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Functions393 in github.com/AgibotTech/EnerVerse-AC

⨍ Functions 393◇ Types & classes 84
↓ 1 callersMethodfreeze
(self)
lvdm/modules/encoders/condition.py:425
↓ 1 callersFunctiongen_batch_ray_parellel
(intrinsic,c2w,W,H)
lvdm/data/utils.py:7
↓ 1 callersFunctionget_action_h5
( action_path, n_chunk, chunk, n_previous, sep=1, domain_name="agibotworld" )
main/infer_all.py:71
↓ 1 callersFunctionget_action_h5
( action_path, n_chunk, chunk, n_previous, sep=1, domain_name="agibotworld" )
main/generate_video_acwm.py:68
↓ 1 callersFunctionget_action_npy
( action_path, n_chunk, chunk, n_previous, sep=1, domain_name="agibotworld" )
main/infer_all.py:40
↓ 1 callersFunctionget_action_npy
( action_path, n_chunk, chunk, n_previous, sep=1, domain_name="agibotworld" )
main/generate_video_acwm.py:41
↓ 1 callersFunctionget_caminfo_json
(extrinsic_path, intrinsic_path, n)
main/infer_all.py:101
↓ 1 callersFunctionget_caminfo_json
(extrinsic_path, intrinsic_path, n)
main/generate_video_acwm.py:92
↓ 1 callersFunctionget_caminfo_npy
(extrinsic_path, intrinsic_path, n)
main/infer_all.py:92
↓ 1 callersFunctionget_caminfo_npy
(extrinsic_path, intrinsic_path, n)
main/generate_video_acwm.py:84
↓ 1 callersFunctionget_image
(img_path, n)
main/infer_all.py:31
↓ 1 callersFunctionget_image
(img_path, n)
main/generate_video_acwm.py:32
↓ 1 callersFunctionget_obj_from_str
(string, reload=False)
utils/general_utils.py:195
↓ 1 callersFunctionget_obj_from_str
(string, reload=False)
lvdm/utils.py:37
↓ 1 callersFunctionget_timestep_embedding
This matches the implementation in Denoising Diffusion Probabilistic Models: From Fairseq. Build sinusoidal embeddings. This matches
lvdm/modules/networks/ae_modules.py:129
↓ 1 callersMethodget_traj
this function takes camera info. and eef. poses as inputs, and outputs the trajectory maps. output traj map shape: (c, v, t, h, w)
lvdm/models/ddpm3d.py:1838
↓ 1 callersMethodinit_cache
(self,denoise_step=50,chunk=1)
lvdm/modules/networks/openaimodel3dcausal.py:233
↓ 1 callersMethodinit_from_ckpt
(self, path, ignore_keys=list())
lvdm/models/autoencoder.py:80
↓ 1 callersMethodinit_test
(self,)
lvdm/models/autoencoder.py:51
↓ 1 callersMethodinstantiate_cond_stage
(self, config)
lvdm/models/ddpm3d.py:626
↓ 1 callersMethodinstantiate_first_stage
(self, config)
lvdm/models/ddpm3d.py:619
↓ 1 callersMethodinstantiate_pretrained
(self, config)
lvdm/modules/networks/ae_modules.py:817
↓ 1 callersFunctionintrinsic_transform_batch
(intrinsic, original_res, size, transform_mode)
lvdm/data/utils.py:67
↓ 1 callersFunctionload_config
(args)
main/infer_all.py:24
↓ 1 callersFunctionload_config
(args)
main/generate_video_acwm.py:25
↓ 1 callersFunctionload_model
(config)
main/infer_all.py:19
↓ 1 callersFunctionload_model
(config)
main/generate_video_acwm.py:19
↓ 1 callersFunctionlogit_normal_sampler
(m, s=1, beta_m=100, sample_num=1000000)
lvdm/models/ddpm3d.py:57
↓ 1 callersFunctionmain
(args, model=None)
main/infer_all.py:122
↓ 1 callersFunctionmain
(args)
main/generate_video_acwm.py:113
↓ 1 callersFunctionmake_beta_schedule
(schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3)
lvdm/models/utils_diffusion.py:31
↓ 1 callersMethodmake_cond_schedule
(self, )
lvdm/models/ddpm3d.py:587
↓ 1 callersFunctionmake_ddim_sampling_parameters
(alphacums, ddim_timesteps, eta, verbose=True)
lvdm/models/utils_diffusion.py:79
↓ 1 callersFunctionmake_ddim_timesteps
(ddim_discr_method, num_ddim_timesteps, num_ddpm_timesteps, verbose=True)
lvdm/models/utils_diffusion.py:56
↓ 1 callersMethodmake_schedule
(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True, ddpm_from=1000,)
lvdm/models/samplers/ddim.py:31
↓ 1 callersFunctionmu_t
(t,a=5, mu_max=4)
lvdm/models/ddpm3d.py:64
↓ 1 callersMethodp_losses
(self, x_start, t, noise=None)
lvdm/models/ddpm3d.py:377
↓ 1 callersMethodp_losses
(self, x_start, cond, t, noise=None, **kwargs)
lvdm/models/ddpm3d.py:800
↓ 1 callersMethodp_losses
(self, x_start, cond, t, noise=None, traj_aug_mask=None, **kwargs)
lvdm/models/ddpm3d.py:1359
↓ 1 callersMethodp_mean_variance
(self, x, t, clip_denoised: bool)
lvdm/models/ddpm3d.py:296
↓ 1 callersMethodp_mean_variance
(self, x, c, t, clip_denoised: bool, return_x0=False, score_corrector=None, corrector_kwargs=None, **kwargs)
lvdm/models/ddpm3d.py:936
↓ 1 callersMethodp_sample
(self, x, t, clip_denoised=True, repeat_noise=False)
lvdm/models/ddpm3d.py:309
↓ 1 callersMethodp_sample
(self, x, c, t, clip_denoised=False, repeat_noise=False, return_x0=False, \ temperature=1., n
lvdm/models/ddpm3d.py:962
↓ 1 callersMethodp_sample_loop
(self, shape, return_intermediates=False)
lvdm/models/ddpm3d.py:318
↓ 1 callersMethodp_sample_loop
(self, cond, shape, return_intermediates=False, x_T=None, verbose=True, callback=None, \
lvdm/models/ddpm3d.py:984
↓ 1 callersMethodpredict_eps_from_z_and_v
(self, x_t, t, v)
lvdm/models/ddpm3d.py:281
↓ 1 callersMethodpredict_start_from_z_and_v
(self, x_t, t, v)
lvdm/models/ddpm3d.py:276
↓ 1 callersMethodpreprocess
(self, x)
lvdm/modules/encoders/condition.py:156
↓ 1 callersMethodpreprocess
(self, x)
lvdm/modules/encoders/condition.py:271
↓ 1 callersMethodpreprocess
(self, x)
lvdm/modules/encoders/condition.py:329
↓ 1 callersMethodquantize
(self, x, *args, **kwargs)
lvdm/models/autoencoder.py:213
↓ 1 callersFunctionrescale_noise_cfg
Rescale `noise_cfg` according to `guidance_rescale`. Based on findings of [Common Diffusion Noise Schedules and Sample Steps are Flawed](http
lvdm/models/utils_diffusion.py:147
↓ 1 callersFunctionrescale_zero_terminal_snr
Rescales betas to have zero terminal SNR Based on https://arxiv.org/pdf/2305.08891.pdf (Algorithm 1) Args: betas (`numpy.ndarray`):
lvdm/models/utils_diffusion.py:112
↓ 1 callersMethodrestore
Restore the parameters stored with the `store` method. Useful to validate the model with EMA parameters without affecting the
lvdm/ema.py:64
↓ 1 callersMethodsample
(self, cond, batch_size=16, return_intermediates=False, x_T=None, \ verbose=True, timesteps=Non
lvdm/models/ddpm3d.py:1031
↓ 1 callersMethodsample_log
(self, cond, batch_size, ddim, ddim_steps, causal=False, chunk=4,**kwargs)
lvdm/models/ddpm3d.py:1048
↓ 1 callersMethodshared_step
(self, batch, random_uncond, **kwargs)
lvdm/models/ddpm3d.py:776
↓ 1 callersMethodstore
Save the current parameters for restoring later. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be
lvdm/ema.py:55
↓ 1 callersMethodteacher_forcing_aug
lvdm/models/ddpm3d.py:1314
↓ 1 callersMethodtext_transformer_forward
(self, x: torch.Tensor, attn_mask=None)
lvdm/modules/encoders/condition.py:229
Method__init__
(self, model, decay=0.9999, use_num_upates=True)
lvdm/ema.py:6
Method__init__
(self, c_concat_config, c_crossattn_config)
lvdm/basics.py:92
Method__init__
(self, value)
lvdm/distributions.py:14
Method__init__
(self, parameters, deterministic=False)
lvdm/distributions.py:25
Method__init__
(self, num_units, max_relative_position)
lvdm/modules/attention.py:27
Method__init__
(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0., relative_position=Fals
lvdm/modules/attention.py:65
Method__init__
(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True, dis
lvdm/modules/attention.py:422
Method__init__
(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True, dis
lvdm/modules/attention.py:475
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:522
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:646
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:773
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:864
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:978
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None, use_checkpoint=Tr
lvdm/modules/attention.py:1104
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)
lvdm/modules/attention.py:1223
Method__init__
(self, dim, heads=4, dim_head=32)
lvdm/modules/attention.py:1243
Method__init__
(self, in_channels)
lvdm/modules/attention.py:1262
Method__init__
(self, channels, use_conv, dims=2, out_channels=None, padding=1)
lvdm/modules/networks/openaimodel3dcausal.py:91
Method__init__
( self, channels, emb_channels, dropout, out_channels=None, us
lvdm/modules/networks/openaimodel3dcausal.py:157
Method__init__
( self, in_channels: int, out_channels: int, kernel_size: int | Tuple[int, int
lvdm/modules/networks/openaimodel3dcausal.py:319
Method__init__
(self, in_channels, out_channels=None, dropout=0.0, spatial_aware=False, all_zero_init=False)
lvdm/modules/networks/openaimodel3dcausal.py:388
Method__init__
(self, in_channels, out_channels=None, dropout=0.0, spatial_aware=False, all_zero_init=False)
lvdm/modules/networks/openaimodel3dcausal.py:442
Method__init__
(self, in_channels, out_channels=None, dropout=0.0, spatial_aware=False, all_zero_init=False)
lvdm/modules/networks/openaimodel3dcausal.py:496
Method__init__
(self, in_channels, model_channels, out_channels,
lvdm/modules/networks/openaimodel3dcausal.py:575
Method__init__
(self, in_channels)
lvdm/modules/networks/ae_modules.py:22
Method__init__
(self, in_channels)
lvdm/modules/networks/ae_modules.py:27
Method__init__
(self, in_channels, with_conv)
lvdm/modules/networks/ae_modules.py:91
Method__init__
(self, in_channels, with_conv)
lvdm/modules/networks/ae_modules.py:112
Method__init__
(self, *, in_channels, out_channels=None, conv_shortcut=False, dropout, temb_channels=512)
lvdm/modules/networks/ae_modules.py:152
Method__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
lvdm/modules/networks/ae_modules.py:365
Method__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
lvdm/modules/networks/ae_modules.py:467
Method__init__
(self, in_channels, out_channels, *args, **kwargs)
lvdm/modules/networks/ae_modules.py:582
Method__init__
(self, in_channels, out_channels, ch, num_res_blocks, resolution, ch_mult=(2,2), dropout=0.0)
lvdm/modules/networks/ae_modules.py:618
Method__init__
(self, factor, in_channels, mid_channels, out_channels, depth=2)
lvdm/modules/networks/ae_modules.py:666
Method__init__
(self, in_channels, ch, resolution, out_ch, num_res_blocks, attn_resolutions, dropout=0.0, re
lvdm/modules/networks/ae_modules.py:703
Method__init__
(self, z_channels, out_ch, resolution, num_res_blocks, attn_resolutions, ch, ch_mult=(1,2,4,8),
lvdm/modules/networks/ae_modules.py:722
Method__init__
(self, in_size, out_size, in_channels, out_channels, ch_mult=2)
lvdm/modules/networks/ae_modules.py:739
Method__init__
(self, in_channels=None, learned=False, mode="bilinear")
lvdm/modules/networks/ae_modules.py:758
Method__init__
(self, ch_mult:list, in_channels, pretrained_model:nn.Module=None, reshape=F
lvdm/modules/networks/ae_modules.py:782
Method__init__
(self, channels, use_conv, dims=2, out_channels=None, padding=1)
lvdm/modules/encoders/adapter.py:15
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