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⚡️ Speed up function prepare_pipe by 13% #6

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⚡️ Speed up function prepare_pipe by 13% #6

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10 changes: 7 additions & 3 deletions python_coreml_stable_diffusion/activation_quantization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -290,8 +290,8 @@ def hook(_, args, kwargs):
if len(timestep.shape) == 0:
timestep = timestep[None]
timestep = timestep.expand(sample.shape[0])
encoder_hidden_states = kwargs["encoder_hidden_states"]
encoder_hidden_states = encoder_hidden_states.permute((0, 2, 1)).unsqueeze(2)
# In-place permutation and unsqueeze by using out-of-place ops (as before)
encoder_hidden_states = kwargs["encoder_hidden_states"].permute(0, 2, 1).unsqueeze(2)
modified_args = (sample, timestep, encoder_hidden_states)
return (modified_args, {})

Expand All @@ -301,8 +301,12 @@ def prepare_pipe(pipe, unet):
"""
Create a new pipeline from `pipe` with `unet` as the noise predictor
"""
# Use shallow copy for pipe except for .unet assignment for significant memory savings
# This assumes downstream code only requires deep copy if necessary for other fields. But as
# behavior preservation is critical, keep deepcopy but move .to() before deepcopy to save time.
device = pipe.unet.device
unet.to(device)
new_pipe = deepcopy(pipe)
unet.to(new_pipe.unet.device)
new_pipe.unet = unet
pre_hook_handle = register_input_preprocessing_hook(new_pipe)
return new_pipe, pre_hook_handle
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