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Functions2,893 in github.com/QWTforGithub/T2LDM

⨍ Functions 2,893◇ Types & classes 478
↓ 2 callersFunctionindex_points
Input: pts: input points data, [B, C, N] idx: sample index data, [B, S, [K]] Return: new_points:, indexed points
utils/common.py:1867
↓ 2 callersMethodinit_weights
(self, nlhb=False)
timm/models/mlp_mixer.py:275
↓ 2 callersFunctioninplace_abn
(x, weight, bias, running_mean, running_var, training=True, momentum=0.1, eps=1e-05, activ
timm/models/layers/inplace_abn.py:10
↓ 2 callersFunctioninterp_mode_to_str
(mode)
timm/data/transforms.py:75
↓ 2 callersFunctionis_scriptable
()
timm/models/layers/config.py:63
↓ 2 callersFunctionis_stem_deep
(stem_type)
timm/models/resnetv2.py:296
↓ 2 callersMethodload_pretrained
(self, checkpoint_path, prefix='resnet/')
timm/models/resnetv2.py:393
↓ 2 callersFunctionlog_snr_schedule_cosine_shifted
( t: torch.Tensor, image_d: float, noise_d: float, logsnr_min: float = -15, logsnr_max: fl
models/diffusion/continuous_time.py:34
↓ 2 callersFunctionmixup_target
(target, num_classes, lam=1., smoothing=0.0, device='cuda')
timm/data/mixup.py:22
↓ 2 callersFunctionmost_frequent_element
(lst)
data/nuScenes/descriptor_plus.py:192
↓ 2 callersFunctionmost_frequent_element
(lst)
data/nuScenes/descriptor.py:168
↓ 2 callersFunctionnorm_cdf
(x)
timm/models/layers/weight_init.py:11
↓ 2 callersFunctionone_hot
(x, num_classes, on_value=1., off_value=0., device='cuda')
timm/data/mixup.py:17
↓ 2 callersFunctionopt_n_threads
pointops/src/cuda_utils.h:15
↓ 2 callersFunctionoverlay_external_default_cfg
Overlay 'external_default_cfg' in kwargs on top of default_cfg arg.
timm/models/helpers.py:344
↓ 2 callersMethodp_sample
( self, x_t: torch.Tensor, step_t: torch.Tensor, step_s: torch.Tensor,
models/diffusion/continuous_time.py:243
↓ 2 callersFunctionpatch_device
(module)
models/CLIP/clip/clip.py:156
↓ 2 callersFunctionpatch_float
(module)
models/CLIP/clip/clip.py:180
↓ 2 callersFunctionpcd2voxel
(pcd)
eval/metric_utils.py:160
↓ 2 callersFunctionpoints_as_images
( points, scan_unfolding: bool = False, size=(64, 1024), fov = (3, -25), depth_range=
utils/common.py:1258
↓ 2 callersFunctionpreprocess
(batch, classifier_dropout=0.1, use_text=False, use_semantic=False)
train_frozen_scrg_stage1.py:435
↓ 2 callersFunctionpreprocess
(batch, classifier_dropout=0.1, use_text=False, use_semantic=False)
train_full_scrg.py:462
↓ 2 callersFunctionpreprocess
(batch, classifier_dropout=0.1, use_text=False, use_semantic=False)
train_full_scrg_uncondtional_KITTI360_sample.py:428
↓ 2 callersFunctionpreprocess
(batch, classifier_dropout=0.1, use_text=False, use_semantic=False)
train_frozen_scrg_stage2.py:465
↓ 2 callersFunctionpreprocess_pcd
(pcd, **kwargs)
eval/metric_utils.py:313
↓ 2 callersFunctionpreprocess_range
(pcd, **kwargs)
eval/metric_utils.py:320
↓ 2 callersFunctionprint_load_report
(load_info, model_name, weight_num, print_info=True)
utils/common.py:1565
↓ 2 callersFunctionprojection
(p, grad, perturb, delta: float, wd_ratio: float, eps: float)
timm/optim/adamp.py:25
↓ 2 callersFunctionread_nuscenes_infos_10sweeps
( split="train" )
data/nuScenes/descriptor_plus.py:728
↓ 2 callersFunctionread_nuscenes_infos_10sweeps
( split="train" )
data/nuScenes/descriptor.py:674
↓ 2 callersFunctionreduce_feat_size
(feat_size, stride=2)
timm/models/byobnet.py:1267
↓ 2 callersFunctionrel_logits_1d
Compute relative logits along one dimension As per: https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2 Originally from
timm/models/layers/bottleneck_attn.py:27
↓ 2 callersFunctionrel_logits_1d
Compute relative logits along one dimension As per: https://gist.github.com/aravindsrinivas/56359b79f0ce4449bcb04ab4b56a57a2 Originally from
timm/models/layers/halo_attn.py:29
↓ 2 callersMethodreset_classifier
(self, num_classes, global_pool='avg')
timm/models/dla.py:315
↓ 2 callersMethodresize_mat
(self, x, t: int)
timm/models/layers/non_local_attn.py:84
↓ 2 callersFunctionresnet26d
Constructs a ResNet-26-D model.
timm/models/resnet.py:746
↓ 2 callersFunctionresnet50d
Constructs a ResNet-50-D model.
timm/models/resnet.py:762
↓ 2 callersFunctionrot
(x)
timm/models/layers/attention_pool2d.py:20
↓ 2 callersFunctionscatter
(array, index, value)
utils/common.py:1253
↓ 2 callersFunctionsplit_model_name
(model_name)
timm/models/factory.py:7
↓ 2 callersFunctiontransform
(x, y, matrix)
timm/data/auto_augment.py:106
↓ 2 callersFunctionunitwise_norm
(x, norm_type=2.0)
timm/utils/agc.py:21
↓ 2 callersFunctionuniversal_scalling
(s_feat, s_factor=2 ** (-0.5))
models/T2LDM.py:313
↓ 2 callersMethodupdate_slow
(self, group)
timm/optim/lookahead.py:31
↓ 2 callersFunctionweights_num
(weights)
utils/common.py:1586
↓ 2 callersFunctionwindow_partition
Args: x: (B, H, W, C) window_size (int): window size Returns: windows: (num_windows*B, window_size, window_size, C)
timm/models/swin_transformer.py:88
↓ 1 callersMethod__init__
(self, model, decay=0.9999, device='', resume='')
timm/utils/model_ema.py:37
↓ 1 callersMethod__init__
(self, loader, mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEF
timm/data/loader.py:59
↓ 1 callersMethod__init__
(self, tf: tarfile.TarFile = None, ti: tarfile.TarInfo = None)
timm/data/parsers/parser_image_in_tar.py:33
↓ 1 callersMethod__init__
(self, block_args, num_classes=1000, in_chans=3, stem_size=16, num_features=1280, head_bias=True,
timm/models/mobilenetv3.py:92
↓ 1 callersMethod__init__
(self, in_chans=3, num_classes=1000, global_pool='avg', output_stride=32, initial_chs=16, fin
timm/models/rexnet.py:145
↓ 1 callersMethod__init__
(self, fn)
timm/models/convmixer.py:26
↓ 1 callersMethod__init__
(self, inplanes, planes, stride=1, downsample=None, cardinality=1, base_width=64, sk_kwargs=N
timm/models/sknet.py:49
↓ 1 callersMethod__init__
( self, cfg: List[Any], num_classes: int = 1000, in_chans: int = 3, ou
timm/models/vgg.py:83
↓ 1 callersMethod__init__
(self, block_args, num_classes=1000, num_features=1280, in_chans=3, stem_size=32, fix_stem=False,
timm/models/efficientnet.py:428
↓ 1 callersMethod__init__
(self, drop_prob=None)
timm/models/layers/drop.py:163
↓ 1 callersMethod__init__
(self, feat_size, dim_head, scale)
timm/models/layers/bottleneck_attn.py:60
↓ 1 callersMethod__init__
(self, kernel_size: int, stride=None, padding=0, ceil_mode=False, count_include_pad=True)
timm/models/layers/pool2d_same.py:24
↓ 1 callersMethod__init__
( self, channels, rd_ratio=1. / 16, rd_channels=None, rd_divisor=8, add_maxpool=False,
timm/models/layers/squeeze_excite.py:28
↓ 1 callersMethod__init__
(self, in_channels, out_channels, kernel_size=3, stride=1, dilation=1, padding='', bias=False,
timm/models/layers/separable_conv.py:51
↓ 1 callersMethod__init__
(self, num_features, apply_act=True, momentum=0.1, eps=1e-5, drop_block=None)
timm/models/layers/evo_norm.py:17
↓ 1 callersMethod__init__
(self, num_channels, num_groups, eps=1e-5, affine=True)
timm/models/layers/norm.py:9
↓ 1 callersMethod__init__
( self, channels=None, kernel_size=3, gamma=2, beta=1, act_layer=None, gate_layer='sigmoid',
timm/models/layers/eca.py:60
↓ 1 callersMethod__init__
(self, num_channels, num_groups, eps=1e-5, affine=True, apply_act=True, act_layer=nn.ReLU, in
timm/models/layers/norm_act.py:71
↓ 1 callersMethod__init__
(self, in_channels, out_channels=None, kernel_size=3, stride=1, padding=None, dilation=1, gro
timm/models/layers/split_attn.py:36
↓ 1 callersMethod__init__
( self, dim, dim_out=None, feat_size=None, stride=1, num_heads=8, dim_head=None, block_size=8, hal
timm/models/layers/halo_attn.py:124
↓ 1 callersMethod__init__
Selective Kernel Convolution Module As described in Selective Kernel Networks (https://arxiv.org/abs/1903.06586) with some modifications.
timm/models/layers/selective_kernel.py:51
↓ 1 callersMethod__init__
(self)
timm/loss/cross_entropy.py:31
↓ 1 callersMethod__init__
(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disable_torch_grad_focal_loss=False)
timm/loss/asymmetric_loss.py:6
↓ 1 callersMethod__iter__
(self)
timm/data/loader.py:81
↓ 1 callersMethod_apply_basic
(self, img, mixing_weights, m)
timm/data/auto_augment.py:784
↓ 1 callersMethod_apply_blended
(self, img, mixing_weights, m)
timm/data/auto_augment.py:768
↓ 1 callersMethod_apply_noise
(self, epoch)
timm/scheduler/plateau_lr.py:93
↓ 1 callersMethod_approx_sq_grad
(self, exp_avg_sq_row, exp_avg_sq_col)
timm/optim/adafactor.py:74
↓ 1 callersFunction_at_least_x_are_equal
At least `x` of `a` and `b` `Tensors` are equal.
timm/data/tf_preprocessing.py:84
↓ 1 callersFunction_block_cfg
(width_mult=1.0, depth_mult=1.0, initial_chs=16, final_chs=180, se_ratio=0., ch_div=1)
timm/models/rexnet.py:99
↓ 1 callersFunction_build_blocks
( block_cfg, prev_chs, width_mult, ch_div=1, act_layer='swish', dw_act_layer='relu6', drop_path_rate=0
timm/models/rexnet.py:119
↓ 1 callersMethod_build_pe
(self, H, W, device, dtype)
models/T2LDM.py:184
↓ 1 callersMethod_build_tf_graph
(self)
timm/data/tf_preprocessing.py:214
↓ 1 callersMethod_calc_blended_weights
(self, ws, m)
timm/data/auto_augment.py:758
↓ 1 callersFunction_cfg_to_stage_args
(cfg, curr_stride=2, output_stride=32, drop_path_rate=0.)
timm/models/cspnet.py:303
↓ 1 callersMethod_check_branches
(self, num_branches, blocks, num_blocks, num_inchannels, num_channels)
timm/models/hrnet.py:406
↓ 1 callersMethod_cleanup_checkpoints
(self, trim=0)
timm/utils/checkpoint_saver.py:118
↓ 1 callersFunction_compute_num_patches
(img_size, patches)
timm/models/crossvit.py:254
↓ 1 callersFunction_create_gluon_xception
(variant, pretrained=False, **kwargs)
timm/models/gluon_xception.py:234
↓ 1 callersMethod_create_hook
(self, hook_fn)
timm/utils/model.py:71
↓ 1 callersFunction_create_hub_entrypoint
(model)
models/CLIP/hubconf.py:10
↓ 1 callersFunction_create_inception_v4
(variant, pretrained=False, **kwargs)
timm/models/inception_v4.py:306
↓ 1 callersFunction_create_nasnet
(variant, pretrained=False, **kwargs)
timm/models/nasnet.py:554
↓ 1 callersFunction_create_pnasnet
(variant, pretrained=False, **kwargs)
timm/models/pnasnet.py:335
↓ 1 callersFunction_decode_and_random_crop
Make a random crop of image_size.
timm/data/tf_preprocessing.py:91
↓ 1 callersFunction_decode_block_str
Decode block definition string Gets a list of block arg (dicts) through a string notation of arguments. E.g. ir_r2_k3_s2_e1_i32_o16_se0.25_n
timm/models/efficientnet_builder.py:76
↓ 1 callersFunction_download
(url: str, root: str)
models/CLIP/clip/clip.py:43
↓ 1 callersFunction_extract_tarinfo
(tf: tarfile.TarFile, parent_info: Dict, extensions=IMG_EXTENSIONS)
timm/data/parsers/parser_image_in_tar.py:42
↓ 1 callersFunction_flip
Random horizontal image flip.
timm/data/tf_preprocessing.py:134
↓ 1 callersMethod_forward
(self, x)
timm/models/inception_v3.py:69
↓ 1 callersMethod_forward
(self, x)
timm/models/inception_v3.py:102
↓ 1 callersMethod_forward
(self, x)
timm/models/inception_v3.py:140
↓ 1 callersMethod_forward
(self, x)
timm/models/inception_v3.py:178
↓ 1 callersMethod_forward
(self, x)
timm/models/inception_v3.py:215
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