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Make test_generate_with_static_cache even less flaky (#34995)

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* fix

* fix

* fix

* fix

* fix

* fix

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* fix

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2024-12-20 16:03:26 +01:00
committed by GitHub
parent 0fc2970363
commit 504c4d3692
5 changed files with 93 additions and 32 deletions
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15
tests/models/musicgen_melody/test_modeling_musicgen_melody.py
View File

@@ -41,6 +41,9 @@ from transformers.testing_utils import (
require_torch_gpu,
require_torch_sdpa,
require_torchaudio,
set_config_for_less_flaky_test,
set_model_for_less_flaky_test,
set_model_tester_for_less_flaky_test,
slow,
torch_device,
)
@@ -516,8 +519,11 @@ class MusicgenMelodyDecoderTest(ModelTesterMixin, GenerationTesterMixin, unittes
def get_mean_reldiff(failcase, x, ref, atol, rtol):
return f"{failcase}: mean relative difference: {((x - ref).abs() / (ref.abs() + 1e-12)).mean():.3e}, torch atol = {atol}, torch rtol = {rtol}"
set_model_tester_for_less_flaky_test(self)
for model_class in self.all_model_classes:
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
set_config_for_less_flaky_test(config)
model = model_class(config)
is_encoder_decoder = model.config.is_encoder_decoder
@@ -534,6 +540,9 @@ class MusicgenMelodyDecoderTest(ModelTesterMixin, GenerationTesterMixin, unittes
)
model_eager = model_eager.eval().to(torch_device)
set_model_for_less_flaky_test(model_eager)
set_model_for_less_flaky_test(model_sdpa)
# We use these for loops instead of parameterized.expand just for the interest of avoiding loading/saving 8 times the model,
# but it would be nicer to have an efficient way to use parameterized.expand
fail_cases = []
@@ -1528,8 +1537,11 @@ class MusicgenMelodyTest(ModelTesterMixin, GenerationTesterMixin, PipelineTester
def get_mean_reldiff(failcase, x, ref, atol, rtol):
return f"{failcase}: mean relative difference: {((x - ref).abs() / (ref.abs() + 1e-12)).mean():.3e}, torch atol = {atol}, torch rtol = {rtol}"
set_model_tester_for_less_flaky_test(self)
for model_class in self.all_model_classes:
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
set_config_for_less_flaky_test(config)
model = model_class(config)
is_encoder_decoder = model.config.is_encoder_decoder
@@ -1546,6 +1558,9 @@ class MusicgenMelodyTest(ModelTesterMixin, GenerationTesterMixin, PipelineTester
)
model_eager = model_eager.eval().to(torch_device)
set_model_for_less_flaky_test(model_eager)
set_model_for_less_flaky_test(model_sdpa)
# We use these for loops instead of parameterized.expand just for the interest of avoiding loading/saving 8 times the model,
# but it would be nicer to have an efficient way to use parameterized.expand
fail_cases = []

16
tests/models/seamless_m4t_v2/test_modeling_seamless_m4t_v2.py
View File

@@ -840,7 +840,13 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
def test_speech_generation(self):
config, input_speech, input_text = self.prepare_speech_and_text_input()
from transformers.testing_utils import set_config_for_less_flaky_test, set_model_for_less_flaky_test
set_config_for_less_flaky_test(config)
model = SeamlessM4Tv2Model(config=config)
set_model_for_less_flaky_test(model)
self.update_generation(model)
model.save_pretrained(self.tmpdirname)
model.to(torch_device)
@@ -852,6 +858,11 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
state_dict = model.state_dict()
text_model = SeamlessM4Tv2ForTextToSpeech.from_pretrained(self.tmpdirname)
# Even if this component is loaded after `model.save_pretrained` which is after
# `set_model_for_less_flaky_test(model)`, we still need to apply `set_model_for_less_flaky_test` here as the
# `eps` attribute in the model's norm layers is not set from the config.
set_model_for_less_flaky_test(text_model)
self.update_generation(text_model)
text_model.to(torch_device)
text_model.eval()
@@ -859,6 +870,11 @@ class SeamlessM4Tv2GenerationTest(unittest.TestCase):
output_text = self.factory_generation_speech_test(model, input_text)
speech_model = SeamlessM4Tv2ForSpeechToSpeech.from_pretrained(self.tmpdirname)
# Even if this component is loaded after `model.save_pretrained` which is after
# `set_model_for_less_flaky_test(model)`, we still need to apply `set_model_for_less_flaky_test` here as the
# `eps` attribute in the model's norm layers is not set from the config.
set_model_for_less_flaky_test(speech_model)
self.update_generation(speech_model)
speech_model.to(torch_device)
speech_model.eval()