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update

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DN6
2025-10-24 10:07:23 +05:30
parent 1f217a5440
commit 1d9dfd2c19
1 changed files with 36 additions and 43 deletions
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79
tests/pipelines/test_pipelines_common.py
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@@ -48,12 +48,6 @@ from diffusers.utils import logging
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.source_code_parsing_utils import ReturnNameVisitor
from ..models.autoencoders.vae import (
get_asym_autoencoder_kl_config,
get_autoencoder_kl_config,
get_autoencoder_tiny_config,
get_consistency_vae_config,
)
from ..models.transformers.test_models_transformer_flux import create_flux_ip_adapter_state_dict
from ..models.unets.test_models_unet_2d_condition import (
create_ip_adapter_faceid_state_dict,
@@ -70,7 +64,6 @@ from ..testing_utils import (
require_torch,
require_torch_accelerator,
require_transformers_version_greater,
skip_mps,
torch_device,
)
@@ -193,12 +186,12 @@ class SDFunctionTesterMixin:
and hasattr(component, "original_attn_processors")
and component.original_attn_processors is not None
):
assert check_qkv_fusion_processors_exist(
component
), "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
assert check_qkv_fusion_matches_attn_procs_length(
component, component.original_attn_processors
), "Something wrong with the attention processors concerning the fused QKV projections."
assert check_qkv_fusion_processors_exist(component), (
"Something wrong with the fused attention processors. Expected all the attention processors to be fused."
)
assert check_qkv_fusion_matches_attn_procs_length(component, component.original_attn_processors), (
"Something wrong with the attention processors concerning the fused QKV projections."
)
inputs = self.get_dummy_inputs(device)
inputs["return_dict"] = False
@@ -211,15 +204,15 @@ class SDFunctionTesterMixin:
image_disabled = pipe(**inputs)[0]
image_slice_disabled = image_disabled[0, -3:, -3:, -1]
assert np.allclose(
original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2
), "Fusion of QKV projections shouldn't affect the outputs."
assert np.allclose(
image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2
), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
assert np.allclose(
original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
), "Original outputs should match when fused QKV projections are disabled."
assert np.allclose(original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2), (
"Fusion of QKV projections shouldn't affect the outputs."
)
assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2), (
"Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
)
assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
"Original outputs should match when fused QKV projections are disabled."
)
class IPAdapterTesterMixin:
@@ -862,9 +855,9 @@ class PipelineFromPipeTesterMixin:
for component in pipe_original.components.values():
if hasattr(component, "attn_processors"):
assert all(
type(proc) == AttnProcessor for proc in component.attn_processors.values()
), "`from_pipe` changed the attention processor in original pipeline."
assert all(type(proc) == AttnProcessor for proc in component.attn_processors.values()), (
"`from_pipe` changed the attention processor in original pipeline."
)
@require_accelerator
@require_accelerate_version_greater("0.14.0")
@@ -2632,12 +2625,12 @@ class PyramidAttentionBroadcastTesterMixin:
image_slice_pab_disabled = output.flatten()
image_slice_pab_disabled = np.concatenate((image_slice_pab_disabled[:8], image_slice_pab_disabled[-8:]))
assert np.allclose(
original_image_slice, image_slice_pab_enabled, atol=expected_atol
), "PAB outputs should not differ much in specified timestep range."
assert np.allclose(
original_image_slice, image_slice_pab_disabled, atol=1e-4
), "Outputs from normal inference and after disabling cache should not differ."
assert np.allclose(original_image_slice, image_slice_pab_enabled, atol=expected_atol), (
"PAB outputs should not differ much in specified timestep range."
)
assert np.allclose(original_image_slice, image_slice_pab_disabled, atol=1e-4), (
"Outputs from normal inference and after disabling cache should not differ."
)
class FasterCacheTesterMixin:
@@ -2702,12 +2695,12 @@ class FasterCacheTesterMixin:
output = run_forward(pipe).flatten()
image_slice_faster_cache_disabled = np.concatenate((output[:8], output[-8:]))
assert np.allclose(
original_image_slice, image_slice_faster_cache_enabled, atol=expected_atol
), "FasterCache outputs should not differ much in specified timestep range."
assert np.allclose(
original_image_slice, image_slice_faster_cache_disabled, atol=1e-4
), "Outputs from normal inference and after disabling cache should not differ."
assert np.allclose(original_image_slice, image_slice_faster_cache_enabled, atol=expected_atol), (
"FasterCache outputs should not differ much in specified timestep range."
)
assert np.allclose(original_image_slice, image_slice_faster_cache_disabled, atol=1e-4), (
"Outputs from normal inference and after disabling cache should not differ."
)
def test_faster_cache_state(self):
from diffusers.hooks.faster_cache import _FASTER_CACHE_BLOCK_HOOK, _FASTER_CACHE_DENOISER_HOOK
@@ -2842,12 +2835,12 @@ class FirstBlockCacheTesterMixin:
output = run_forward(pipe).flatten()
image_slice_fbc_disabled = np.concatenate((output[:8], output[-8:]))
assert np.allclose(
original_image_slice, image_slice_fbc_enabled, atol=expected_atol
), "FirstBlockCache outputs should not differ much."
assert np.allclose(
original_image_slice, image_slice_fbc_disabled, atol=1e-4
), "Outputs from normal inference and after disabling cache should not differ."
assert np.allclose(original_image_slice, image_slice_fbc_enabled, atol=expected_atol), (
"FirstBlockCache outputs should not differ much."
)
assert np.allclose(original_image_slice, image_slice_fbc_disabled, atol=1e-4), (
"Outputs from normal inference and after disabling cache should not differ."
)
# Some models (e.g. unCLIP) are extremely likely to significantly deviate depending on which hardware is used.