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[fix] pipeline_unclip generator (#1751)
* [fix] pipeline_unclip generator pass generator to all schedulers * fix fast tests test data
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@@ -292,7 +292,7 @@ class UnCLIPPipeline(DiffusionPipeline):
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# compute the previous noisy sample x_t -> x_t-1
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decoder_latents = self.decoder_scheduler.step(
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noise_pred, t, decoder_latents, prev_timestep=prev_timestep
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noise_pred, t, decoder_latents, prev_timestep=prev_timestep, generator=generator
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).prev_sample
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decoder_latents = decoder_latents.clamp(-1, 1)
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@@ -348,7 +348,7 @@ class UnCLIPPipeline(DiffusionPipeline):
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# compute the previous noisy sample x_t -> x_t-1
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super_res_latents = self.super_res_scheduler.step(
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noise_pred, t, super_res_latents, prev_timestep=prev_timestep
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noise_pred, t, super_res_latents, prev_timestep=prev_timestep, generator=generator
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).prev_sample
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image = super_res_latents
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@@ -233,15 +233,15 @@ class UnCLIPPipelineFastTests(unittest.TestCase):
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expected_slice = np.array(
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[
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0.0009,
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0.0011,
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0.0002,
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0.9962,
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0.9940,
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0.0002,
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0.9997,
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0.0003,
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0.9991,
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0.9967,
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0.0003,
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0.9997,
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0.0003,
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0.0004,
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0.9987,
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0.9989,
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]
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)
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@@ -261,7 +261,7 @@ class UnCLIPPipelineIntegrationTests(unittest.TestCase):
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def test_unclip_karlo(self):
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expected_image = load_numpy(
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"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
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"/karlo_v1_alpha/horse.npy"
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"/unclip/karlo_v1_alpha_horse.npy"
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)
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pipeline = UnCLIPPipeline.from_pretrained("kakaobrain/karlo-v1-alpha")
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