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

⨍ Functions 1,157◇ Types & classes 222
↓ 2 callersMethod__init__
(self, model)
models/qwen_image.py:583
↓ 2 callersMethod__init__
(self, vocab_size=250002, max_seq_len=514, type_size=1,
models/wan/xlm_roberta.py:79
↓ 2 callersFunction_apply_rotary_pos_emb_base
Base implementation of applying rotary positional embedding tensor to the input tensor. Parameters ---------- t: torch.Tensor
models/cosmos_predict2_modeling.py:51
↓ 2 callersFunction_cache_text_embeddings
(metadata_dataset, map_fn, i, cache_dir, regenerate_cache, caching_batch_size)
utils/dataset.py:177
↓ 2 callersFunction_compute_text_embeddings
(text_encoder, input_ids, attn_mask, is_generic_llm=False)
models/cosmos_predict2.py:165
↓ 2 callersMethod_get_input_ids
(self, prompt, tokenizer)
models/sdxl.py:579
↓ 2 callersMethod_get_lr
(param_group, param_state)
optimizers/automagic.py:125
↓ 2 callersMethod_rms
(tensor)
optimizers/automagic.py:142
↓ 2 callersMethod_set_param_original_name
(self)
models/sdxl.py:414
↓ 2 callersMethod_submit_move_blocks
(self, block_idx_to_cpu, block_idx_to_cuda)
utils/offloading.py:146
↓ 2 callersMethod_wait_blocks_move
(self, block_idx)
utils/offloading.py:167
↓ 2 callersFunctionapply_rotary_pos_emb
Apply rotary positional embedding tensor to the input tensor. Support matrix: Fused/Unfused: Training: qkv_formats:
models/cosmos_predict2_modeling.py:120
↓ 2 callersFunctionapply_rotary_pos_emb
(x, cos, sin, unsqueeze_dim=1)
models/llm_adapter.py:43
↓ 2 callersFunctionattention
( q, k, v, q_lens=None, k_lens=None, dropout_p=0., softmax_scale=None, q_scale
models/wan/attention.py:128
↓ 2 callersMethodcache_metadata
(self, regenerate_cache=False, trust_cache=False)
utils/dataset.py:1034
↓ 2 callersFunctioncall_model
(inputs)
tools/test_ideogram4.py:62
↓ 2 callersMethodclear
Deletes all cache files from disk. Calls init() again.
utils/cache.py:81
↓ 2 callersFunctionclosest_smaller_divisor_of_n_to_k
Helper function for subset-norm subset-size computation. Get the closest smaller divisor of n to k.
optimizers/generic_optim.py:134
↓ 2 callersMethodconfigure_adapter
(self, adapter_config)
models/base.py:307
↓ 2 callersMethodconnector_forward
(self, connector, hidden_states, attention_mask)
models/ltx2.py:421
↓ 2 callersFunctionconvert_state_dict_dtype
(state_dict, dtype)
utils/saver.py:14
↓ 2 callersFunctioncopy_stochastic
Performs stochastic rounding from source tensor to target tensor. Args: target: Destination tensor (determines the target format)
optimizers/optimizer_utils.py:142
↓ 2 callersFunctioncount_conv3d
(model)
models/wan/vae2_2.py:726
↓ 2 callersFunctioncount_conv3d
(model)
models/wan/vae2_1.py:471
↓ 2 callersFunctiondataset_config_validation
(config)
models/cosmos.py:123
↓ 2 callersMethoddecode
(self, z, scale)
models/wan/vae2_1.py:540
↓ 2 callersFunctiondedup_and_sort
(values)
utils/dataset.py:73
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/hidream.py:275
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/chroma.py:288
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/hunyuan_video.py:492
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/hunyuan_image.py:334
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/flux2.py:184
↓ 2 callersMethodenable_block_swap
(self, blocks_to_swap)
models/flux.py:404
↓ 2 callersFunctionevaluate
(model, model_engine, eval_dataloaders, tb_writer, step, eval_gradient_accumulation_steps, disable_block_swap)
train.py:230
↓ 2 callersMethodforward
(self, x)
models/wan/clip.py:100
↓ 2 callersMethodforward
(self, x: torch.Tensor, first_chunk=False)
models/wan/vae2_2.py:390
↓ 2 callersMethodforward
(self, x)
models/wan/vae2_1.py:506
↓ 2 callersFunctionget_data_iterator_for_step
(dataloader, engine, num_micro_batches=None)
train.py:167
↓ 2 callersMethodget_denominator
(self, group, state, grad, state_device)
optimizers/generic_optim.py:534
↓ 2 callersMethodget_loss_fn
(self)
models/base.py:364
↓ 2 callersMethodget_prompt_embeds
(self, input_ids, tokenizer, text_encoder, return_pooled_prompt_embeds=False)
models/sdxl.py:743
↓ 2 callersFunctionget_rank
()
utils/common.py:29
↓ 2 callersMethodget_size_bucket_datasets
(self)
utils/dataset.py:412
↓ 2 callersFunctionget_subsample_idx_and_random_signs_from_matrix
(input_mat, rank, manual_seed)
optimizers/projectors/approx_svd.py:135
↓ 2 callersFunctionget_text_embeddings
(prompt)
tools/test_ideogram4.py:38
↓ 2 callersMethodload_adapter_weights
(self, adapter_path)
models/base.py:313
↓ 2 callersFunctionmaybe_copy
(name, arg)
utils/patches.py:263
↓ 2 callersFunctionneed_to_checkpoint
(config, epoch=None)
utils/saver.py:20
↓ 2 callersFunctionone_at_a_time
()
utils/common.py:47
↓ 2 callersMethodprepare_embedded_sequence
Prepares an embedded sequence tensor by applying positional embeddings and handling padding masks. Args: x_B_C_T_H_W (to
models/cosmos_predict2_modeling.py:1361
↓ 2 callersMethodproject_back
(self, low_rank_grad)
optimizers/projectors/svd_projector.py:132
↓ 2 callersFunctionrope_apply
(x, grid_sizes, freqs)
models/wan/model.py:40
↓ 2 callersFunctionseed_from_hash
(item)
utils/dataset.py:80
↓ 2 callersMethodstate_dict
(self)
train.py:72
↓ 2 callersMethodsync_epoch
(self)
utils/dataset.py:1393
↓ 2 callersMethodto_layers
(self)
models/sd3.py:161
↓ 2 callersFunctiontop_k_norm_indices
(tensor: torch.Tensor, dim: int, k: int)
optimizers/projectors/topk_norm_projector.py:6
↓ 2 callersFunctionvae_decode
(tensor, vae)
tools/wan_vae_test.py:29
↓ 2 callersFunctionvae_encode
(tensor, vae)
tools/wan_vae_test.py:25
↓ 2 callersFunctionvae_encode
(tensor, vae)
models/wan/wan.py:55
↓ 2 callersFunctionweights_to_device
(layer: nn.Module, device: torch.device)
utils/offloading.py:114
↓ 2 callersFunctionwhitespace_clean
(text)
models/wan/tokenizers.py:16
↓ 2 callersFunctionwrite_image
(decoded, name)
tools/wan_vae_test.py:33
↓ 1 callersMethod__init__
(self, block_type: str, blocks: list[nn.Module], num_blocks: int, blocks_to_swap: int, device: torch.device, d
utils/offloading.py:127
↓ 1 callersMethod__init__
(self, dataset_config, model, skip_dataset_validation=False)
utils/dataset.py:926
↓ 1 callersMethod__init__
(self, *args, **kwargs)
models/base.py:295
↓ 1 callersMethod__init__
( self, hidden_size: int, heads_num: int, mlp_width_ratio: float, mlp_
models/hunyuan_image_modeling.py:66
↓ 1 callersMethod_after_fork
(self)
utils/reduction.py:77
↓ 1 callersMethod_approx_sq_grad
(exp_avg_sq_row, exp_avg_sq_col)
optimizers/automagic.py:146
↓ 1 callersMethod_broadcast_target
(self, target)
utils/dataset.py:1370
↓ 1 callersMethod_byt5_embeddings
(self, text_list, device)
models/hunyuan_image.py:204
↓ 1 callersMethod_clean
(self, text)
models/wan/tokenizers.py:73
↓ 1 callersFunction_clip
(pretrained=False, pretrained_name=None, model_cls=XLMRobertaCLIP, return_transf
models/wan/clip.py:428
↓ 1 callersMethod_collate
(self, examples)
utils/dataset.py:1003
↓ 1 callersFunction_collect_rng_states
Collect the global random state of :mod:`torch`, :mod:`torch.cuda`, :mod:`numpy` and Python.
utils/isolate_rng.py:29
↓ 1 callersFunction_convert_state_dict_keys
(model_state_dict, loaded_state_dict)
models/hunyuan_video.py:161
↓ 1 callersFunction_evaluate
(model_engine, eval_dataloaders, tb_writer, step, eval_gradient_accumulation_steps)
train.py:196
↓ 1 callersMethod_find_closest_ar_bucket
(self, log_ar, frames, is_video)
utils/dataset.py:837
↓ 1 callersMethod_find_closest_size_bucket
(self, log_ar, frames, is_video)
utils/dataset.py:853
↓ 1 callersFunction_get_automagic_lrs
(optimizer)
train.py:265
↓ 1 callersMethod_get_group_lr
(self, group)
optimizers/automagic.py:132
↓ 1 callersMethod_get_mods
(self, mod_vectors)
models/chroma.py:433
↓ 1 callersMethod_get_mods
(self, mod_vectors)
models/chroma.py:482
↓ 1 callersMethod_get_qwen2_prompt_embeds
( self, prompt, device=None, max_sequence_length=256, )
models/omnigen2.py:82
↓ 1 callersMethod_get_qwen_prompt_embeds
( self, prompt, control_files, device=None, dtype=None, )
models/qwen_image.py:328
↓ 1 callersMethod_get_ungrouped_metadata
(self, regenerate_cache=False, trust_cache=False)
utils/dataset.py:620
↓ 1 callersMethod_group_metadata_and_save_to_disk
(self, regenerate_cache=False, trust_cache=False)
utils/dataset.py:588
↓ 1 callersMethod_handle_task
(self, task)
utils/dataset.py:1217
↓ 1 callersMethod_load_diffusion_model
(self)
models/ltx2.py:242
↓ 1 callersMethod_load_from_state_dict
Loads the tensor state from a state dictionary.
optimizers/optimizer_utils.py:262
↓ 1 callersMethod_make_divisible_by
(self, n)
utils/dataset.py:391
↓ 1 callersMethod_metadata_map_fn
(self)
utils/dataset.py:737
↓ 1 callersMethod_norm
(self, x: torch.Tensor)
models/cosmos_predict2_modeling.py:235
↓ 1 callersMethod_norm
(self, x)
models/wan/model.py:85
↓ 1 callersMethod_process_user_provided_ars
(self, ars)
utils/dataset.py:872
↓ 1 callersMethod_process_user_provided_resolutions
(self, resolutions)
utils/dataset.py:881
↓ 1 callersMethod_qwenvl_embeddings
(self, text, device)
models/hunyuan_image.py:180
↓ 1 callersMethod_relative_position_bucket
(self, rel_pos)
models/wan/t5.py:239
↓ 1 callersFunction_rotate_half
Change sign so the last dimension becomes [-odd, +even] Args: x: torch.Tensor. Input tensor. interleaved: bool. Whether to use in
models/cosmos_predict2_modeling.py:30
↓ 1 callersMethod_set_defaults
(self, directory_config, dataset_config)
utils/dataset.py:730
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