in TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: