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DN6
2025-07-21 09:03:32 +05:30
parent 54e17f3084
commit 39be374591
2 changed files with 33 additions and 33 deletions
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54
tests/modular_pipelines/stable_diffusion_xl/test_modular_pipeline_stable_diffusion_xl.py
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@@ -99,9 +99,9 @@ class SDXLModularTests:
assert image.shape == expected_image_shape
assert (
np.abs(image_slice.flatten() - expected_slice).max() < expected_max_diff
), "Image Slice does not match expected slice"
assert np.abs(image_slice.flatten() - expected_slice).max() < expected_max_diff, (
"Image Slice does not match expected slice"
)
class SDXLModularIPAdapterTests:
@@ -114,20 +114,20 @@ class SDXLModularIPAdapterTests:
parameters = blocks.input_names
assert issubclass(self.pipeline_class, ModularIPAdapterMixin)
assert (
"ip_adapter_image" in parameters
), "`ip_adapter_image` argument must be supported by the `__call__` method"
assert "ip_adapter_image" in parameters, (
"`ip_adapter_image` argument must be supported by the `__call__` method"
)
assert "ip_adapter" in blocks.sub_blocks, "pipeline must contain an IPAdapter block"
_ = blocks.sub_blocks.pop("ip_adapter")
parameters = blocks.input_names
intermediate_parameters = blocks.intermediate_input_names
assert (
"ip_adapter_image" not in parameters
), "`ip_adapter_image` argument must be removed from the `__call__` method"
assert (
"ip_adapter_image_embeds" not in intermediate_parameters
), "`ip_adapter_image_embeds` argument must be supported by the `__call__` method"
assert "ip_adapter_image" not in parameters, (
"`ip_adapter_image` argument must be removed from the `__call__` method"
)
assert "ip_adapter_image_embeds" not in intermediate_parameters, (
"`ip_adapter_image_embeds` argument must be supported by the `__call__` method"
)
def _get_dummy_image_embeds(self, cross_attention_dim: int = 32):
return torch.randn((1, 1, cross_attention_dim), device=torch_device)
@@ -203,9 +203,9 @@ class SDXLModularIPAdapterTests:
max_diff_without_adapter_scale = np.abs(output_without_adapter_scale - output_without_adapter).max()
max_diff_with_adapter_scale = np.abs(output_with_adapter_scale - output_without_adapter).max()
assert (
max_diff_without_adapter_scale < expected_max_diff
), "Output without ip-adapter must be same as normal inference"
assert max_diff_without_adapter_scale < expected_max_diff, (
"Output without ip-adapter must be same as normal inference"
)
assert max_diff_with_adapter_scale > 1e-2, "Output with ip-adapter must be different from normal inference"
# 2. Multi IP-Adapter test cases
@@ -235,12 +235,12 @@ class SDXLModularIPAdapterTests:
output_without_multi_adapter_scale - output_without_adapter
).max()
max_diff_with_multi_adapter_scale = np.abs(output_with_multi_adapter_scale - output_without_adapter).max()
assert (
max_diff_without_multi_adapter_scale < expected_max_diff
), "Output without multi-ip-adapter must be same as normal inference"
assert (
max_diff_with_multi_adapter_scale > 1e-2
), "Output with multi-ip-adapter scale must be different from normal inference"
assert max_diff_without_multi_adapter_scale < expected_max_diff, (
"Output without multi-ip-adapter must be same as normal inference"
)
assert max_diff_with_multi_adapter_scale > 1e-2, (
"Output with multi-ip-adapter scale must be different from normal inference"
)
class SDXLModularControlNetTests:
@@ -253,9 +253,9 @@ class SDXLModularControlNetTests:
parameters = blocks.input_names
assert "control_image" in parameters, "`control_image` argument must be supported by the `__call__` method"
assert (
"controlnet_conditioning_scale" in parameters
), "`controlnet_conditioning_scale` argument must be supported by the `__call__` method"
assert "controlnet_conditioning_scale" in parameters, (
"`controlnet_conditioning_scale` argument must be supported by the `__call__` method"
)
def _modify_inputs_for_controlnet_test(self, inputs: Dict[str, Any]):
controlnet_embedder_scale_factor = 2
@@ -301,9 +301,9 @@ class SDXLModularControlNetTests:
max_diff_without_controlnet_scale = np.abs(output_without_controlnet_scale - output_without_controlnet).max()
max_diff_with_controlnet_scale = np.abs(output_with_controlnet_scale - output_without_controlnet).max()
assert (
max_diff_without_controlnet_scale < expected_max_diff
), "Output without controlnet must be same as normal inference"
assert max_diff_without_controlnet_scale < expected_max_diff, (
"Output without controlnet must be same as normal inference"
)
assert max_diff_with_controlnet_scale > 1e-2, "Output with controlnet must be different from normal inference"
def test_controlnet_cfg(self):

12
tests/modular_pipelines/test_modular_pipelines_common.py
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@@ -143,9 +143,9 @@ class ModularPipelineTesterMixin:
def _check_for_parameters(parameters, expected_parameters, param_type):
remaining_parameters = {param for param in parameters if param not in expected_parameters}
assert (
len(remaining_parameters) == 0
), f"Required {param_type} parameters not present: {remaining_parameters}"
assert len(remaining_parameters) == 0, (
f"Required {param_type} parameters not present: {remaining_parameters}"
)
_check_for_parameters(self.params, input_parameters, "input")
_check_for_parameters(self.intermediate_params, intermediate_parameters, "intermediate")
@@ -274,9 +274,9 @@ class ModularPipelineTesterMixin:
model_devices = [
component.device.type for component in pipe.components.values() if hasattr(component, "device")
]
assert all(
device == torch_device for device in model_devices
), "All pipeline components are not on accelerator device"
assert all(device == torch_device for device in model_devices), (
"All pipeline components are not on accelerator device"
)
def test_inference_is_not_nan_cpu(self):
pipe = self.get_pipeline()