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Unverified Commit 06fd4277 authored by Aryan's avatar Aryan Committed by GitHub
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[tests] Improve Flux tests (#11919) 

update
parent 48a55125
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Showing with 30 additions and 77 deletions
tests/pipelines/flux/test_pipeline_flux.py
View file @ 06fd4277
......@@ -155,7 +155,7 @@ class FluxPipelineFastTests(
# Outputs should be different here
# For some reasons, they don't show large differences
assert max_diff > 1e-6
self.assertGreater(max_diff, 1e-6, "Outputs should be different for different prompts.")
def test_fused_qkv_projections(self):
device = "cpu" # ensure determinism for the device-dependent torch.Generator
......@@ -187,14 +187,17 @@ class FluxPipelineFastTests(
image = pipe(**inputs).images
image_slice_disabled = image[0, -3:, -3:, -1]
assert np.allclose(original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3), (
"Fusion of QKV projections shouldn't affect the outputs."
self.assertTrue(
np.allclose(original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3),
("Fusion of QKV projections shouldn't affect the outputs."),
)
assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3), (
"Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
self.assertTrue(
np.allclose(image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3),
("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."
self.assertTrue(
np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2),
("Original outputs should match when fused QKV projections are disabled."),
)
def test_flux_image_output_shape(self):
......@@ -209,7 +212,11 @@ class FluxPipelineFastTests(
inputs.update({"height": height, "width": width})
image = pipe(**inputs).images[0]
output_height, output_width, _ = image.shape
assert (output_height, output_width) == (expected_height, expected_width)
self.assertEqual(
(output_height, output_width),
(expected_height, expected_width),
f"Output shape {image.shape} does not match expected shape {(expected_height, expected_width)}",
)
def test_flux_true_cfg(self):
pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
......@@ -220,7 +227,9 @@ class FluxPipelineFastTests(
inputs["negative_prompt"] = "bad quality"
inputs["true_cfg_scale"] = 2.0
true_cfg_out = pipe(**inputs, generator=torch.manual_seed(0)).images[0]
assert not np.allclose(no_true_cfg_out, true_cfg_out)
self.assertFalse(
np.allclose(no_true_cfg_out, true_cfg_out), "Outputs should be different when true_cfg_scale is set."
)
@nightly
......@@ -269,45 +278,17 @@ class FluxPipelineSlowTests(unittest.TestCase):
image = pipe(**inputs).images[0]
image_slice = image[0, :10, :10]
# fmt: off
expected_slice = np.array(
[
0.3242,
0.3203,
0.3164,
0.3164,
0.3125,
0.3125,
0.3281,
0.3242,
0.3203,
0.3301,
0.3262,
0.3242,
0.3281,
0.3242,
0.3203,
0.3262,
0.3262,
0.3164,
0.3262,
0.3281,
0.3184,
0.3281,
0.3281,
0.3203,
0.3281,
0.3281,
0.3164,
0.3320,
0.3320,
0.3203,
],
[0.3242, 0.3203, 0.3164, 0.3164, 0.3125, 0.3125, 0.3281, 0.3242, 0.3203, 0.3301, 0.3262, 0.3242, 0.3281, 0.3242, 0.3203, 0.3262, 0.3262, 0.3164, 0.3262, 0.3281, 0.3184, 0.3281, 0.3281, 0.3203, 0.3281, 0.3281, 0.3164, 0.3320, 0.3320, 0.3203],
dtype=np.float32,
)
# fmt: on
max_diff = numpy_cosine_similarity_distance(expected_slice.flatten(), image_slice.flatten())
assert max_diff < 1e-4
self.assertLess(
max_diff, 1e-4, f"Image slice is different from expected slice: {image_slice} != {expected_slice}"
)
@slow
......@@ -377,42 +358,14 @@ class FluxIPAdapterPipelineSlowTests(unittest.TestCase):
image = pipe(**inputs).images[0]
image_slice = image[0, :10, :10]
# fmt: off
expected_slice = np.array(
[
0.1855,
0.1680,
0.1406,
0.1953,
0.1699,
0.1465,
0.2012,
0.1738,
0.1484,
0.2051,
0.1797,
0.1523,
0.2012,
0.1719,
0.1445,
0.2070,
0.1777,
0.1465,
0.2090,
0.1836,
0.1484,
0.2129,
0.1875,
0.1523,
0.2090,
0.1816,
0.1484,
0.2110,
0.1836,
0.1543,
],
[0.1855, 0.1680, 0.1406, 0.1953, 0.1699, 0.1465, 0.2012, 0.1738, 0.1484, 0.2051, 0.1797, 0.1523, 0.2012, 0.1719, 0.1445, 0.2070, 0.1777, 0.1465, 0.2090, 0.1836, 0.1484, 0.2129, 0.1875, 0.1523, 0.2090, 0.1816, 0.1484, 0.2110, 0.1836, 0.1543],
dtype=np.float32,
)
# fmt: on
max_diff = numpy_cosine_similarity_distance(expected_slice.flatten(), image_slice.flatten())
assert max_diff < 1e-4, f"{image_slice} != {expected_slice}"
self.assertLess(
max_diff, 1e-4, f"Image slice is different from expected slice: {image_slice} != {expected_slice}"
)
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