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Functions408 in github.com/Shank2358/TS-Conv

⨍ Functions 408◇ Types & classes 100
Method__init__
( self, in_channels, out_channels, kernel_size, stride, paddin
lib/DCNv2/dcn_v2_amp.py:279
Method__init__
( self, spatial_scale, pooled_size, output_dim, no_trans, grou
lib/DCNv2/dcn_v2_amp.py:550
Method__init__
( self, spatial_scale, pooled_size, output_dim, no_trans, grou
lib/DCNv2/dcn_v2_amp.py:591
Method__init__
(self, init_weights=True, inputsize=int(cfg.TRAIN["TRAIN_IMG_SIZE"]), weight_path=None)
model/TSConv.py:14
Method__init__
(self, pre_weight=None)
model/backbones/darknet53.py:10
Method__init__
( self, inplanes: int, planes: int, stride: int = 1, downsample: Optio
model/backbones/model_resnet.py:60
Method__init__
( self, inplanes: int, planes: int, stride: int = 1, downsample: Optio
model/backbones/model_resnet.py:115
Method__init__
(self, inp, oup, stride, expand_ratio)
model/backbones/mobilenetv2.py:45
Method__init__
(self, num_classes=1000, width_mult=1.)
model/backbones/mobilenetv2.py:85
Method__init__
(self, submodule, extracted_layers)
model/backbones/mobilenetv2.py:142
Method__init__
(self, n)
model/backbones/resnet.py:18
Method__init__
The function takes in a backbone and a number of channels and returns a body with the layers of the backbone Parameters -----
model/backbones/resnet.py:50
Method__init__
(self, filters_in, nC, stride)
model/head/head.py:172
Method__init__
(self, channel)
model/layers/attention_blocks.py:35
Method__init__
(self,inplanes,ratio,pooling_type='att', fusion_types=('channel_add', ))
model/layers/attention_blocks.py:67
Method__init__
(self, inplanes, planes, use_scale=False, groups=None)
model/layers/attention_blocks.py:146
Method__init__
(self, depth=512)
model/layers/multiscale_fusion_blocks.py:24
Method__init__
(self, in_channel=1280, depth=512)
model/layers/multiscale_fusion_blocks.py:36
Method__init__
(self, level, vis=False)
model/layers/multiscale_fusion_blocks.py:54
Method__init__
(self, in_ch, out_ch, n_anchors)
model/layers/multiscale_fusion_blocks.py:115
Method__init__
(self, in_channels, out_channels, r=16)
model/layers/multiscale_fusion_blocks.py:128
Method__init__
(self, channel_in, alpha=0.5, sigma=4)
model/layers/np_attention_blocks.py:70
Method__init__
(self, channel_in, alpha=0.5, sigma=4)
model/layers/np_attention_blocks.py:86
Method__init__
(self, inplanes, planes, use_scale=False, groups=None)
model/layers/np_attention_blocks.py:101
Method__init__
(self, inplanes, planes, use_scale=False, groups=None)
model/layers/np_attention_blocks.py:165
Method__init__
(self, inplanes, planes, use_scale=False, groups=None)
model/layers/np_attention_blocks.py:228
Method__init__
(self, filters_in, filters_out, filters_medium, norm="bn", activate="leaky")
model/layers/conv_blocks.py:6
Method__init__
(self, filters_in)
model/layers/conv_blocks.py:35
Method__init__
(self, inp, oup, stride, expand_ratio)
model/layers/conv_blocks.py:50
Method__init__
(self, c1, k=3)
model/layers/activations.py:51
Method__init__
(self, filters_in)
model/layers/msr_blocks.py:34
Method__init__
(self, filters_in)
model/layers/msr_blocks.py:60
Method__init__
(self, filters_in, filters_out, kernel_size, stride, pad, groups=1, dila=1, norm=None, activate=None)
model/layers/convolutions.py:23
Method__init__
(self, filters_in, filters_out, kernel_size, stride, pad, groups=1, norm=None, activate=None)
model/layers/convolutions.py:64
Method__init__
(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bia
model/layers/convolutions.py:122
Method__init__
(self, filters_in, filters_out, kernel_size, stride=1, pad=0, dila=1, groups=1, bias=True, num_experts=1, norm
model/layers/convolutions.py:170
Method__init__
(self, scale_factor=1, mode='nearest')
model/neck/neck.py:13
Method__init__
(self)
model/neck/neck.py:23
Method__init__
(self, gamma=2.0, alpha=1.0, reduction="mean")
model/loss/loss.py:9
Method__init__
(self)
model/loss/loss.py:20
Method__init__
(self, anno_file_name, img_size=int(cfg.TRAIN["TRAIN_IMG_SIZE"]))
dataloadR/datasetsv2.py:12
Method__init__
( self, sampler, batch_size, drop_last, multiscale_step=None, img_sizes=None )
dataloadR/batch_sampler.py:7
Method__iter__
(self)
trainv2.py:52
Method__iter__
(self)
trainv2.py:61
Method__iter__
(self)
batch_sampler.py:36
Method__iter__
(self)
dataloadR/batch_sampler.py:36
Method__len__
(self)
trainv2.py:49
Method__len__
(self)
datasetsv2.py:21
Method__len__
(self)
batch_sampler.py:53
Method__len__
(self)
dataloadR/datasetsv2.py:21
Method__len__
(self)
dataloadR/batch_sampler.py:53
Method__repr__
(self)
utils/mics.py:302
Method__save_model_weights_best
(self, epoch)
trainv2.py:231
Method__str__
(self)
utils/mics.py:79
Method__str__
(self)
utils/mics.py:178
Method_load_from_state_dict
( self, state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs )
model/backbones/resnet.py:25
Functionaccuracy
Computes the precision@k for the specified values of k
utils/mics.py:432
Methodadd_meter
(self, name, meter)
utils/mics.py:190
Functionall_gather
Run all_gather on arbitrary picklable data (not necessarily tensors) Args: data: any picklable object Returns: list[data]
utils/mics.py:88
Methodavg
(self)
utils/mics.py:63
Methodbackward
(ctx, grad_output)
lib/DCNv2/dcn_v2_onnx.py:65
Methodbackward
(ctx, grad_output)
lib/DCNv2/dcn_v2_onnx.py:204
Methodbackward
(ctx, grad_output)
lib/DCNv2/dcn_v2.py:238
Methodbackward
(ctx, grad_output)
lib/DCNv2/dcn_v2_amp.py:73
Methodbackward
(ctx, grad_output)
lib/DCNv2/dcn_v2_amp.py:507
Methodbackward
(ctx, grad_output)
model/layers/activations.py:23
Methodbackward
(ctx, grad_output)
model/layers/activations.py:42
Functionbboxes_iou
(bboxes_a, bboxes_b, xyxy=True)
utils/utils_coco.py:101
Functionbox2label
(box, info_img)
utils/utils_coco.py:142
Functioncheck_gradient_dconv
()
lib/DCNv2/testcuda.py:69
Functioncheck_gradient_dpooling
()
lib/DCNv2/testcuda.py:134
Functioncheck_pooling_zero_offset
()
lib/DCNv2/testcuda.py:100
Functioncheck_zero_offset
()
lib/DCNv2/testcuda.py:32
Functioncollate_fn
(batch)
utils/mics.py:268
Functiondcn_v2_backward
lib/DCNv2/src/dcn_v2.h:48
Functiondcn_v2_forward
lib/DCNv2/src/dcn_v2.h:9
Functiondcn_v2_psroi_pooling_backward
lib/DCNv2/src/dcn_v2.h:140
Functiondcn_v2_psroi_pooling_forward
lib/DCNv2/src/dcn_v2.h:94
Methoddecompose
(self)
utils/mics.py:299
Functionexample_dpooling
()
lib/DCNv2/testcuda.py:183
Functionexample_mdpooling
()
lib/DCNv2/testcuda.py:226
Methodforward
(ctx, input, offset_mask, weight, bias, stride, padding, dilation, deformable_groups)
lib/DCNv2/dcn_v2_onnx.py:33
Methodforward
(self, input, offset, mask)
lib/DCNv2/dcn_v2_onnx.py:111
Methodforward
(self, input)
lib/DCNv2/dcn_v2_onnx.py:146
Methodforward
(ctx, input, rois, offset, spatial_scale, pooled_size, output_
lib/DCNv2/dcn_v2_onnx.py:175
Methodforward
(self, input, rois, offset)
lib/DCNv2/dcn_v2_onnx.py:249
Methodforward
(self, input, rois)
lib/DCNv2/dcn_v2_onnx.py:300
Methodforward
( ctx, input, offset, mask, weight, bias, stride, padding, dilation, deformable_groups )
lib/DCNv2/dcn_v2.py:17
Methodforward
(self, input, offset, mask)
lib/DCNv2/dcn_v2.py:128
Methodforward
(self, input)
lib/DCNv2/dcn_v2.py:177
Methodforward
( ctx, input, rois, offset, spatial_scale, pooled_size,
lib/DCNv2/dcn_v2.py:197
Methodforward
(self, input, rois, offset)
lib/DCNv2/dcn_v2.py:284
Methodforward
(self, input, rois)
lib/DCNv2/dcn_v2.py:342
Methodforward
( ctx, input, offset, mask, weight, bias, stride,
lib/DCNv2/dcn_v2_amp.py:25
Methodforward
(self, input, offset, mask)
lib/DCNv2/dcn_v2_amp.py:161
Methodforward
(self, input, offset, mask)
lib/DCNv2/dcn_v2_amp.py:219
Methodforward
(self, x)
lib/DCNv2/dcn_v2_amp.py:270
Methodforward
(self, input, offset, mask, w_c8)
lib/DCNv2/dcn_v2_amp.py:318
Methodforward
(self, input)
lib/DCNv2/dcn_v2_amp.py:438
Methodforward
( ctx, input, rois, offset, spatial_scale, pooled_size,
lib/DCNv2/dcn_v2_amp.py:458
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