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github.com/VAST-AI-Research/MIDI-3D
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Functions
380 in github.com/VAST-AI-Research/MIDI-3D
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Functions
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1
Method
__init__
( self, num_attention_heads: int = 16, width: int = 2048, in_channels: int = 6
midi/models/transformers/triposg_transformer.py:405
Method
__init__
( self, parameters: torch.Tensor, deterministic: bool = False, feature_dim: in
midi/models/autoencoders/vae.py:9
Method
__init__
( self, in_channels: int = 3, out_channels: int = 1, dim: int = 512, n
midi/models/autoencoders/autoencoder_kl_triposg.py:92
Method
__init__
( self, in_channels: int = 3, # NOTE xyz instead of feature dim latent_channels: int
midi/models/autoencoders/autoencoder_kl_triposg.py:217
Method
__len__
(self)
midi/schedulers/scheduling_rectified_flow.py:326
Method
__new__
(cls)
midi/utils/misc.py:244
Function
_buildq3d_gpu
Builds the filterq matrix for the given variables on GPU, using chunking to reduce memory usage.
midi/utils/smoothing.py:124
Method
_init_custom_adapter
( self, # Attention processor set_self_attn_module_names: Optional[List[str]] = None,
midi/pipelines/pipeline_midi.py:482
Method
_load_custom_adapter
(self, state_dict)
midi/pipelines/pipeline_midi.py:569
Method
_save_custom_adapter
( self, include_keys: Optional[List[str]] = None, exclude_keys: Optional[List[str]] =
midi/pipelines/pipeline_midi.py:590
Method
_set_gradient_checkpointing
(self, module, value=False)
midi/models/transformers/triposg_transformer.py:464
Method
_sigma_to_t
(self, sigma)
midi/schedulers/scheduling_rectified_flow.py:154
Function
apply_texture
(scene_path: str, rgb_image: Any, seg_image: Any, seed: int)
gradio_demo.py:225
Method
attention_kwargs
(self)
midi/pipelines/pipeline_midi.py:140
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
midi/models/transformers/triposg_transformer.py:544
Method
attn_processors
r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with
midi/models/autoencoders/autoencoder_kl_triposg.py:310
Method
backward
(ctx, g)
midi/utils/ops.py:51
Method
backward
(ctx, graddist1, graddist2)
midi/utils/chamfer_distance/chamfer_distance.py:44
Function
barrier
()
midi/utils/misc.py:214
Method
begin_index
The index for the first timestep. It should be set from pipeline with `set_begin_index` method.
midi/schedulers/scheduling_rectified_flow.py:137
Function
binary_cross_entropy
F.binary_cross_entropy is not numerically stable in mixed-precision training.
midi/utils/ops.py:316
Method
blend_rgba
(image)
midi/utils/saving.py:198
Function
broadcast
(tensor, src=0)
midi/utils/misc.py:221
Function
c2w_to_polar
(c2w: Float[Tensor, "4 4"])
midi/utils/ops.py:396
Function
calc_num_train_steps
(num_data, batch_size, max_epochs, num_nodes, num_cards=8)
midi/utils/config.py:26
Function
chamfer_distance_backward
midi/utils/chamfer_distance/chamfer_distance.cpp:114
Function
chamfer_distance_backward_cuda
midi/utils/chamfer_distance/chamfer_distance.cpp:41
Function
chamfer_distance_forward
midi/utils/chamfer_distance/chamfer_distance.cpp:90
Function
chamfer_distance_forward_cuda
midi/utils/chamfer_distance/chamfer_distance.cpp:27
Method
check_train
(self, batch, **kwargs)
midi/systems/base.py:141
Function
chunk_batch
(func: Callable, chunk_size: int, *args, **kwargs)
midi/utils/ops.py:96
Method
collate
(self, batch)
midi/data/multi_object.py:613
Function
compute_density_for_timestep_sampling
( weighting_scheme: str, batch_size: int, logit_mean: float = 0.0, logit_std: float = 1.0,
midi/schedulers/scheduling_rectified_flow.py:20
Function
compute_loss_weighting
Computes loss weighting scheme for SD3 training. Courtesy: This was contributed by Rafie Walker in https://github.com/huggingface/diffusers/
midi/schedulers/scheduling_rectified_flow.py:47
Method
configure
(self)
midi/systems/system_midi.py:74
Method
configure_optimizers
(self)
midi/systems/base.py:117
Method
create_custom_forward
(module)
midi/models/transformers/triposg_transformer.py:675
Method
custom_forward
(*inputs)
midi/models/transformers/triposg_transformer.py:676
Function
decimate_quadric_edge_collapse
( ms, targetfacenum=None, preservenormal=True, verbose=False )
midi/utils/mesh_process.py:50
Function
decimate_quadric_edge_collapse_with_texture
( ms, targetfacenum=None, preservenormal=True, verbose=False )
midi/utils/mesh_process.py:30
Method
decode_progressive
(self)
midi/pipelines/pipeline_midi.py:148
Function
default_set_attn_proc_func
( name: str, hidden_size: int, cross_attention_dim: Optional[int], ori_attn_proc: object, )
midi/models/transformers/__init__.py:6
Function
disable_flash3
()
midi/utils/constants.py:12
Method
disable_forward_chunking
(self)
midi/models/transformers/triposg_transformer.py:758
Method
disable_vae_slicing
r""" Disable sliced VAE decoding. If `enable_vae_slicing` was previously enabled, this method will go back to computing decoding in on
midi/pipelines/pipeline_utils.py:18
Method
disable_vae_tiling
r""" Disable tiled VAE decoding. If `enable_vae_tiling` was previously enabled, this method will go back to computing decoding in one
midi/pipelines/pipeline_utils.py:33
Method
do_classifier_free_guidance
(self)
midi/pipelines/pipeline_midi.py:132
Method
enable_forward_chunking
Sets the attention processor to use [feed forward chunking](https://huggingface.co/blog/reformer#2-chunked-feed-forward-layers).
midi/models/transformers/triposg_transformer.py:724
Function
enable_gradient
(model, enabled: bool = True)
midi/utils/misc.py:229
Method
enable_vae_tiling
r""" Enable tiled VAE decoding. When this option is enabled, the VAE will split the input tensor into tiles to compute decoding and en
midi/pipelines/pipeline_utils.py:25
Method
encode
Encode a batch of point features into latents.
midi/models/autoencoders/autoencoder_kl_triposg.py:453
Method
end
(self, name: str, accumulate: bool = False)
midi/utils/misc.py:259
Method
file_handle
(self)
midi/utils/callbacks.py:130
Method
filter
(self, record)
launch.py:35
Function
finish_with_cleanup
(func: Callable)
midi/utils/misc.py:201
Method
fn_recursive_add_processors
( name: str, module: torch.nn.Module, processors: Dict[str, AttentionProce
midi/models/transformers/triposg_transformer.py:553
Method
fn_recursive_add_processors
( name: str, module: torch.nn.Module, processors: Dict[str, AttentionProce
midi/models/autoencoders/autoencoder_kl_triposg.py:319
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
midi/models/transformers/triposg_transformer.py:595
Method
fn_recursive_attn_processor
(name: str, module: torch.nn.Module, processor)
midi/models/autoencoders/autoencoder_kl_triposg.py:361
Method
fn_recursive_feed_forward
( module: torch.nn.Module, chunk_size: int, dim: int )
midi/models/transformers/triposg_transformer.py:745
Method
forward
(ctx, x)
midi/utils/ops.py:45
Method
forward
(ctx, xyz1, xyz2)
midi/utils/chamfer_distance/chamfer_distance.py:19
Method
forward
Forward process. Args: x: tensor of shape [..., dim] Returns: embedding: an embedding of `x` of shape [...,
midi/models/embeddings.py:76
Method
forward
( self, hidden_states: torch.Tensor, encoder_hidden_states: Optional[torch.Tensor] = N
midi/models/transformers/triposg_transformer.py:283
Method
forward
The [`HunyuanDiT2DModel`] forward method. Args: hidden_states (`torch.Tensor` of shape `(batch size, dim, height, width)`):
midi/models/transformers/triposg_transformer.py:614
Method
forward
(self, sample_1: torch.Tensor, sample_2: torch.Tensor)
midi/models/autoencoders/autoencoder_kl_triposg.py:74
Method
forward
( self, sample: torch.Tensor, queries: torch.Tensor, kv_cache: Optional[torch.
midi/models/autoencoders/autoencoder_kl_triposg.py:189
Method
forward
(self, x: torch.Tensor)
midi/models/autoencoders/autoencoder_kl_triposg.py:528
Function
fourier_position_encoding
(x, n_freq: int, dim: int)
midi/utils/ops.py:439
Method
fuse_qkv_projections
Enables fused QKV projections. For self-attention modules, all projection matrices (i.e., query, key, value) are fused. For cross-att
midi/pipelines/pipeline_utils.py:40
Method
fuse_qkv_projections
Enables fused QKV projections. For self-attention modules, all projection matrices (i.e., query, key, value) are fused. For cross-att
midi/models/transformers/triposg_transformer.py:501
Method
fuse_qkv_projections
Enables fused QKV projections. For self-attention modules, all projection matrices (i.e., query, key, value) are fused. For cross-att
midi/models/autoencoders/autoencoder_kl_triposg.py:267
Method
get_accumulation
(self, name: str, average: bool = False)
midi/utils/misc.py:270
Function
get_activation
(name)
midi/utils/ops.py:59
Function
get_config_from_file
( config_file: str, cli_args: list = [], **kwargs )
midi/utils/misc.py:40
Function
get_intrinsic_from_fov
(fov, H, W, bs=-1)
midi/utils/ops.py:302
Method
get_metrics
(self, *args, **kwargs)
midi/utils/callbacks.py:116
Function
get_mvp_matrix
( c2w: Float[Tensor, "*B 4 4"], proj_mtx: Float[Tensor, "*B 4 4"] )
midi/utils/ops.py:281
Function
get_obj_from_config
(config)
midi/utils/misc.py:78
Function
get_plucker_rays
( rays_o: Float[Tensor, "*N 3"], rays_d: Float[Tensor, "*N 3"] )
midi/utils/ops.py:388
Function
get_projection_matrix
( fovy: Union[float, Float[Tensor, "B"]], aspect_wh: float, near: float, far: float )
midi/utils/ops.py:256
Function
get_ray_directions
Get ray directions for all pixels in camera coordinate. Reference: https://www.scratchapixel.com/lessons/3d-basic-rendering/ r
midi/utils/ops.py:163
Function
get_rays
( directions: Float[Tensor, "... 3"], c2w: Float[Tensor, "... 4 4"], keepdim=False, noise_scal
midi/utils/ops.py:207
Method
guidance_scale
(self)
midi/pipelines/pipeline_midi.py:128
Method
include_fn
(k)
midi/pipelines/pipeline_midi.py:595
Function
instantiate_from_config
(config, **kwargs)
midi/utils/misc.py:85
Method
interrupt
(self)
midi/pipelines/pipeline_midi.py:144
Method
kl
(self, other: "DiagonalGaussianDistribution" = None)
midi/models/autoencoders/vae.py:38
Function
laplacian_smooth
(ms, stepsmoothnum=3, verbose=False)
midi/utils/mesh_process.py:136
Method
mode
(self)
midi/models/autoencoders/vae.py:68
Method
nll
( self, sample: torch.Tensor, dims: Tuple[int, ...] = [1, 2, 3] )
midi/models/autoencoders/vae.py:57
Method
non_module
(self, name: str)
midi/utils/base.py:122
Method
normalize_
(tensor)
midi/systems/system_midi.py:239
Method
num_timesteps
(self)
midi/pipelines/pipeline_midi.py:136
Method
on_before_optimizer_step
# some gradient-related debugging goes here, example: from lightning.pytorch.utilities import grad_norm norms = grad_norm(sel
midi/systems/base.py:252
Method
on_check_train
(self, batch)
midi/systems/system_midi.py:178
Method
on_fit_start
(self, trainer, pl_module)
midi/utils/callbacks.py:90
Method
on_fit_start
(self, trainer, pl_module)
midi/utils/callbacks.py:111
Method
on_fit_start
(self)
midi/systems/system_midi.py:131
Method
on_fit_start
(self)
midi/systems/base.py:130
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