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support no CFG in compute_clip_text_embedding
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@ -77,6 +77,10 @@ class StableDiffusion_1(LatentDiffusionModel):
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If not provided, the negative prompt is assumed to be empty (i.e., `""`).
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"""
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text = [text] if isinstance(text, str) else text
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if not self.classifier_free_guidance:
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return self.clip_text_encoder(text)
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negative_text = [negative_text] if isinstance(negative_text, str) else negative_text
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assert len(text) == len(negative_text), "The length of the text list and negative_text should be the same"
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@ -77,6 +77,10 @@ class StableDiffusion_XL(LatentDiffusionModel):
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"""
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text = [text] if isinstance(text, str) else text
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if not self.classifier_free_guidance:
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return self.clip_text_encoder(text)
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negative_text = [negative_text] if isinstance(negative_text, str) else negative_text
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assert len(text) == len(negative_text), "The length of the text list and negative_text should be the same"
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@ -114,8 +114,7 @@ def test_lcm_base(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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expected_image = expected_lcm_base
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# *NOT* compute_clip_text_embedding! We disable classifier-free guidance.
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clip_text_embedding, pooled_text_embedding = sdxl.clip_text_encoder(prompt)
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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manual_seed(2)
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@ -163,7 +162,6 @@ def test_lcm_lora_with_guidance(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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expected_image = expected_lcm_lora_1_0 if condition_scale == 1.0 else expected_lcm_lora_1_2
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# *NOT* clip_text_encoder! We use classifier-free guidance here.
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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assert time_ids.shape == (2, 6) # CFG
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@ -213,8 +211,7 @@ def test_lcm_lora_without_guidance(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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expected_image = expected_lcm_lora_1_0
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# *NOT* compute_clip_text_embedding! We disable classifier-free guidance.
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clip_text_embedding, pooled_text_embedding = sdxl.clip_text_encoder(prompt)
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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assert time_ids.shape == (1, 6) # no CFG
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@ -127,7 +127,7 @@ def test_lightning_base_4step(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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clip_text_embedding, pooled_text_embedding = sdxl.clip_text_encoder(prompt)
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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manual_seed(0)
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@ -178,7 +178,7 @@ def test_lightning_base_1step(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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clip_text_embedding, pooled_text_embedding = sdxl.clip_text_encoder(prompt)
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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manual_seed(0)
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@ -232,7 +232,7 @@ def test_lightning_lora_4step(
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prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
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clip_text_embedding, pooled_text_embedding = sdxl.clip_text_encoder(prompt)
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clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(prompt)
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time_ids = sdxl.default_time_ids
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manual_seed(0)
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