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remove blocking from all .to() operations at beginning of pipeline

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This commit is contained in:
Nouamane Tazi
2022-09-13 18:06:11 +00:00
parent 96477527eb
commit cab7b285bb
1 changed files with 2 additions and 2 deletions
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src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
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@@ -190,7 +190,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
uncond_input = self.tokenizer(
[""] * batch_size, padding="max_length", max_length=max_length, return_tensors="pt"
)
uncond_embeddings = self.text_encoder(uncond_input.input_ids.to(self.device, non_blocking=True))[0]
uncond_embeddings = self.text_encoder(uncond_input.input_ids.to(self.device))[0]
# For classifier free guidance, we need to do two forward passes.
# Here we concatenate the unconditional and text embeddings into a single batch
@@ -208,7 +208,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
else:
if latents.shape != latents_shape:
raise ValueError(f"Unexpected latents shape, got {latents.shape}, expected {latents_shape}")
latents = latents.to(self.device, non_blocking=True)
latents = latents.to(self.device)
# set timesteps
accepts_offset = "offset" in set(inspect.signature(self.scheduler.set_timesteps).parameters.keys())