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Make (TF) CI faster (test only a subset of model classes) (#24592)

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* fix

* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar 2023-06-30 16:54:54 +02:00 committed by GitHub
parent 78a2b19fc8
commit 3441ad7d43
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GPG key ID: 4AEE18F83AFDEB23
2 changed files with 8 additions and 8 deletions
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4
tests/test_modeling_tf_common.py
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@ -341,7 +341,7 @@ class TFModelTesterMixin:
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
model = model_class(config)
model.build()
@ -689,7 +689,7 @@ class TFModelTesterMixin:
def test_compile_tf_model(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
# Prepare our model
model = model_class(config)
# These are maximally general inputs for the model, with multiple None dimensions

12
tests/utils/test_modeling_tf_core.py
View file

@ -111,7 +111,7 @@ class TFCoreModelTesterMixin:
@slow
def test_graph_mode(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
inputs = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
@ -125,7 +125,7 @@ class TFCoreModelTesterMixin:
@slow
def test_xla_mode(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
inputs = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
@ -140,7 +140,7 @@ class TFCoreModelTesterMixin:
def test_xla_fit(self):
# This is a copy of the test_keras_fit method, but we use XLA compilation instead of eager
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
model = model_class(config)
if getattr(model, "hf_compute_loss", None):
# Test that model correctly compute the loss with kwargs
@ -214,7 +214,7 @@ class TFCoreModelTesterMixin:
encoder_seq_length = getattr(self.model_tester, "encoder_seq_length", self.model_tester.seq_length)
encoder_key_length = getattr(self.model_tester, "key_length", encoder_seq_length)
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
class_inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
model.build()
@ -269,7 +269,7 @@ class TFCoreModelTesterMixin:
# try/finally block to ensure subsequent tests run in float32
try:
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
class_inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config)
outputs = model(class_inputs_dict)
@ -352,7 +352,7 @@ class TFCoreModelTesterMixin:
def test_graph_mode_with_inputs_embeds(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
for model_class in self.all_model_classes[:2]:
model = model_class(config)
inputs = copy.deepcopy(inputs_dict)