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Fix typo in AttnProcessor2_0 symbol (#2404) 

Fix typo in AttnProcessor2_0 symbol.
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Pedro Cuenca 2023-02-17 21:21:18 +01:00 committed by GitHub
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commit 780b3a4f8c
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2 changed files with 6 additions and 6 deletions
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4
docs/source/en/optimization/torch2.0.mdx
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@ -50,10 +50,10 @@ pip install --pre torch torchvision --index-url https://download.pytorch.org/whl
```Python ```Python
import torch import torch
from diffusers import StableDiffusionPipeline from diffusers import StableDiffusionPipeline
from diffusers.models.cross_attention import AttnProccesor2_0 from diffusers.models.cross_attention import AttnProcessor2_0
pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to("cuda") pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to("cuda")
pipe.unet.set_attn_processor(AttnProccesor2_0()) pipe.unet.set_attn_processor(AttnProcessor2_0())
prompt = "a photo of an astronaut riding a horse on mars" prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt).images[0] image = pipe(prompt).images[0]

8
src/diffusers/models/cross_attention.py
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@ -99,10 +99,10 @@ class CrossAttention(nn.Module):
self.to_out.append(nn.Dropout(dropout)) self.to_out.append(nn.Dropout(dropout))
# set attention processor # set attention processor
# We use the AttnProccesor2_0 by default when torch2.x is used which uses # We use the AttnProcessor2_0 by default when torch2.x is used which uses
# torch.nn.functional.scaled_dot_product_attention for native Flash/memory_efficient_attention # torch.nn.functional.scaled_dot_product_attention for native Flash/memory_efficient_attention
if processor is None: if processor is None:
processor = AttnProccesor2_0() if hasattr(F, "scaled_dot_product_attention") else CrossAttnProcessor() processor = AttnProcessor2_0() if hasattr(F, "scaled_dot_product_attention") else CrossAttnProcessor()
self.set_processor(processor) self.set_processor(processor)
def set_use_memory_efficient_attention_xformers( def set_use_memory_efficient_attention_xformers(
@ -466,10 +466,10 @@ class XFormersCrossAttnProcessor:
return hidden_states return hidden_states
class AttnProccesor2_0: class AttnProcessor2_0:
def __init__(self): def __init__(self):
if not hasattr(F, "scaled_dot_product_attention"): if not hasattr(F, "scaled_dot_product_attention"):
raise ImportError("AttnProccesor2_0 requires PyTorch 2.0, to use it, please upgrade PyTorch to 2.0.") raise ImportError("AttnProcessor2_0 requires PyTorch 2.0, to use it, please upgrade PyTorch to 2.0.")
def __call__(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None): def __call__(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None):
batch_size, sequence_length, inner_dim = hidden_states.shape batch_size, sequence_length, inner_dim = hidden_states.shape