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Functions2,541 in github.com/OpenDriveLab/ReSim

⨍ Functions 2,541◇ Types & classes 556↳ Endpoints 3
↓ 7 callersFunctiondefault
(val, d)
sat/vae_modules/utils.py:225
↓ 7 callersFunctionget_context_parallel_rank
()
sat/sgm/util.py:62
↓ 7 callersFunctionget_context_parallel_rank
()
sat/vae_modules/utils.py:55
↓ 7 callersFunctionget_context_parallel_world_size
()
sat/vae_modules/utils.py:49
↓ 7 callersMethodmax
(self)
SwissArmyTransformer/examples/yolos/util/misc.py:72
↓ 7 callersFunctionnonlinearity
(x)
sat/sgm/modules/diffusionmodules/model.py:44
↓ 7 callersMethodstate_dict
(self)
SwissArmyTransformer/examples/yolos/util/scheduler.py:60
↓ 7 callersFunctionunscaled_init_method
Init method based on N(0, sigma).
SwissArmyTransformer/sat/mpu/utils.py:84
↓ 6 callersMethodEncodeAsIds
(self, text, process_fn=None)
SwissArmyTransformer/sat/tokenization/cogview/unified_tokenizer.py:80
↓ 6 callersMethod__init__
( self, width, height, hidden_size, num_layers, time_embed_dim
sat/dit_video_concat.py:575
↓ 6 callersMethod__init__
( self, in_channels, with_conv, compress_time=False, )
sat/sgm/modules/cp_enc_dec.py:434
↓ 6 callersMethod__init__
( self, in_channels, with_conv, compress_time=False, )
sat/vae_modules/cp_enc_dec.py:532
↓ 6 callersMethod__init__
(self, **kwargs)
sat/vae_modules/autoencoder.py:503
↓ 6 callersMethod__setattr__
(self, __name, __value)
SwissArmyTransformer/sat/model/registry.py:37
↓ 6 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/eva2/transform_param.py:77
↓ 6 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/eva2clip/transform_param.py:64
↓ 6 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/yolos/transform_param.py:22
↓ 6 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/mae/transform_param.py:25
↓ 6 callersFunctioncopy_to_model_parallel_region
(input_)
SwissArmyTransformer/sat/mpu/mappings.py:131
↓ 6 callersMethoddecode
(self, z: torch.Tensor, **kwargs)
sat/sgm/models/autoencoder.py:217
↓ 6 callersFunctiondefault
(val, d)
sat/sgm/util.py:233
↓ 6 callersMethodencode
( self, x: torch.Tensor, return_reg_log: bool = False, unregularized: bool = F
sat/sgm/models/autoencoder.py:202
↓ 6 callersFunctionexists
(v)
sat/sgm/modules/autoencoding/regularizers/lookup_free_quantization.py:29
↓ 6 callersFunctionexists
(v)
sat/sgm/modules/autoencoding/losses/video_loss.py:25
↓ 6 callersFunctionget_context_parallel_group
()
sat/sgm/util.py:50
↓ 6 callersFunctionget_data_parallel_group
Get the data parallel group the caller rank belongs to.
SwissArmyTransformer/sat/mpu/initialize.py:116
↓ 6 callersFunctionget_model
Build the model.
SwissArmyTransformer/sat/model/base_model.py:396
↓ 6 callersFunctionget_model_parallel_src_rank
Calculate the global rank corresponding to a local rank zero in the model parallel group.
SwissArmyTransformer/sat/mpu/initialize.py:150
↓ 6 callersFunctionget_obj_from_str
(string, reload=False, invalidate_cache=True)
sat/sgm/util.py:264
↓ 6 callersFunctionis_odd
(n)
sat/sgm/modules/autoencoding/magvit2_pytorch.py:80
↓ 6 callersFunctionnonlinearity
(x)
sat/sgm/modules/autoencoding/vqvae/vqvae_blocks.py:29
↓ 6 callersFunctionpick_video_frame
(video, frame_indices)
sat/sgm/modules/autoencoding/magvit2_pytorch.py:106
↓ 6 callersMethodrotary
(self, t, **kwargs)
sat/dit_video_concat.py:326
↓ 6 callersFunctionsave_video_as_grid_and_mp4
(video_batch: torch.Tensor, save_path: str, fps: int = 5, args=None, key=None, ind=None, foldername=None)
sat/sample_video.py:61
↓ 6 callersFunctionset_random_seed
Set random seed for reproducability.
SwissArmyTransformer/sat/arguments.py:566
↓ 6 callersFunctiontrunc_normal_
r"""Fills the input Tensor with values drawn from a truncated normal distribution. The values are effectively drawn from the normal distributi
SwissArmyTransformer/examples/yolos/models/layers/weight_init.py:42
↓ 5 callersFunctionNormalize
(in_channels)
sat/sgm/modules/autoencoding/vqvae/vqvae_blocks.py:34
↓ 5 callersFunctionNormalize3D
(in_channels, zq_ch, add_conv)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d.py:87
↓ 5 callersFunctionNormalize3D
(in_channels, zq_ch, add_conv)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d_dev.py:95
↓ 5 callersMethodTokenToId
(self, token)
SwissArmyTransformer/sat/tokenization/hf_tokenizer.py:63
↓ 5 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
SwissArmyTransformer/examples/yolos/models/backbone.py:8
↓ 5 callersMethod__init__
(self, args, transformer=None, layernorm_epsilon=1e-6)
SwissArmyTransformer/sat/model/official/cait_model.py:175
↓ 5 callersMethod__init__
(self, args, layernorm_epsilon=1e-5)
SwissArmyTransformer/sat/model/official/clip_model.py:97
↓ 5 callersMethod__init__
(self, args, transformer=None, **kwargs)
SwissArmyTransformer/sat/model/official/dpr_model.py:81
↓ 5 callersMethod__init__
(self, s_churn=0.0, s_tmin=0.0, s_tmax=float("inf"), s_noise=1.0, *args, **kwargs)
sat/sgm/modules/diffusionmodules/sampling.py:86
↓ 5 callersMethod__init__
(self, num_tokens, codebook_dim, decay=0.99, eps=1e-5)
sat/sgm/modules/autoencoding/regularizers/quantize.py:298
↓ 5 callersMethod__init__
(self, in_channels, with_conv)
sat/sgm/modules/autoencoding/vqvae/movq_modules.py:79
↓ 5 callersMethod__init__
( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,
sat/sgm/modules/autoencoding/vqvae/vqvae_blocks.py:159
↓ 5 callersMethod__init__
( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,
sat/sgm/modules/autoencoding/vqvae/movq_enc_3d.py:296
↓ 5 callersMethod__init__
( self, *args, encoder_config: Dict, decoder_config: Dict, loss_config
sat/sgm/models/autoencoder.py:119
↓ 5 callersFunction_conv_split
(input_, dim, kernel_size)
sat/sgm/modules/cp_enc_dec.py:137
↓ 5 callersFunction_conv_split
(input_, dim, kernel_size)
sat/vae_modules/cp_enc_dec.py:135
↓ 5 callersMethod_get_text_tokenizer
(self, encode_special_tokens=False)
SwissArmyTransformer/sat/tokenization/icetk_glm_130B/ice_tokenizer.py:54
↓ 5 callersFunctionapply_rotary_pos_emb_index
(q, k, cos, sin, position_id)
SwissArmyTransformer/sat/model/position_embedding/rotary_embeddings.py:106
↓ 5 callersFunctionauto_create
(name, *, path=None, url=None)
SwissArmyTransformer/sat/resources/download.py:42
↓ 5 callersFunctioncast_tuple
(t, length=1)
sat/sgm/modules/autoencoding/magvit2_pytorch.py:89
↓ 5 callersFunctioncheckpoint
Evaluate a function without caching intermediate activations, allowing for reduced memory at the expense of extra compute in the backward pas
sat/sgm/modules/diffusionmodules/util.py:127
↓ 5 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/deit/transform_param.py:37
↓ 5 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/vit/transform_param.py:10
↓ 5 callersFunctioncopy_layer_param
in-place copy from src to dst src and dst should be the same layer type, e.g., both are LayerNorm or both are Linear. Or at least, bo
SwissArmyTransformer/examples/chatglm/transform_param.py:60
↓ 5 callersMethoddecode
(self, quantized: Tensor, cond: Optional[Tensor] = None, video_contains_first_frame=True)
sat/sgm/modules/autoencoding/magvit2_pytorch.py:1450
↓ 5 callersFunctiondefault
(val, d)
sat/vae_modules/attention.py:64
↓ 5 callersFunctionexists
(val)
sat/sgm/modules/attention.py:56
↓ 5 callersMethodfrom_pretrained
Instantiate a PreTrainedBertModel from a pre-trained model file. Download and cache the pre-trained model file if needed.
SwissArmyTransformer/sat/tokenization/glm/tokenization_gpt2.py:97
↓ 5 callersFunctionget_context_parallel_group_rank
()
sat/vae_modules/utils.py:63
↓ 5 callersFunctionget_context_parallel_world_size
()
sat/sgm/util.py:56
↓ 5 callersFunctioninstalled_cuda_version
(name="")
SwissArmyTransformer/sat/ops/ops_builder/builder.py:38
↓ 5 callersFunctioninstantiate_from_config
(config)
sat/vae_modules/utils.py:246
↓ 5 callersFunctionmake_attn
(in_channels, attn_type="vanilla", attn_kwargs=None)
sat/sgm/modules/diffusionmodules/model.py:233
↓ 5 callersFunctionmake_loaders
makes training/val/test Args: args.train_data, args.valid_data, args.test_data: str. Paths to the dataset. args.split: str. format
SwissArmyTransformer/sat/data_utils/configure_data.py:171
↓ 5 callersFunctionmerge_linear_lora
(lin)
SwissArmyTransformer/sat/model/finetune/lora2.py:159
↓ 5 callersFunctionnested_tensor_from_tensor_list
(tensor_list: List[Tensor])
SwissArmyTransformer/examples/yolos/util/misc.py:306
↓ 5 callersFunctionnonlinearity
(x)
sat/sgm/modules/cp_enc_dec.py:69
↓ 5 callersFunctionnonlinearity
(x)
sat/sgm/modules/autoencoding/vqvae/movq_modules.py:29
↓ 5 callersFunctionnonlinearity
(x)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d.py:43
↓ 5 callersFunctionnonlinearity
(x)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d_dev.py:48
↓ 5 callersFunctionnonlinearity
(x)
sat/vae_modules/cp_enc_dec.py:67
↓ 5 callersFunctionpartialclass
(cls, *args, **kwargs)
sat/sgm/util.py:184
↓ 5 callersFunctionreplace_linear_with_lora
(lin, partition, r, *args, **kw_args)
SwissArmyTransformer/sat/model/finetune/lora2.py:144
↓ 5 callersFunctionto_d
(x, sigma, denoised)
sat/sgm/modules/diffusionmodules/sampling_utils.py:146
↓ 5 callersFunctionto_neg_log_sigma
(sigma)
sat/sgm/modules/diffusionmodules/sampling_utils.py:150
↓ 5 callersFunctionupdate_args_with_file
(args, path)
SwissArmyTransformer/sat/arguments.py:472
↓ 4 callersMethodEncodeAsIds
encode text using text tokenizer and shift Id values for command tokens
SwissArmyTransformer/sat/tokenization/glm/tokenization.py:232
↓ 4 callersFunctionNormalize
(in_channels, zq_ch, add_conv)
sat/sgm/modules/autoencoding/vqvae/movq_modules.py:65
↓ 4 callersFunctionNormalize3D
(in_channels)
sat/sgm/modules/autoencoding/vqvae/movq_enc_3d.py:104
↓ 4 callersFunctionResidualUnit
(dim, kernel_size: Union[int, Tuple[int, int, int]], pad_mode: str = "constant")
sat/sgm/modules/autoencoding/magvit2_pytorch.py:843
↓ 4 callersMethod__init__
( self, in_channel=3, channel=128, n_res_block=2, n_res_channel=32,
SwissArmyTransformer/sat/tokenization/cogview/vqvae/vqvae_zc.py:220
↓ 4 callersMethod__init__
(self, hidden_size, output_dropout_prob, init_method, inner_hidden_size=None, output_layer_in
SwissArmyTransformer/sat/model/transformer.py:202
↓ 4 callersMethod__init__
(self, args, transformer=None, **kwargs)
SwissArmyTransformer/sat/model/official/eva2_model.py:126
↓ 4 callersMethod__init__
(self, args, **kwargs)
SwissArmyTransformer/sat/model/official/t5_model.py:194
↓ 4 callersMethod__init__
(self, args, transformer=None, layernorm_epsilon=1e-6)
SwissArmyTransformer/sat/model/official/mae_model.py:136
↓ 4 callersMethod__init__
(self, in_channels, out_channels, video_kernel_size=3, *args, **kwargs)
sat/sgm/modules/autoencoding/temporal_ae.py:85
↓ 4 callersMethod__init__
(self, in_channels, zq_ch=None, add_conv=False)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d.py:156
↓ 4 callersMethod__init__
(self, in_channels, zq_ch=None, add_conv=False)
sat/sgm/modules/autoencoding/vqvae/movq_dec_3d_dev.py:180
↓ 4 callersMethod__init__
(self)
sat/sgm/modules/encoders/modules.py:30
↓ 4 callersMethod__init__
(self, *, seq_len, patch_size, num_classes, dim, depth, heads, mlp_dim, channels = 3, dim_head = 64, dropout =
sat/sgm/modules/encoders/traj_encoder.py:95
↓ 4 callersMethod_backup_cpuinfo
(self)
SwissArmyTransformer/sat/ops/ops_builder/builder.py:350
↓ 4 callersFunction_conv_gather
(input_, dim, kernel_size)
sat/sgm/modules/cp_enc_dec.py:163
↓ 4 callersFunction_conv_gather
(input_, dim, kernel_size)
sat/vae_modules/cp_enc_dec.py:162
↓ 4 callersMethod_encode
(self, text)
SwissArmyTransformer/sat/tokenization/glm/tokenization.py:303
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