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adding enable_vae_tiling and disable_vae_tiling functions (#3225)

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adding enable_vae_tiling and disable_val_tiling functions
This commit is contained in:
Isaac
2023-04-25 18:42:21 +05:30
committed by Daniel Gu
parent 4e03663091
commit 167cb7ae17
1 changed files with 18 additions and 0 deletions
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src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
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@@ -249,6 +249,24 @@ class StableDiffusionControlNetPipeline(DiffusionPipeline, TextualInversionLoade
"""
self.vae.disable_slicing()
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.enable_vae_tiling
def enable_vae_tiling(self):
r"""
Enable tiled VAE decoding.
When this option is enabled, the VAE will split the input tensor into tiles to compute decoding and encoding in
several steps. This is useful to save a large amount of memory and to allow the processing of larger images.
"""
self.vae.enable_tiling()
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.disable_vae_tiling
def disable_vae_tiling(self):
r"""
Disable tiled VAE decoding. If `enable_vae_tiling` was previously invoked, this method will go back to
computing decoding in one step.
"""
self.vae.disable_tiling()
def enable_sequential_cpu_offload(self, gpu_id=0):
r"""
Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet,