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cache non lora pipeline outputs.

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This commit is contained in:
sayakpaul
2025-09-08 11:39:11 +05:30
parent fc337d5853
commit 02fd92e38e
1 changed files with 49 additions and 31 deletions
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80
tests/lora/utils.py
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@@ -129,6 +129,30 @@ class PeftLoraLoaderMixinTests:
text_encoder_target_modules = ["q_proj", "k_proj", "v_proj", "out_proj"]
denoiser_target_modules = ["to_q", "to_k", "to_v", "to_out.0"]
cached_non_lora_outputs = {}
@pytest.fixture(scope="class", autouse=True)
def cache_non_lora_outputs(self, request):
"""
This fixture will be executed once per test class and will populate
the cached_non_lora_outputs dictionary.
"""
for scheduler_cls in self.scheduler_classes:
# Check if the output for this scheduler is already cached to avoid re-running
if scheduler_cls.__name__ in self.cached_non_lora_outputs:
continue
components, _, _ = self.get_dummy_components(scheduler_cls)
pipe = self.pipeline_class(**components)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
# Always ensure the inputs are without the `generator`. Make sure to pass the `generator`
# explicitly.
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.cached_non_lora_outputs[scheduler_cls.__name__] = output_no_lora
def get_dummy_components(self, scheduler_cls=None, use_dora=False, lora_alpha=None):
if self.unet_kwargs and self.transformer_kwargs:
raise ValueError("Both `unet_kwargs` and `transformer_kwargs` cannot be specified.")
@@ -320,13 +344,7 @@ class PeftLoraLoaderMixinTests:
Tests a simple inference and makes sure it works as expected
"""
for scheduler_cls in self.scheduler_classes:
components, text_lora_config, _ = self.get_dummy_components(scheduler_cls)
pipe = self.pipeline_class(**components)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs()
output_no_lora = pipe(**inputs)[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
def test_simple_inference_with_text_lora(self):
@@ -341,7 +359,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -424,7 +442,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -480,7 +498,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -518,7 +536,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -550,7 +568,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -585,7 +603,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -636,7 +654,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -687,7 +705,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config=None)
@@ -730,7 +748,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -771,7 +789,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -815,7 +833,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -853,7 +871,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, denoiser = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -932,7 +950,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
@@ -1061,7 +1079,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
self.assertTrue(check_if_lora_correctly_set(pipe.text_encoder), "Lora not correctly set in text encoder")
@@ -1118,7 +1136,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
@@ -1281,7 +1299,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
@@ -1375,7 +1393,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
pipe.text_encoder.add_adapter(text_lora_config, "adapter-1")
@@ -1619,7 +1637,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
@@ -1700,7 +1718,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
@@ -1755,7 +1773,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_dora_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_dora_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_dora_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -1887,7 +1905,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
original_out = pipe(**inputs, generator=torch.manual_seed(0))[0]
original_out = self.cached_non_lora_outputs[scheduler_cls.__name__]
no_op_state_dict = {"lora_foo": torch.tensor(2.0), "lora_bar": torch.tensor(3.0)}
logger = logging.get_logger("diffusers.loaders.peft")
@@ -1933,7 +1951,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(pipe, text_lora_config, denoiser_lora_config)
@@ -2287,7 +2305,7 @@ class PeftLoraLoaderMixinTests:
pipe = self.pipeline_class(**components).to(torch_device)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs(scheduler_cls.__name__)
self.assertTrue(output_no_lora.shape == self.output_shape)
pipe, _ = self.add_adapters_to_pipeline(
@@ -2337,7 +2355,7 @@ class PeftLoraLoaderMixinTests:
pipe.set_progress_bar_config(disable=None)
_, _, inputs = self.get_dummy_inputs(with_generator=False)
output_no_lora = pipe(**inputs, generator=torch.manual_seed(0))[0]
output_no_lora = self.cached_non_lora_outputs[scheduler_cls.__name__]
if "text_encoder" in self.pipeline_class._lora_loadable_modules:
pipe.text_encoder.add_adapter(text_lora_config)