SYMBOL INDEX (339 symbols across 37 files)

FILE: interdiff/data/dataset_skeleton.py
  function parse_paths (line 20) | def parse_paths():
  function recover_init_obj (line 40) | def recover_init_obj(initial_obj, initial_pose):
  function get_consistent_poses (line 53) | def get_consistent_poses(downsampled_poses):
  function pose_init_to_seq (line 67) | def pose_init_to_seq(zero_pose_obj, poses):
  function check_sequences (line 85) | def check_sequences(poseData, objData,discard_discrep):
  function get_sequences (line 108) | def get_sequences(pathName, discard_discrep=False,unseen=False,filename ...
  function get_datasets (line 164) | def get_datasets(align_data=False,discard_discrep=False):
  function get_unseen_dataset (line 207) | def get_unseen_dataset():
  class SimpleDataset (line 220) | class SimpleDataset(Dataset):
    method __init__ (line 221) | def __init__(self,sequences):
    method __getitem__ (line 224) | def __getitem__(self, index):
    method __len__ (line 227) | def __len__(self):

FILE: interdiff/data/dataset_smpl.py
  class Dataset (line 25) | class Dataset(Dataset):
    method __init__ (line 26) | def __init__(self, mode='train', past_len=10, future_len=25, sample_ra...
    method __getitem__ (line 105) | def __getitem__(self, idx):
    method __len__ (line 206) | def __len__(self):

FILE: interdiff/data/prepare_behave.py
  class ContactLabelGenerator (line 26) | class ContactLabelGenerator(object):
    method __init__ (line 28) | def __init__(self):
    method get_contact_labels (line 32) | def get_contact_labels(self, smpl, object_points, thres=0.02):
    method to_trimesh (line 54) | def to_trimesh(self, mesh):
  function main (line 59) | def main(args, name):

FILE: interdiff/data/tools.py
  function vertex_normals (line 4) | def vertex_normals(vertices, faces):

FILE: interdiff/data/utils.py
  function to_tensor (line 10) | def to_tensor(
  class VertexJointSelector (line 164) | class VertexJointSelector(nn.Module):
    method __init__ (line 166) | def __init__(self, vertex_ids=SMPLH_VERTEX_INDEX,
    method forward (line 208) | def forward(self, vertices, joints):
  function get_root_idx (line 409) | def get_root_idx(joinstype):
  function get_body_model (line 413) | def get_body_model(path, model_type, gender, batch_size, device='cpu', e...

FILE: interdiff/diffusion/gaussian_diffusion.py
  function get_named_beta_schedule (line 20) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps, scal...
  function betas_for_alpha_bar (line 47) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
  class ModelMeanType (line 67) | class ModelMeanType(enum.Enum):
  class ModelVarType (line 77) | class ModelVarType(enum.Enum):
  class LossType (line 91) | class LossType(enum.Enum):
    method is_vb (line 99) | def is_vb(self):
  class GaussianDiffusion (line 103) | class GaussianDiffusion:
    method __init__ (line 120) | def __init__(
    method masked_l2 (line 201) | def masked_l2(self, a, b, mask):
    method q_mean_variance (line 216) | def q_mean_variance(self, x_start, t):
    method q_sample (line 233) | def q_sample(self, x_start, t, noise=None):
    method q_posterior_mean_variance (line 253) | def q_posterior_mean_variance(self, x_start, x_t, t):
    method p_mean_variance (line 277) | def p_mean_variance(
    method _predict_xstart_from_eps (line 390) | def _predict_xstart_from_eps(self, x_t, t, eps):
    method _predict_xstart_from_xprev (line 397) | def _predict_xstart_from_xprev(self, x_t, t, xprev):
    method _predict_eps_from_xstart (line 407) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
    method _scale_timesteps (line 413) | def _scale_timesteps(self, t):
    method condition_mean (line 418) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_mean_with_grad (line 433) | def condition_mean_with_grad(self, cond_fn, p_mean_var, x, t, model_kw...
    method condition_score (line 448) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
    method condition_score_with_grad (line 472) | def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_k...
    method p_sample (line 496) | def p_sample(
    method p_sample_with_grad (line 550) | def p_sample_with_grad(
    method p_sample_loop (line 598) | def p_sample_loop(
    method p_sample_loop_progressive (line 663) | def p_sample_loop_progressive(
    method ddim_sample (line 738) | def ddim_sample(
    method ddim_sample_with_grad (line 790) | def ddim_sample_with_grad(
    method ddim_reverse_sample (line 847) | def ddim_reverse_sample(
    method ddim_sample_loop (line 885) | def ddim_sample_loop(
    method ddim_sample_loop_progressive (line 934) | def ddim_sample_loop_progressive(
    method plms_sample (line 1001) | def plms_sample(
    method plms_sample_loop (line 1085) | def plms_sample_loop(
    method plms_sample_loop_progressive (line 1127) | def plms_sample_loop_progressive(
    method _vb_terms_bpd (line 1198) | def _vb_terms_bpd(
    method training_losses (line 1233) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
    method fc_loss_rot_repr (line 1370) | def fc_loss_rot_repr(self, gt_xyz, pred_xyz, mask):
    method _prior_bpd (line 1535) | def _prior_bpd(self, x_start):
    method calc_bpd_loop (line 1553) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
  function _extract_into_tensor (line 1611) | def _extract_into_tensor(arr, timesteps, broadcast_shape):

FILE: interdiff/diffusion/losses.py
  function normal_kl (line 12) | def normal_kl(mean1, logvar1, mean2, logvar2):
  function approx_standard_normal_cdf (line 42) | def approx_standard_normal_cdf(x):
  function discretized_gaussian_log_likelihood (line 50) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):

FILE: interdiff/diffusion/nn.py
  class SiLU (line 13) | class SiLU(nn.Module):
    method forward (line 14) | def forward(self, x):
  class GroupNorm32 (line 18) | class GroupNorm32(nn.GroupNorm):
    method forward (line 19) | def forward(self, x):
  function conv_nd (line 23) | def conv_nd(dims, *args, **kwargs):
  function linear (line 36) | def linear(*args, **kwargs):
  function avg_pool_nd (line 43) | def avg_pool_nd(dims, *args, **kwargs):
  function update_ema (line 56) | def update_ema(target_params, source_params, rate=0.99):
  function zero_module (line 69) | def zero_module(module):
  function scale_module (line 78) | def scale_module(module, scale):
  function mean_flat (line 87) | def mean_flat(tensor):
  function sum_flat (line 93) | def sum_flat(tensor):
  function normalization (line 100) | def normalization(channels):
  function timestep_embedding (line 110) | def timestep_embedding(timesteps, dim, max_period=10000):
  function checkpoint (line 131) | def checkpoint(func, inputs, params, flag):
  class CheckpointFunction (line 148) | class CheckpointFunction(th.autograd.Function):
    method forward (line 151) | def forward(ctx, run_function, length, *args):
    method backward (line 161) | def backward(ctx, *output_grads):

FILE: interdiff/diffusion/resample.py
  function create_named_schedule_sampler (line 8) | def create_named_schedule_sampler(name, diffusion):
  class ScheduleSampler (line 23) | class ScheduleSampler(ABC):
    method weights (line 35) | def weights(self):
    method sample (line 42) | def sample(self, batch_size, device):
  class UniformSampler (line 61) | class UniformSampler(ScheduleSampler):
    method __init__ (line 62) | def __init__(self, diffusion):
    method weights (line 66) | def weights(self):
  class LossAwareSampler (line 70) | class LossAwareSampler(ScheduleSampler):
    method update_with_local_losses (line 71) | def update_with_local_losses(self, local_ts, local_losses):
    method update_with_all_losses (line 107) | def update_with_all_losses(self, ts, losses):
  class LossSecondMomentResampler (line 124) | class LossSecondMomentResampler(LossAwareSampler):
    method __init__ (line 125) | def __init__(self, diffusion, history_per_term=10, uniform_prob=0.001):
    method weights (line 134) | def weights(self):
    method update_with_all_losses (line 143) | def update_with_all_losses(self, ts, losses):
    method _warmed_up (line 153) | def _warmed_up(self):

FILE: interdiff/diffusion/respace.py
  function space_timesteps (line 8) | def space_timesteps(num_timesteps, section_counts):
  class SpacedDiffusion (line 64) | class SpacedDiffusion(GaussianDiffusion):
    method __init__ (line 73) | def __init__(self, use_timesteps, **kwargs):
    method p_mean_variance (line 89) | def p_mean_variance(
    method training_losses (line 94) | def training_losses(
    method condition_mean (line 99) | def condition_mean(self, cond_fn, *args, **kwargs):
    method condition_score (line 102) | def condition_score(self, cond_fn, *args, **kwargs):
    method _wrap_model (line 105) | def _wrap_model(self, model):
    method _scale_timesteps (line 112) | def _scale_timesteps(self, t):
  class _WrappedModel (line 117) | class _WrappedModel:
    method __init__ (line 118) | def __init__(self, model, timestep_map, rescale_timesteps, original_nu...
    method __call__ (line 124) | def __call__(self, x, ts, **kwargs):

FILE: interdiff/eval_skeleton.py
  function body_obj_to_contact (line 17) | def body_obj_to_contact(body, obj):
  function calc_obj_pred (line 34) | def calc_obj_pred(pose_pred, zero_pose_obj):
  function calc_metric_single (line 46) | def calc_metric_single(body_pred, body_gt, obj_pred, obj_gt, pose_pred, ...
  function get_batch (line 70) | def get_batch(old_batch, body_pred, obj_pred, pose_pred):
  function denoised_fn (line 82) | def denoised_fn(x, t, model_kwargs):
  function sample_once_proj (line 114) | def sample_once_proj(batch):
  function sample (line 145) | def sample(t, dataloader, data_size):

FILE: interdiff/eval_skeleton_no_correction.py
  function body_obj_to_contact (line 17) | def body_obj_to_contact(body, obj):
  function calc_obj_pred (line 34) | def calc_obj_pred(pose_pred, zero_pose_obj):
  function calc_metric_single (line 46) | def calc_metric_single(body_pred, body_gt, obj_pred, obj_gt, pose_pred, ...
  function get_batch (line 70) | def get_batch(old_batch, body_pred, obj_pred, pose_pred):
  function denoised_fn (line 82) | def denoised_fn(x, t, model_kwargs):
  function sample_once_proj (line 85) | def sample_once_proj(batch):
  function sample (line 115) | def sample(t, dataloader, data_size):

FILE: interdiff/eval_smpl_long.py
  function get_batch (line 26) | def get_batch(body, obj, batch, verts, pel):
  function denoised_fn (line 86) | def denoised_fn(x, t, model_kwargs):
  function sample_once_proj (line 135) | def sample_once_proj(batch):
  function sample_once (line 181) | def sample_once(batch):
  function get_gt (line 220) | def get_gt(batch):
  function sample (line 247) | def sample(name, T=0):
  function visualize (line 313) | def visualize(batch, j, obj, verts, faces, name):

FILE: interdiff/eval_smpl_short.py
  function metrics (line 24) | def metrics(obj_pred, body_jtr, body, obj_gt, body_jtr_gt, body_gt, vert...
  function denoised_fn (line 84) | def denoised_fn(x, t, model_kwargs):
  function sample_once_proj (line 133) | def sample_once_proj(batch):
  function sample_once (line 179) | def sample_once(batch):
  function smooth (line 217) | def smooth(obj, body, verts, jtrs, pelvis):
  function get_gt (line 225) | def get_gt(batch):
  function sample (line 252) | def sample(name):
  function visualize (line 305) | def visualize(batch, j, obj, verts, faces, name):

FILE: interdiff/libsmpl/smplpytorch/native/webuser/lbs.py
  function global_rigid_transformation (line 23) | def global_rigid_transformation(pose, J, kintree_table, xp):
  function verts_core (line 59) | def verts_core(pose, v, J, weights, kintree_table, want_Jtr=False, xp=ch...

FILE: interdiff/libsmpl/smplpytorch/native/webuser/posemapper.py
  class Rodrigues (line 21) | class Rodrigues(ch.Ch):
    method compute_r (line 24) | def compute_r(self):
    method compute_dr_wrt (line 27) | def compute_dr_wrt(self, wrt):
  function lrotmin (line 32) | def lrotmin(p):
  function posemap (line 42) | def posemap(s):

FILE: interdiff/libsmpl/smplpytorch/native/webuser/serialization.py
  function backwards_compatibility_replacements (line 29) | def backwards_compatibility_replacements(dd):
  function ready_arguments (line 52) | def ready_arguments(fname_or_dict):
  function load_model (line 88) | def load_model(fname_or_dict):

FILE: interdiff/libsmpl/smplpytorch/native/webuser/verts.py
  function ischumpy (line 28) | def ischumpy(x): return hasattr(x, 'dterms')
  function verts_decorated (line 31) | def verts_decorated(trans, pose,
  function verts_core (line 91) | def verts_core(pose, v, J, weights, kintree_table, bs_style, want_Jtr=Fa...

FILE: interdiff/libsmpl/smplpytorch/pytorch/rodrigues_layer.py
  function quat2mat (line 13) | def quat2mat(quat):
  function batch_rodrigues (line 41) | def batch_rodrigues(axisang):
  function th_get_axis_angle (line 55) | def th_get_axis_angle(vector):

FILE: interdiff/libsmpl/smplpytorch/pytorch/smpl_layer.py
  class SMPL_Layer (line 17) | class SMPL_Layer(Module):
    method __init__ (line 20) | def __init__(self,
    method forward (line 72) | def forward(self,

FILE: interdiff/libsmpl/smplpytorch/pytorch/tensutils.py
  function th_posemap_axisang (line 6) | def th_posemap_axisang(pose_vectors):
  function th_with_zeros (line 22) | def th_with_zeros(tensor):
  function th_pack (line 32) | def th_pack(tensor):
  function subtract_flat_id (line 41) | def subtract_flat_id(rot_mats, hands=False):
  function make_list (line 56) | def make_list(tensor):

FILE: interdiff/model/correction_skeleton.py
  class ObjProjector (line 7) | class ObjProjector(nn.Module):
    method __init__ (line 8) | def __init__(self, args):
    method get_dct_matrix (line 54) | def get_dct_matrix(self, N, is_torch=True):
    method forward (line 68) | def forward(self, obj_angles, obj_trans, human_points):
    method sample (line 84) | def sample(self, obj_angles, obj_trans, human_points):

FILE: interdiff/model/correction_smpl.py
  class ObjProjector (line 8) | class ObjProjector(nn.Module):
    method __init__ (line 9) | def __init__(self, args):
    method get_dct_matrix (line 55) | def get_dct_matrix(self, N, is_torch=True):
    method forward (line 69) | def forward(self, data, initialize=False):
    method sample (line 79) | def sample(self, obj_angles, obj_trans, human_verts, contact, initiali...

FILE: interdiff/model/diffusion_skeleton.py
  class MDM (line 7) | class MDM(nn.Module):
    method __init__ (line 14) | def __init__(self, args):
    method mask_cond (line 184) | def mask_cond(self, cond, force_mask=False):
    method _get_embeddings (line 194) | def _get_embeddings(self, body_gt, obj_gt, pose_gt, zero_pose_obj):
    method calc_obj_pred (line 218) | def calc_obj_pred(self, pose_pred, zero_pose_obj):
    method _decode (line 231) | def _decode(self, x, time_embedding, y=None, zero_pose_obj=None):
    method forward (line 250) | def forward(self, x, timesteps,zero_pose_obj, y=None):
  function create_gaussian_diffusion (line 262) | def create_gaussian_diffusion(args):
  function create_model_and_diffusion (line 297) | def create_model_and_diffusion(args):

FILE: interdiff/model/diffusion_smpl.py
  class MDM (line 8) | class MDM(nn.Module):
    method __init__ (line 9) | def __init__(self, args):
    method mask_cond (line 185) | def mask_cond(self, cond, force_mask=False):
    method _get_embeddings (line 195) | def _get_embeddings(self, data, device=None):
    method _decode (line 226) | def _decode(self, x, time_embedding, y=None):
    method forward (line 239) | def forward(self, x, timesteps, y=None):
  function create_gaussian_diffusion (line 251) | def create_gaussian_diffusion(args):
  function create_model_and_diffusion (line 286) | def create_model_and_diffusion(args):

FILE: interdiff/model/layers.py
  class PositionalEncoding (line 9) | class PositionalEncoding(nn.Module):
    method __init__ (line 10) | def __init__(self, d_model, dropout=0.1, max_len=5000):
    method forward (line 24) | def forward(self, x):
  class TimestepEmbedder (line 29) | class TimestepEmbedder(nn.Module):
    method __init__ (line 30) | def __init__(self, latent_dim, sequence_pos_encoder):
    method forward (line 42) | def forward(self, timesteps):
  class Embedder (line 48) | class Embedder:
    method __init__ (line 49) | def __init__(self, **kwargs):
    method create_embedding_fn (line 53) | def create_embedding_fn(self):
    method embed (line 77) | def embed(self, inputs):
  function get_embedder (line 81) | def get_embedder(multires, i=0, input_dimension=3):
  class NormalDistDecoder (line 98) | class NormalDistDecoder(nn.Module):
    method __init__ (line 99) | def __init__(self, num_feat_in, latentD):
    method forward (line 106) | def forward(self, Xout):
  class PointNet2Encoder (line 111) | class PointNet2Encoder(nn.Module):
    method __init__ (line 115) | def __init__(self, c_in=6, c_out=128, num_keypoints=256):
    method _break_up_pc (line 145) | def _break_up_pc(self, pc):
    method forward (line 151) | def forward(self, pointcloud):
  class TransformerEncoder (line 177) | class TransformerEncoder(nn.Module):
    method __init__ (line 193) | def __init__(self, encoder_layer, norm=None):
    method forward (line 198) | def forward(self, src: Tensor, mask: Optional[Tensor] = None, src_key_...
  class TransformerDecoder (line 220) | class TransformerDecoder(nn.Module):
    method __init__ (line 237) | def __init__(self, decoder_layer, norm=None):
    method forward (line 242) | def forward(self, tgt: Tensor, memory: Tensor, tgt_mask: Optional[Tens...
  class ST_GCNN_layer (line 271) | class ST_GCNN_layer(nn.Module):
    method __init__ (line 286) | def __init__(self,
    method forward (line 339) | def forward(self, x):

FILE: interdiff/model/sublayers.py
  function _get_activation_fn (line 10) | def _get_activation_fn(activation):
  function _normalize_and_reshape_query (line 18) | def _normalize_and_reshape_query(q, heads, unit_norm, depth_scale, norma...
  class TransformerEncoderLayerQaN (line 37) | class TransformerEncoderLayerQaN(nn.Module):
    method __init__ (line 70) | def __init__(self, d_model: int, nhead: int, dim_feedforward: int = 20...
    method _get_query (line 120) | def _get_query(self, x):
    method __setstate__ (line 131) | def __setstate__(self, state):
    method forward (line 136) | def forward(self, src: Tensor, src_mask: Optional[Tensor] = None, src_...
    method _qa_block (line 180) | def _qa_block(self, x: Tensor,
    method _sa_block (line 192) | def _sa_block(self, x: Tensor,
    method _ff_block (line 201) | def _ff_block(self, x: Tensor) -> Tensor:
  class TransformerDecoderLayerQaN (line 206) | class TransformerDecoderLayerQaN(nn.Module):
    method __init__ (line 242) | def __init__(self, d_model: int, nhead: int, dim_feedforward: int = 20...
    method _get_query (line 295) | def _get_query(self, x):
    method __setstate__ (line 306) | def __setstate__(self, state):
    method forward (line 311) | def forward(self, tgt: Tensor, memory: Tensor, tgt_mask: Optional[Tens...
    method _qa_block (line 343) | def _qa_block(self, x: Tensor,
    method _sa_block (line 355) | def _sa_block(self, x: Tensor,
    method _mha_block (line 364) | def _mha_block(self, x: Tensor, mem: Tensor,
    method _ff_block (line 373) | def _ff_block(self, x: Tensor) -> Tensor:
  class ConvTemporalGraphical (line 378) | class ConvTemporalGraphical(nn.Module):
    method __init__ (line 402) | def __init__(self,
    method forward (line 415) | def forward(self, x):
  class ConvSpatialGraphical (line 421) | class ConvSpatialGraphical(nn.Module):
    method __init__ (line 445) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  class ConvSpatialTemporalGraphical (line 464) | class ConvSpatialTemporalGraphical(nn.Module):
    method __init__ (line 488) | def __init__(self,
    method forward (line 511) | def forward(self, x):

FILE: interdiff/optimization.py
  function optimize (line 19) | def optimize(index, data, visualize=False):

FILE: interdiff/render/mesh_utils.py
  function get_checkerboard_plane (line 25) | def get_checkerboard_plane(plane_mins, center=True):
  class MeshViewer (line 64) | class MeshViewer(object):
    method __init__ (line 66) | def __init__(self, width=1200, height=800, add_ground_plane=False,
    method set_background_color (line 110) | def set_background_color(self, color=colors['white']):
    method update_camera_pose (line 113) | def update_camera_pose(self, camera_pose):
    method close_viewer (line 116) | def close_viewer(self):
    method set_cam_trans (line 120) | def set_cam_trans(self, trans= [0, 0, 3.0]):
    method set_meshes (line 132) | def set_meshes(self, meshes, group_name='static', poses=[]):
    method set_static_meshes (line 153) | def set_static_meshes(self, meshes, poses=[]): self.set_meshes(meshes,...
    method set_dynamic_meshes (line 154) | def set_dynamic_meshes(self, meshes, poses=[]): self.set_meshes(meshes...
    method _add_raymond_light (line 156) | def _add_raymond_light(self):
    method use_raymond_lighting (line 186) | def use_raymond_lighting(self, intensity = 1.0):
    method render (line 195) | def render(self, render_wireframe=None, RGBA=False):

FILE: interdiff/render/mesh_viz.py
  function c2rgba (line 26) | def c2rgba(c):
  function visualize_body_obj (line 33) | def visualize_body_obj(body_verts, body_face, obj_verts, obj_face, past_...
  function tobodyparts (line 157) | def tobodyparts(m_pcd, past=False):

FILE: interdiff/render/viz_helper.py
  function visualize_skeleton (line 29) | def visualize_skeleton(skeledonData, objPoint, save_dir = './test.gif'):
  function visualize_skeleton_pred_gt (line 77) | def visualize_skeleton_pred_gt(skeledonData, objPoint, skeledonData_gt, ...

FILE: interdiff/tools.py
  function point2point_signed (line 11) | def point2point_signed(
  function aa2matrot (line 78) | def aa2matrot(pose):
  function rotvec_to_rotmat (line 88) | def rotvec_to_rotmat(rotvec):
  function mesh_laplacian_smoothing (line 92) | def mesh_laplacian_smoothing(meshes, method: str = "uniform"):
  class LaplacianLoss (line 213) | class LaplacianLoss(nn.Module):
    method __init__ (line 215) | def __init__(self, faces):
    method forward (line 221) | def forward(self, x, y):
  class NormalConsistencyLoss (line 241) | class NormalConsistencyLoss(nn.Module):
    method __init__ (line 243) | def __init__(self, faces):
    method forward (line 248) | def forward(self, x):
  class NormalVectorLoss (line 258) | class NormalVectorLoss(nn.Module):
    method __init__ (line 260) | def __init__(self, face):
    method forward (line 264) | def forward(self, coord_out, coord_gt):
  class EdgeLengthLoss (line 288) | class EdgeLengthLoss(nn.Module):
    method __init__ (line 289) | def __init__(self, face, relative_length=False):
    method forward (line 294) | def forward(self, coord_out, coord_gt):

FILE: interdiff/train_correction_skeleton.py
  class LitObjInteraction (line 19) | class LitObjInteraction(pl.LightningModule):
    method __init__ (line 20) | def __init__(self, args):
    method on_train_start (line 31) | def on_train_start(self) -> None:
    method configure_optimizers (line 41) | def configure_optimizers(self):
    method calc_obj_pred (line 49) | def calc_obj_pred(self, pose_pred, zero_pose_obj):
    method calc_metric (line 61) | def calc_metric(self, body_pred, body_gt, obj_pred, obj_gt, pose_pred,...
    method calc_loss (line 85) | def calc_loss(self, obj_pred, obj_gt):
    method _common_step (line 128) | def _common_step(self, batch, batch_idx, mode):
    method visualize (line 156) | def visualize(self, body_pred, obj_pred, body_gt, obj_gt, batch, batch...
    method training_step (line 182) | def training_step(self, batch, batch_idx):
    method validation_step (line 191) | def validation_step(self, batch, batch_idx):
    method test_step (line 198) | def test_step(self, batch, batch_idx):

FILE: interdiff/train_correction_smpl.py
  class LitInteraction (line 24) | class LitInteraction(pl.LightningModule):
    method __init__ (line 25) | def __init__(self, args):
    method on_train_start (line 41) | def on_train_start(self) -> None:
    method forward (line 48) | def forward(self, x, initialize=False):
    method configure_optimizers (line 51) | def configure_optimizers(self):
    method calc_loss (line 60) | def calc_loss(self, obj_pred, obj_gt, batch):
    method calc_loss_contact (line 103) | def calc_loss_contact(self, obj_pred, obj_gt, batch):
    method _common_step (line 187) | def _common_step(self, batch, batch_idx, mode):
    method training_step (line 263) | def training_step(self, batch, batch_idx):
    method validation_step (line 272) | def validation_step(self, batch, batch_idx):

FILE: interdiff/train_diffusion_skeleton.py
  class LitInteraction (line 22) | class LitInteraction(pl.LightningModule):
    method __init__ (line 23) | def __init__(self, args):
    method on_train_start (line 38) | def on_train_start(self) -> None:
    method l2 (line 46) | def l2(self, a, b):
    method calc_obj_pred (line 52) | def calc_obj_pred(self, pose_pred, zero_pose_obj):
    method calc_metric (line 65) | def calc_metric(self, body_pred, body_gt, obj_pred, obj_gt, pose_pred,...
    method forward_backward (line 89) | def forward_backward(self, batch, cond):
    method log_loss_dict (line 177) | def log_loss_dict(self, diffusion, ts, losses, loss):
    method configure_optimizers (line 181) | def configure_optimizers(self):
    method calc_val_loss (line 190) | def calc_val_loss(self, body_pred, body_gt, obj_pred, obj_gt, pose_pre...
    method _common_step (line 255) | def _common_step(self, batch, batch_idx, mode):
    method visualize (line 298) | def visualize(self, body_pred, obj_pred, body_gt, obj_gt, batch, batch...
    method training_step (line 324) | def training_step(self, batch, batch_idx):
    method validation_step (line 329) | def validation_step(self, batch, batch_idx):
    method test_step (line 335) | def test_step(self, batch, batch_idx):

FILE: interdiff/train_diffusion_smpl.py
  class LitInteraction (line 26) | class LitInteraction(pl.LightningModule):
    method __init__ (line 27) | def __init__(self, args):
    method on_train_start (line 46) | def on_train_start(self) -> None:
    method l2 (line 54) | def l2(self, a, b):
    method forward_backward (line 60) | def forward_backward(self, batch, cond):
    method log_loss_dict (line 168) | def log_loss_dict(self, diffusion, ts, losses, loss):
    method configure_optimizers (line 177) | def configure_optimizers(self):
    method calc_val_loss (line 185) | def calc_val_loss(self, body_pred, body_gt, obj_pred, obj_gt, batch):
    method calc_loss (line 262) | def calc_loss(self, body_pred, body_gt, obj_pred, obj_gt, batch):
    method _common_step (line 381) | def _common_step(self, batch, batch_idx, mode):
    method visualize (line 454) | def visualize(self, body_pred, obj_pred, body_gt, obj_gt, batch, batch...
    method training_step (line 513) | def training_step(self, batch, batch_idx):
    method validation_step (line 517) | def validation_step(self, batch, batch_idx):
    method test_step (line 525) | def test_step(self, batch, batch_idx):

FILE: setup.py
  function collect_docstring (line 8) | def collect_docstring(lines):
  function get_install_requirements (line 20) | def get_install_requirements():
  function setup_package (line 27) | def setup_package():