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[No merge] TF integration testing (#7621)

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* stash

* TF Integration testing for ELECTRA, BERT, Longformer

* Trigger slow tests

* Apply suggestions from code review
This commit is contained in:
Lysandre Debut
2020-11-10 14:02:33 -05:00
committed by GitHub
parent 8fe6629bb4
commit 9fd1f56236
5 changed files with 65 additions and 3 deletions
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26
tests/test_modeling_tf_bert.py
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@@ -17,7 +17,7 @@
import unittest
from transformers import BertConfig, is_tf_available
from transformers.testing_utils import require_tf
from transformers.testing_utils import require_tf, slow
from .test_configuration_common import ConfigTester
from .test_modeling_tf_common import TFModelTesterMixin, ids_tensor
@@ -328,3 +328,27 @@ class TFBertModelTest(TFModelTesterMixin, unittest.TestCase):
self.assertEqual(sorted(output_loading_info["unexpected_keys"]), ["mlm___cls", "nsp___cls"])
for layer in output_loading_info["missing_keys"]:
self.assertTrue(layer.split("_")[0] in ["dropout", "classifier"])
class TFBertModelIntegrationTest(unittest.TestCase):
@slow
def test_inference_masked_lm(self):
model = TFBertForPreTraining.from_pretrained("lysandre/tiny-bert-random")
input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
output = model(input_ids)[0]
expected_shape = [1, 6, 10]
self.assertEqual(output.shape, expected_shape)
print(output[:, :3, :3])
expected_slice = tf.constant(
[
[
[0.03706957, 0.10124919, 0.03616843],
[-0.06099961, 0.02266058, 0.00601412],
[-0.06066202, 0.05684517, 0.02038802],
]
]
)
tf.debugging.assert_near(output[:, :3, :3], expected_slice, atol=1e-4)

16
tests/test_modeling_tf_electra.py
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@@ -248,3 +248,19 @@ class TFElectraModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in ["google/electra-small-discriminator"]:
model = TFElectraModel.from_pretrained(model_name)
self.assertIsNotNone(model)
class TFElectraModelIntegrationTest(unittest.TestCase):
@slow
def test_inference_masked_lm(self):
model = TFElectraForPreTraining.from_pretrained("lysandre/tiny-electra-random")
input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
output = model(input_ids)[0]
expected_shape = [1, 6]
self.assertEqual(output.shape, expected_shape)
print(output[:, :3])
expected_slice = tf.constant([[-0.24651965, 0.8835437, 1.823782]])
tf.debugging.assert_near(output[:, :3], expected_slice, atol=1e-4)

22
tests/test_modeling_tf_longformer.py
View File

@@ -622,3 +622,25 @@ class TFLongformerModelIntegrationTest(unittest.TestCase):
tf.debugging.assert_near(tf.reduce_mean(loss), expected_loss, rtol=1e-4)
tf.debugging.assert_near(tf.reduce_sum(prediction_scores), expected_prediction_scores_sum, rtol=1e-4)
tf.debugging.assert_near(tf.reduce_mean(prediction_scores), expected_prediction_scores_mean, rtol=1e-4)
@slow
def test_inference_masked_lm(self):
model = TFLongformerForMaskedLM.from_pretrained("lysandre/tiny-longformer-random")
input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
output = model(input_ids)[0]
expected_shape = [1, 6, 10]
self.assertEqual(output.shape, expected_shape)
print(output[:, :3, :3])
expected_slice = tf.constant(
[
[
[-0.04926379, 0.0367098, 0.02099686],
[0.03940692, 0.01547744, -0.01448723],
[0.03495252, -0.05900355, -0.01675752],
]
]
)
tf.debugging.assert_near(output[:, :3, :3], expected_slice, atol=1e-4)