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Make test_generate_with_static_cache even less flaky (#34995)

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* fix

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* fix

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---------

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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39
tests/test_modeling_common.py
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@@ -89,6 +89,9 @@ from transformers.testing_utils import (
require_torch_multi_accelerator,
require_torch_multi_gpu,
require_torch_sdpa,
set_config_for_less_flaky_test,
set_model_for_less_flaky_test,
set_model_tester_for_less_flaky_test,
slow,
torch_device,
)
@@ -3976,34 +3979,11 @@ class ModelTesterMixin:
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}"
if hasattr(self.model_tester, "num_hidden_layers"):
self.model_tester.num_hidden_layers = 1
if hasattr(self.model_tester, "vision_config") and "num_hidden_layers" in self.model_tester.vision_config:
self.model_tester.vision_config = copy.deepcopy(self.model_tester.vision_config)
self.model_tester.vision_config["num_hidden_layers"] = 1
if hasattr(self.model_tester, "text_config") and "num_hidden_layers" in self.model_tester.text_config:
self.model_tester.text_config = copy.deepcopy(self.model_tester.text_config)
self.model_tester.text_config["num_hidden_layers"] = 1
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()
config.rms_norm_eps = 1.0
config.layer_norm_eps = 1.0
config.norm_eps = 1.0
config.norm_epsilon = 1.0
config.layer_norm_epsilon = 1.0
# norm layers (layer/group norm, etc.) could cause flaky tests when the tensors have very small variance.
# (We don't need the original epsilon values to check eager/sdpa matches)
for attr in ["text_config", "vision_config", "text_encoder", "audio_encoder", "decoder"]:
if hasattr(config, attr):
getattr(config, attr).rms_norm_eps = 1.0
getattr(config, attr).layer_norm_eps = 1.0
getattr(config, attr).norm_eps = 1.0
getattr(config, attr).norm_epsilon = 1.0
getattr(config, attr).layer_norm_epsilon = 1.0
set_config_for_less_flaky_test(config)
model = model_class(config)
# FIXME: we deactivate boolean mask for models using "use_mask_token" in their constructors.
# These models support masking only in the case `use_mask_token=True`. Otherwise they cannot consume an input mask.
@@ -4029,13 +4009,8 @@ class ModelTesterMixin:
)
model_eager = model_eager.eval().to(torch_device, dtype=torch_dtype)
# Another way to make sure norm layers have desired epsilon. (Some models don't set it from its config.)
for x in model_eager.modules():
if isinstance(x, (nn.LayerNorm, nn.GroupNorm)):
x.eps = 1.0
for x in model_sdpa.modules():
if isinstance(x, (nn.LayerNorm, nn.GroupNorm)):
x.eps = 1.0
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 16 times the model,
# but it would be nicer to have an efficient way to use parameterized.expand