↓ 5 callersMethodget_dummy_inputs(self, device, seed=0, height=64, width=64, num_images=1)
tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py:275
↓ 5 callersMethodget_sd_image(self, seed=0, shape=(4, 3, 512, 512), fp16=False)
tests/models/autoencoders/test_models_vae.py:862
↓ 5 callersFunctiononnx_export(
model,
model_args: tuple,
output_path: Path,
ordered_input_names,
output_names,
dyna
scripts/convert_stable_diffusion_controlnet_to_onnx.py:187
↓ 5 callersFunctiononnx_export(
model,
model_args: tuple,
output_path: Path,
ordered_input_names,
output_names,
dyna
scripts/convert_stable_diffusion_checkpoint_to_onnx.py:31
↓ 4 callersMethod__init__(
self,
channels,
num_res_blocks: int,
hidden_size,
hidden_dropout,
src/diffusers/models/unets/uvit_2d.py:308
↓ 4 callersMethod_combiner""" Combines a latent iamge img_vae of shape (B, C, H, W) and a CLIP-embedded image img_clip of shape (B, 1, clip_img_dim) into a sin
src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py:789
↓ 4 callersMethod_get_add_time_ids(
self, original_size, crops_coords_top_left, target_size, dtype, text_encoder_projection_dim=None
examples/community/pipeline_stable_diffusion_xl_ipex.py:633
↓ 4 callersMethodenable_sequential_cpu_offloadr""" Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet, text_encoder, vae and safety
src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_combined.py:181
↓ 4 callersMethodenable_sequential_cpu_offloadr""" Offloads all models (`unet`, `text_encoder`, `vae`, and `safety checker` state dicts) to CPU using 🤗 Accelerate, significantly re
src/diffusers/pipelines/kandinsky/pipeline_kandinsky_combined.py:195