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idefics2 enable_input_require_grads not aligned with disable_input_re… (#33194)

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* idefics2 enable_input_require_grads not aligned with disable_input_require_grads
make peft+idefics2 checkpoints disable fail

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* split test case

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* fix ci failure

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* refine test

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

---------

Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
This commit is contained in:
Wang, Yi
2024-09-17 17:39:34 +08:00
committed by GitHub
parent 642256de71
commit 74026b473e
3 changed files with 58 additions and 0 deletions
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38
tests/test_modeling_common.py
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@@ -403,6 +403,44 @@ class ModelTesterMixin:
m.gradient_checkpointing, f"Module {n} does not have gradient_checkpointing set to False"
)
def test_peft_gradient_checkpointing_enable_disable(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
if not model_class.supports_gradient_checkpointing:
continue
# at init model should have gradient checkpointing disabled
model = model_class(config)
self.assertFalse(model.is_gradient_checkpointing)
# check enable works
model._hf_peft_config_loaded = True
try:
model.gradient_checkpointing_enable()
except NotImplementedError:
continue
self.assertTrue(model.is_gradient_checkpointing)
# Loop over all modules and check that relevant modules have gradient_checkpointing set to True
for n, m in model.named_modules():
if hasattr(m, "gradient_checkpointing"):
self.assertTrue(
m.gradient_checkpointing, f"Module {n} does not have gradient_checkpointing set to True"
)
# check disable works
model.gradient_checkpointing_disable()
self.assertFalse(model.is_gradient_checkpointing)
# Loop over all modules and check that relevant modules have gradient_checkpointing set to False
for n, m in model.named_modules():
if hasattr(m, "gradient_checkpointing"):
self.assertFalse(
m.gradient_checkpointing, f"Module {n} does not have gradient_checkpointing set to False"
)
@is_flaky(description="low likelihood of failure, reason not yet discovered")
def test_save_load_fast_init_from_base(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()