Functions — github.com/tdrussell/diffusion-pipe

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Functions1,157 in github.com/tdrussell/diffusion-pipe

⨍ Functions 1,157◇ Types & classes 222

Method__init__

(self, in_dim, out_dim, dropout=0.0)

models/wan/vae2_2.py:195

Method__init__

(self, dim)

models/wan/vae2_2.py:243

Method__init__

( self, in_channels, out_channels, factor_t, factor_s=1, )

models/wan/vae2_2.py:318

Method__init__

(self, in_dim, out_dim, dropout, mult,

models/wan/vae2_2.py:417

Method__init__

(self, in_dim, out_dim, dropout, mult,

models/wan/vae2_2.py:457

Method__init__

( self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4], num_res_blocks=2,

models/wan/vae2_2.py:502

Method__init__

( self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4], num_res_blocks=2,

models/wan/vae2_2.py:618

Method__init__

( self, dim=160, dec_dim=256, z_dim=16, dim_mult=[1, 2, 4, 4],

models/wan/vae2_2.py:736

Method__init__

( self, z_dim=48, c_dim=160, vae_pth=None, dim_mult=[1, 2, 4, 4],

models/wan/vae2_2.py:890

Method__init__

(self, *args, **kwargs)

models/wan/vae2_1.py:18

Method__init__

(self, dim, channel_first=True, images=True, bias=False)

models/wan/vae2_1.py:37

Method__init__

(self, dim, mode)

models/wan/vae2_1.py:64

Method__init__

(self, in_dim, out_dim, dropout=0.0)

models/wan/vae2_1.py:184

Method__init__

(self, dim)

models/wan/vae2_1.py:224

Method__init__

(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],

models/wan/vae2_1.py:263

Method__init__

(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],

models/wan/vae2_1.py:367

Method__init__

(self, z_dim=16, vae_pth='cache/vae_step_411000.pth', dtype

models/wan/vae2_1.py:617

Method__init__

(self, dim, num_heads, dropout=0.1, eps=1e-5)

models/wan/xlm_roberta.py:10

Method__init__

(self, dim, num_heads, post_norm, dropout=0.1, eps=1e-5)

models/wan/xlm_roberta.py:49

Method__init__

(self, dim, eps=1e-5)

models/wan/model.py:72

Method__init__

(self, dim, eps=1e-6, elementwise_affine=False)

models/wan/model.py:91

Method__init__

(self, dim, num_heads, window_size=(-1, -1),

models/wan/model.py:104

Method__init__

(self, dim, num_heads, window_size=(-1, -1),

models/wan/model.py:186

Method__init__

(self, cross_attn_type, dim, ffn_dim, num_

models/wan/model.py:239

Method__init__

(self, in_dim, out_dim, flf_pos_emb=False)

models/wan/model.py:348

Method__init__

r""" Initialize the diffusion model backbone. Args: model_type (`str`, *optional*, defaults to 't2v'): Mo

models/wan/model.py:379

Method__iter__

(self)

utils/dataset.py:1319

Method__iter__

(self)

utils/dataset.py:1430

utils/dataset.py:1323

Method__len__

(self)

utils/dataset.py:1427

Method__next__

(self)

utils/dataset.py:1326

Method__setitem__

(self, key, storage_ref)

utils/reduction.py:84

Method__str__

(self)

optimizers/optimizer_utils.py:268

Function_cache_fn

(datasets, queue, preprocess_media_file_fn, num_text_encoders, regenerate_cache, trust_cache, caching_batch_si

utils/dataset.py:1047

Function_count_all_layer_params

(self)

train.py:81

Function_exec_reduce_grads

(self)

train.py:703

Method_fn

( _x_B_T_H_W_D: torch.Tensor, _norm_layer: nn.Module, _scale_B_T_1_1_D: to

models/cosmos_predict2_modeling.py:924

Method_fn

(_x_B_T_H_W_D, _norm_layer, _scale_B_T_1_1_D, _shift_B_T_1_1_D)

models/cosmos_predict2_modeling.py:1081

Method_get_lr

(param_group, param_state)

optimizers/generic_optim.py:600

Function_move_adapter_to_device_of_base_layer

Move the adapter of the given name to the device of the base layer.

utils/patches.py:34

Method_partition_layers

(self, method='uniform')

utils/pipeline.py:16

Function_report_progress

(self, step)

train.py:694

Method_x_fn

( _x_B_T_H_W_D: torch.Tensor, layer_norm_cross_attn: Callable, _scale_cros

models/cosmos_predict2_modeling.py:1104

Function_zero_first

()

utils/dataset.py:1440

Functionadd_

(self, *args, **kwargs)

Methodapply_norm_and_rotary_pos_emb

( q: torch.Tensor, k: torch.Tensor, v: torch.Tensor, rope_emb: Optional[torch.Tensor] )

models/cosmos_predict2_modeling.py:428

Functionattention

Multi-modal attention function that processes image and text sequences.

models/hunyuan_image_modeling.py:20

Methodautodetect_error

()

models/wan/wan.py:118

Methodbackward

(ctx, *grads)

utils/unsloth_utils.py:45

Methodbackward_hook

(module, grad_input, grad_output)

utils/offloading.py:245

Functionbroadcast_model

(self)

utils/patches.py:163

Methodcache_latents

(self, map_fn, regenerate_cache=False, trust_cache=False, caching_batch_size=1)

utils/dataset.py:233

Methodcache_latents

(self, map_fn, regenerate_cache=False, trust_cache=False, caching_batch_size=1)

utils/dataset.py:415

Methodcache_latents

(self, map_fn, regenerate_cache=False, trust_cache=False, caching_batch_size=1)

utils/dataset.py:898

Methodcache_metadata

(self, regenerate_cache=False, trust_cache=False)

utils/dataset.py:532

Methodcache_text_embeddings

(self, map_fn, i, regenerate_cache=False, caching_batch_size=1)

utils/dataset.py:300

Methodcache_text_embeddings

(self, map_fn, i, regenerate_cache=False, caching_batch_size=1)

utils/dataset.py:440

Methodcache_text_embeddings

(self, map_fn, i, regenerate_cache=False, caching_batch_size=1)

utils/dataset.py:904

Methodcheck_grouped_metadata

()

utils/dataset.py:533

Functionconcat_hidden_states

(inputs)

models/auraflow.py:239

Functionconcatenate_hidden_states

(inputs)

models/hidream.py:442

Functionconcatenate_hidden_states

(inputs)

models/chroma.py:455

Functionconcatenate_hidden_states

(inputs)

models/hunyuan_video.py:638

Functionconcatenate_hidden_states

(inputs)

models/hunyuan_image.py:474

Methodconfigure_adapter

(self, target_model, adapter_config)

models/base.py:216

Methodconfigure_adapter

(self, adapter_config)

models/base.py:606

Methodconfigure_adapter

(self, adapter_config)

models/sdxl.py:430

Methodconfigure_adapter

(self, adapter_config)

models/krea2.py:34

Methodconfigure_adapter

(self, adapter_config)

models/flux.py:222

Functioncopy_args_to_cpu_if_needed

To support benchmarking in the presence of mutated args, we need to avoid autotuning contanminating them. We try to pass cloned args to the k

utils/patches.py:249

Methodcross_attn_ffn

(x, context, context_lens, e)

models/wan/model.py:305

models/wan/vae2_2.py:1038

Methoddecode

(self, zs)

models/wan/vae2_1.py:653

Methoddisable_deterministic

(self)

models/hunyuan_image_modeling.py:146

Methoddisable_deterministic

(self)

models/hunyuan_image_modeling.py:298

Functiondouble_stream_forward

(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, attn_mask=None, modulation_dims_img=None, modulation

utils/patches.py:297

Methodenable_block_swap

(self)

utils/offloading.py:219

Methodenable_block_swap

(self, blocks_to_swap)

models/base.py:727

Methodenable_deterministic

(self)

models/hunyuan_image_modeling.py:143

Methodenable_deterministic

(self)

models/hunyuan_image_modeling.py:295

Methodencode

(self, videos)

models/wan/vae2_2.py:1024

Methodencode

videos: A list of videos each with shape [C, T, H, W].

models/wan/vae2_1.py:643

Functionencode_token_weights

(self, token_weight_pairs)

models/base.py:394

Functionencode_token_weights

(self, token_weight_pairs)

models/ltx2.py:27

Functionflatten_captions

models/hidream.py:139

(captions: list[str], is_video: list[bool])

models/hunyuan_video_15.py:40

Methodfn

(image)

models/auraflow.py:88

Methodfn

(tensor)

models/lumina_2.py:105

(captions: list[str], is_video: list[bool])

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