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Functions50 in github.com/ChinaYi/ASFormer

⨍ Functions 50 ◇ Types & classes 14

↓ 9 callersMethod__init__

(self, num_layers, r1, r2, num_f_maps, input_dim, num_classes, channel_masking_rate, att_type, alpha)

↓ 4 callersFunctionget_labels_start_end_time

(frame_wise_labels, bg_class=["background"])

↓ 3 callersMethodhas_next

batch_gen.py:25

↓ 3 callersMethodnext_batch

(self, batch_size, if_warp=False)

batch_gen.py:86

↓ 3 callersMethodread_data

(self, vid_list_file)

batch_gen.py:30

↓ 3 callersFunctionread_file

↓ 3 callersMethodreset

batch_gen.py:21

↓ 3 callersMethodscalar_dot_att

scalar dot attention. :param proj_query: shape of (B, C, L) => (Batch_Size, Feature_Dimension, Length) :param proj_key: shape

↓ 2 callersFunctionfunc_eval

(dataset, recog_path, file_list)

↓ 2 callersMethodmy_shuffle

batch_gen.py:39

↓ 2 callersMethodsample

(self, batchsize=1)

grid_sampler.py:40

↓ 2 callersMethodtrain

(self, save_dir, batch_gen, num_epochs, batch_size, learning_rate, batch_gen_tst=None)

↓ 1 callersMethod__init__

(self, N_grid, low=1, high=5)

grid_sampler.py:32

↓ 1 callersMethod_block_wise_self_att

(self, q,k,v, mask)

↓ 1 callersMethod_normal_self_att

(self,q,k,v, mask)

↓ 1 callersMethod_sliding_window_self_att

(self, q,k,v, mask)

↓ 1 callersMethodconstruct_window_mask

construct window mask of shape (1, l, l + l//2 + l//2), used for sliding window self attention

↓ 1 callersFunctionedit_score

(recognized, ground_truth, norm=True, bg_class=["background"])

↓ 1 callersFunctionexponential_descrease

(idx_decoder, p=3)

↓ 1 callersFunctionf_score

(recognized, ground_truth, overlap, bg_class=["background"])

↓ 1 callersFunctionlevenstein

(p, y, norm=False)

↓ 1 callersFunctionmain

↓ 1 callersMethodpredict

(self, model_dir, results_dir, features_path, batch_gen_tst, epoch, actions_dict, sample_rate)

↓ 1 callersFunctionsegment_bars_with_confidence

(save_path, confidence, *labels)

↓ 1 callersMethodtest

(self, batch_gen_tst, epoch)

↓ 1 callersMethodwarp_video

:param batch_input_tensor: (bs, C_in, L_in) :param batch_target_tensor: (bs, L_in) :return: warped input and target

batch_gen.py:50

grid_sampler.py:12

(self, q_dim, k_dim, v_dim, r1, r2, r3, bl, stage, att_type)

(self, q_dim, k_dim, v_dim, r1, r2, r3, bl, stage, att_type, num_head)

(self, dilation, in_channels, out_channels)

(self, in_channels, out_channels)

(self, dilation, in_channels, out_channels, r1, r2, att_type, stage, alpha)

(self, d_model, max_len=10000)

(self, num_layers, r1, r2, num_f_maps, input_dim, num_classes, att_type, alpha)

(self, num_decoders, num_layers, r1, r2, num_f_maps, input_dim, num_classes, channel_masking_rate)

(self, num_layers, r1, r2, num_f_maps, input_dim, num_classes, channel_masking_rate)

(self, num_classes, actions_dict, gt_path, features_path, sample_rate)

batch_gen.py:11

:type&shape x: (cuda.)FloatTensor, (N, D, T) :type&shape grid: (cuda.)FloatTensor, (N, T, 2) :type&mode: bilinear or nearest

grid_sampler.py:15

(self, x1, x2, mask)

(self, x1, x2, mask)

(self, x, f, mask)

:param x: (N, C, L) :param mask: :return:

(self, x, fencoder, mask)

(self, x, mask)

merge two batch generator. I.E BatchGenerator a; BatchGenerator b; a.merge(b, suffix='@1') :param bg:

batch_gen.py:68

Functionsegment_bars

(save_path, *labels)