SYMBOL INDEX (159 symbols across 33 files)

FILE: datasets/base_dataset.py
  class BaseDataset (line 7) | class BaseDataset(Dataset):
    method __init__ (line 9) | def __init__(self):

FILE: datasets/imagenet.py
  class ImageNet (line 13) | class ImageNet(Dataset):
    method __init__ (line 15) | def __init__(self, root_dir, split="train"):
    method __getitem__ (line 42) | def __getitem__(self, index):
    method __len__ (line 52) | def __len__(self):

FILE: datasets/shapenet.py
  class ShapeNet (line 15) | class ShapeNet(BaseDataset):
    method __init__ (line 20) | def __init__(self, file_root, file_list_name, mesh_pos, normalization,...
    method __getitem__ (line 34) | def __getitem__(self, index):
    method __len__ (line 74) | def __len__(self):
  class ShapeNetImageFolder (line 78) | class ShapeNetImageFolder(BaseDataset):
    method __init__ (line 80) | def __init__(self, folder, normalization, shapenet_options):
    method __getitem__ (line 96) | def __getitem__(self, item):
    method __len__ (line 119) | def __len__(self):
  function get_shapenet_collate (line 123) | def get_shapenet_collate(num_points):

FILE: entrypoint_eval.py
  function parse_args (line 8) | def parse_args():
  function main (line 30) | def main():

FILE: entrypoint_predict.py
  function parse_args (line 8) | def parse_args():
  function main (line 30) | def main():

FILE: entrypoint_train.py
  function parse_args (line 8) | def parse_args():
  function main (line 30) | def main():

FILE: external/chamfer/chamfer_cuda.cpp
  function chamfer_forward (line 11) | int chamfer_forward(at::Tensor xyz1, at::Tensor xyz2, at::Tensor dist1, ...
  function chamfer_backward (line 16) | int chamfer_backward(at::Tensor xyz1, at::Tensor xyz2, at::Tensor gradxy...
  function PYBIND11_MODULE (line 22) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: functions/base.py
  class CheckpointRunner (line 17) | class CheckpointRunner(object):
    method __init__ (line 18) | def __init__(self, options, logger: Logger, summary_writer: SummaryWri...
    method load_dataset (line 63) | def load_dataset(self, dataset, training):
    method load_collate_fn (line 74) | def load_collate_fn(self, dataset, training):
    method init_fn (line 80) | def init_fn(self, shared_model=None, **kwargs):
    method models_dict (line 84) | def models_dict(self):
    method optimizers_dict (line 87) | def optimizers_dict(self):
    method init_with_checkpoint (line 91) | def init_with_checkpoint(self):
    method dump_checkpoint (line 113) | def dump_checkpoint(self):
    method time_elapsed (line 132) | def time_elapsed(self):

FILE: functions/evaluator.py
  class Evaluator (line 17) | class Evaluator(CheckpointRunner):
    method __init__ (line 19) | def __init__(self, options, logger: Logger, writer, shared_model=None):
    method init_fn (line 23) | def init_fn(self, shared_model=None, **kwargs):
    method models_dict (line 56) | def models_dict(self):
    method evaluate_f1 (line 59) | def evaluate_f1(self, dis_to_pred, dis_to_gt, pred_length, gt_length, ...
    method evaluate_chamfer_and_f1 (line 64) | def evaluate_chamfer_and_f1(self, pred_vertices, gt_points, labels):
    method evaluate_accuracy (line 78) | def evaluate_accuracy(self, output, target):
    method evaluate_step (line 96) | def evaluate_step(self, input_batch):
    method evaluate (line 118) | def evaluate(self):
    method average_of_average_meters (line 162) | def average_of_average_meters(self, average_meters):
    method get_result_summary (line 174) | def get_result_summary(self):
    method evaluate_summaries (line 187) | def evaluate_summaries(self, input_batch, out_summary):

FILE: functions/predictor.py
  class Predictor (line 17) | class Predictor(CheckpointRunner):
    method __init__ (line 19) | def __init__(self, options, logger: Logger, writer, shared_model=None):
    method init_fn (line 23) | def init_fn(self, shared_model=None, **kwargs):
    method models_dict (line 47) | def models_dict(self):
    method predict_step (line 50) | def predict_step(self, input_batch):
    method predict (line 59) | def predict(self):
    method save_inference_results (line 76) | def save_inference_results(self, inputs, outputs):

FILE: functions/saver.py
  class CheckpointSaver (line 7) | class CheckpointSaver(object):
    method __init__ (line 10) | def __init__(self, logger, checkpoint_dir=None, checkpoint_file=None):
    method load_checkpoint (line 23) | def load_checkpoint(self):
    method save_checkpoint (line 34) | def save_checkpoint(self, obj, name):
    method get_latest_checkpoint (line 39) | def get_latest_checkpoint(self):

FILE: functions/trainer.py
  class Trainer (line 20) | class Trainer(CheckpointRunner):
    method init_fn (line 23) | def init_fn(self, shared_model=None, **kwargs):
    method models_dict (line 82) | def models_dict(self):
    method optimizers_dict (line 85) | def optimizers_dict(self):
    method train_step (line 89) | def train_step(self, input_batch):
    method train (line 110) | def train(self):
    method train_summaries (line 154) | def train_summaries(self, input_batch, out_summary, loss_summary):
    method test (line 176) | def test(self):

FILE: logger.py
  function create_logger (line 5) | def create_logger(cfg, phase='train'):

FILE: models/backbones/__init__.py
  function get_backbone (line 5) | def get_backbone(options):

FILE: models/backbones/resnet.py
  class P2MResNet (line 8) | class P2MResNet(ResNet):
    method __init__ (line 10) | def __init__(self, *args, **kwargs):
    method _make_layer (line 14) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method forward (line 19) | def forward(self, x):
    method features_dim (line 38) | def features_dim(self):
  function resnet50 (line 42) | def resnet50():

FILE: models/backbones/vgg16.py
  class VGG16TensorflowAlign (line 8) | class VGG16TensorflowAlign(nn.Module):
    method __init__ (line 10) | def __init__(self, n_classes_input=3):
    method forward (line 44) | def forward(self, img):
  class VGG16P2M (line 76) | class VGG16P2M(nn.Module):
    method __init__ (line 78) | def __init__(self, n_classes_input=3, pretrained=False):
    method _initialize_weights (line 113) | def _initialize_weights(self):
    method forward (line 126) | def forward(self, img):
  class VGG16Recons (line 160) | class VGG16Recons(nn.Module):
    method __init__ (line 162) | def __init__(self, input_dim=512, image_channel=3):
    method forward (line 171) | def forward(self, img_feats):

FILE: models/classifier.py
  class Classifier (line 6) | class Classifier(nn.Module):
    method __init__ (line 8) | def __init__(self, options, num_classes):
    method _initialize_weights (line 30) | def _initialize_weights(self):
    method forward (line 36) | def forward(self, img):

FILE: models/layers/chamfer_wrapper.py
  class ChamferFunction (line 9) | class ChamferFunction(Function):
    method forward (line 11) | def forward(ctx, xyz1, xyz2):
    method backward (line 31) | def backward(ctx, graddist1, graddist2, _idx1, _idx2):
  class ChamferDist (line 45) | class ChamferDist(nn.Module):
    method __init__ (line 46) | def __init__(self):
    method forward (line 49) | def forward(self, input1, input2):

FILE: models/layers/gbottleneck.py
  class GResBlock (line 7) | class GResBlock(nn.Module):
    method __init__ (line 9) | def __init__(self, in_dim, hidden_dim, adj_mat, activation=None):
    method forward (line 16) | def forward(self, inputs):
  class GBottleneck (line 27) | class GBottleneck(nn.Module):
    method __init__ (line 29) | def __init__(self, block_num, in_dim, hidden_dim, out_dim, adj_mat, ac...
    method forward (line 39) | def forward(self, inputs):

FILE: models/layers/gconv.py
  class GConv (line 9) | class GConv(nn.Module):
    method __init__ (line 15) | def __init__(self, in_features, out_features, adj_mat, bias=True):
    method reset_parameters (line 31) | def reset_parameters(self):
    method forward (line 35) | def forward(self, inputs):
    method __repr__ (line 45) | def __repr__(self):

FILE: models/layers/gpooling.py
  class GUnpooling (line 6) | class GUnpooling(nn.Module):
    method __init__ (line 13) | def __init__(self, unpool_idx):
    method forward (line 20) | def forward(self, inputs):
    method __repr__ (line 27) | def __repr__(self):

FILE: models/layers/gprojection.py
  class GProjection (line 8) | class GProjection(nn.Module):
    method __init__ (line 16) | def __init__(self, mesh_pos, camera_f, camera_c, bound=0, tensorflow_c...
    method bound_val (line 25) | def bound_val(self, x):
    method image_feature_shape (line 36) | def image_feature_shape(img):
    method project_tensorflow (line 39) | def project_tensorflow(self, x, y, img_size, img_feat):
    method forward (line 69) | def forward(self, resolution, img_features, inputs):
    method project (line 101) | def project(self, img_shape, img_feat, sample_points):

FILE: models/losses/classifier.py
  class CrossEntropyLoss (line 5) | class CrossEntropyLoss(nn.Module):
    method __init__ (line 6) | def __init__(self):
    method forward (line 10) | def forward(self, outputs, targets):

FILE: models/losses/p2m.py
  class P2MLoss (line 8) | class P2MLoss(nn.Module):
    method __init__ (line 9) | def __init__(self, options, ellipsoid):
    method edge_regularization (line 20) | def edge_regularization(self, pred, edges):
    method laplace_coord (line 29) | def laplace_coord(inputs, lap_idx):
    method laplace_regularization (line 52) | def laplace_regularization(self, input1, input2, block_idx):
    method normal_loss (line 68) | def normal_loss(self, gt_normal, indices, pred_points, adj_list):
    method image_loss (line 75) | def image_loss(self, gt_img, pred_img):
    method forward (line 79) | def forward(self, outputs, targets):

FILE: models/p2m.py
  class P2MModel (line 12) | class P2MModel(nn.Module):
    method __init__ (line 14) | def __init__(self, options, ellipsoid, camera_f, camera_c, mesh_pos):
    method forward (line 50) | def forward(self, img):

FILE: options.py
  function _update_dict (line 96) | def _update_dict(full_key, val, d):
  function _update_options (line 108) | def _update_options(options_file):
  function update_options (line 123) | def update_options(options_file):
  function gen_options (line 127) | def gen_options(options_file):
  function slugify (line 143) | def slugify(filename):
  function reset_options (line 150) | def reset_options(options, args, phase='train'):

FILE: test.py
  function test (line 7) | def test():

FILE: utils/average_meter.py
  class AverageMeter (line 9) | class AverageMeter(object):
    method __init__ (line 12) | def __init__(self, multiplier=1.0):
    method reset (line 16) | def reset(self):
    method update (line 22) | def update(self, val, n=1):
    method __str__ (line 34) | def __str__(self):

FILE: utils/mesh.py
  function torch_sparse_tensor (line 12) | def torch_sparse_tensor(indices, value, size):
  class Ellipsoid (line 24) | class Ellipsoid(object):
    method __init__ (line 26) | def __init__(self, mesh_pos, file=config.ELLIPSOID_PATH):

FILE: utils/migrations/tensorflow_to_pkl.py
  function nn_distance (line 9) | def nn_distance(xyz1, xyz2):
  function _nn_distance_grad (line 23) | def _nn_distance_grad(op, grad_dist1, grad_idx1, grad_dist2, grad_idx2):

FILE: utils/migrations/validate_dataset_all.py
  function go (line 8) | def go(file_path, subset):

FILE: utils/tensor.py
  function recursive_detach (line 8) | def recursive_detach(t):
  function batch_mm (line 19) | def batch_mm(matrix, batch):
  function dot (line 27) | def dot(x, y, sparse=False):

FILE: utils/vis/renderer.py
  function _process_render_result (line 7) | def _process_render_result(img, height, width):
  function _mix_render_result_with_image (line 20) | def _mix_render_result_with_image(rgb, alpha, image):
  class MeshRenderer (line 25) | class MeshRenderer(object):
    method __init__ (line 27) | def __init__(self, camera_f, camera_c, mesh_pos):
    method _render_mesh (line 42) | def _render_mesh(self, vertices: np.ndarray, faces: np.ndarray, width,...
    method _render_pointcloud (line 79) | def _render_pointcloud(self, vertices: np.ndarray, width, height,
    method visualize_reconstruction (line 100) | def visualize_reconstruction(self, gt_coord, coord, faces, image, mesh...
    method p2m_batch_visualize (line 119) | def p2m_batch_visualize(self, batch_input, batch_output, faces, atmost...