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Add a test for mixed precision (#9806)

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This commit is contained in:
Julien Plu
2021-01-27 09:36:49 +01:00
committed by GitHub
parent d5b40d6693
commit 2c891c156d
20 changed files with 105 additions and 8 deletions
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4
tests/test_modeling_tf_albert.py
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@@ -294,6 +294,10 @@ class TFAlbertModelTest(TFModelTesterMixin, unittest.TestCase):
name = model.get_bias()
assert name is None
def test_mixed_precision(self):
# TODO JP: Make ALBERT float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

4
tests/test_modeling_tf_bart.py
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@@ -278,6 +278,10 @@ class TFBartModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make BART float16 compliant
pass
def _assert_tensors_equal(a, b, atol=1e-12, prefix=""):
"""If tensors not close, or a and b arent both tensors, raise a nice Assertion error."""

4
tests/test_modeling_tf_blenderbot.py
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@@ -214,6 +214,10 @@ class TFBlenderbotModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Blenderbot float16 compliant
pass
def test_resize_token_embeddings(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

4
tests/test_modeling_tf_blenderbot_small.py
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@@ -279,6 +279,10 @@ class TFBlenderbotSmallModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Blenderbot Small float16 compliant
pass
def _assert_tensors_equal(a, b, atol=1e-12, prefix=""):
"""If tensors not close, or a and b arent both tensors, raise a nice Assertion error."""

14
tests/test_modeling_tf_common.py
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@@ -279,6 +279,20 @@ class TFModelTesterMixin:
[self.model_tester.num_attention_heads, encoder_seq_length, encoder_key_length],
)
def test_mixed_precision(self):
tf.keras.mixed_precision.experimental.set_policy("mixed_float16")
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
class_inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
outputs = model(class_inputs_dict)
self.assertIsNotNone(outputs)
tf.keras.mixed_precision.experimental.set_policy("float32")
def test_keras_save_load(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

4
tests/test_modeling_tf_ctrl.py
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@@ -221,6 +221,10 @@ class TFCTRLModelTest(TFModelTesterMixin, unittest.TestCase):
name = model.get_bias()
assert name is None
def test_mixed_precision(self):
# TODO JP: Make CTRL float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

8
tests/test_modeling_tf_flaubert.py
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@@ -330,12 +330,8 @@ class TFFlaubertModelTest(TFModelTesterMixin, unittest.TestCase):
model = TFFlaubertModel.from_pretrained(model_name)
self.assertIsNotNone(model)
def test_saved_model_with_hidden_states_output(self):
# Should be uncommented during patrick TF refactor
pass
def test_saved_model_with_attentions_output(self):
# Should be uncommented during patrick TF refactor
def test_mixed_precision(self):
# TODO JP: Make Flaubert float16 compliant
pass

8
tests/test_modeling_tf_funnel.py
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@@ -371,6 +371,10 @@ class TFFunnelModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Funnel float16 compliant
pass
@require_tf
class TFFunnelBaseModelTest(TFModelTesterMixin, unittest.TestCase):
@@ -401,3 +405,7 @@ class TFFunnelBaseModelTest(TFModelTesterMixin, unittest.TestCase):
def test_saved_model_creation(self):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Funnel float16 compliant
pass

4
tests/test_modeling_tf_gpt2.py
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@@ -387,6 +387,10 @@ class TFGPT2ModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_gpt2_for_sequence_classification(*config_and_inputs)
def test_mixed_precision(self):
# TODO JP: Make GPT2 float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

4
tests/test_modeling_tf_led.py
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@@ -357,6 +357,10 @@ class TFLEDModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make LED float16 compliant
pass
def test_saved_model_with_attentions_output(self):
# This test don't pass because of the error:
# condition [13,8,4,5], then [13,8,4,5], and else [13,8,4,6] must be broadcastable

15
tests/test_modeling_tf_longformer.py
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@@ -340,14 +340,25 @@ class TFLongformerModelTest(TFModelTesterMixin, unittest.TestCase):
@slow
def test_saved_model_with_attentions_output(self):
# longformer has special attentions which are not
# compatible in graph mode
# This test don't pass because of the error:
# condition [13,8,4,5], then [13,8,4,5], and else [13,8,4,6] must be broadcastable
# This occurs line 323 in modeling_tf_led.py because the condition line 255
# returns a tensor of shape
# [batch_size, seq_len, self.num_heads, self.one_sided_attn_window_size * 2 + 2]
# if is_global_attn is True and a tensor of shape
# [batch_size, seq_len, self.num_heads, self.one_sided_attn_window_size * 2 + 1]
# This is due to the tf.concat call line 703 that adds one dimension
# Need to check with PVP how to properly fix this
pass
def test_saved_model_creation(self):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Longformer float16 compliant
pass
@require_tf
@require_sentencepiece

4
tests/test_modeling_tf_lxmert.py
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@@ -704,6 +704,10 @@ class TFLxmertModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Lxmert float16 compliant
pass
@slow
def test_saved_model_with_hidden_states_output(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

4
tests/test_modeling_tf_marian.py
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@@ -247,6 +247,10 @@ class TFMarianModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Marian float16 compliant
pass
def test_resize_token_embeddings(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

4
tests/test_modeling_tf_mbart.py
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@@ -218,6 +218,10 @@ class TFMBartModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make MBart float16 compliant
pass
def test_resize_token_embeddings(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

4
tests/test_modeling_tf_mobilebert.py
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@@ -309,6 +309,10 @@ class TFMobileBertModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make MobileBert float16 compliant
pass
@slow
def test_model_from_pretrained(self):
# for model_name in TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

4
tests/test_modeling_tf_openai.py
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@@ -245,6 +245,10 @@ class TFOpenAIGPTModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_openai_gpt_for_sequence_classification(*config_and_inputs)
def test_mixed_precision(self):
# TODO JP: Make OpenAIGPT float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

4
tests/test_modeling_tf_pegasus.py
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@@ -245,6 +245,10 @@ class TFPegasusModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make Pegasus float16 compliant
pass
def test_resize_token_embeddings(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()

8
tests/test_modeling_tf_t5.py
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@@ -306,6 +306,10 @@ class TFT5ModelTest(TFModelTesterMixin, unittest.TestCase):
# This test is too long (>30sec) and makes fail the CI
pass
def test_mixed_precision(self):
# TODO JP: Make T5 float16 compliant
pass
@slow
def test_model_from_pretrained(self):
model = TFT5Model.from_pretrained("t5-small")
@@ -435,6 +439,10 @@ class TFT5EncoderOnlyModelTest(TFModelTesterMixin, unittest.TestCase):
def test_train_pipeline_custom_model(self):
pass
def test_mixed_precision(self):
# TODO JP: Make T5 float16 compliant
pass
@require_tf
@require_sentencepiece

4
tests/test_modeling_tf_transfo_xl.py
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@@ -204,6 +204,10 @@ class TFTransfoXLModelTest(TFModelTesterMixin, unittest.TestCase):
name = model.get_bias()
assert name is None
def test_mixed_precision(self):
# TODO JP: Make TransfoXL float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

4
tests/test_modeling_tf_xlm.py
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@@ -326,6 +326,10 @@ class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_xlm_for_multiple_choice(*config_and_inputs)
def test_mixed_precision(self):
# TODO JP: Make XLM float16 compliant
pass
@slow
def test_model_from_pretrained(self):
for model_name in TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: