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Revert cond + uncond batching

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This commit is contained in:
Edna
2025-06-12 03:40:52 -06:00
committed by GitHub
parent abf8a33a96
commit 7235805e75
1 changed files with 12 additions and 9 deletions
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21
src/diffusers/pipelines/chroma/pipeline_chroma.py
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@@ -694,9 +694,6 @@ class ChromaPipeline(
max_sequence_length=max_sequence_length,
lora_scale=lora_scale,
)
if self.do_classifier_free_guidance:
prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds], dim=0)
# 4. Prepare latent variables
num_channels_latents = self.transformer.config.in_channels // 4
@@ -773,13 +770,11 @@ class ChromaPipeline(
if image_embeds is not None:
self._joint_attention_kwargs["ip_adapter_image_embeds"] = image_embeds
# expand the latents if we are doing classifier free guidance
latent_model_input = torch.cat([latents] * 2) if self.do_classifier_free_guidance else latents
# broadcast to batch dimension in a way that's compatible with ONNX/Core ML
timestep = t.expand(latent_model_input.shape[0]).to(latents.dtype)
timestep = t.expand(latents.shape[0]).to(latents.dtype)
noise_pred = self.transformer(
hidden_states=latent_model_input,
hidden_states=latents,
timestep=timestep / 1000,
encoder_hidden_states=prompt_embeds,
txt_ids=text_ids,
@@ -791,8 +786,16 @@ class ChromaPipeline(
if self.do_classifier_free_guidance:
if negative_image_embeds is not None:
self._joint_attention_kwargs["ip_adapter_image_embeds"] = negative_image_embeds
noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
noise_pred = noise_pred_uncond + self.guidance_scale * (noise_pred_text - noise_pred_uncond)
neg_noise_pred = self.transformer(
hidden_states=latents,
timestep=timestep / 1000,
encoder_hidden_states=negative_prompt_embeds,
txt_ids=negative_text_ids,
img_ids=latent_image_ids,
joint_attention_kwargs=self.joint_attention_kwargs,
return_dict=False,
)[0]
noise_pred = neg_noise_pred + guidance_scale * (noise_pred - neg_noise_pred)
# compute the previous noisy sample x_t -> x_t-1
latents_dtype = latents.dtype