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Functions269 in github.com/ansleliu/LightNetPlusPlus

⨍ Functions 269◇ Types & classes 87
Methodforward
(self, _input)
modules/aspp.py:210
Methodforward
(self, x)
modules/shuffle.py:78
Methodforward
(self, x)
modules/shuffle.py:139
Methodforward
(self, x)
modules/residual.py:80
Methodforward
(self, data, rois, offset)
modules/deformable/modules/deform_pool.py:27
Methodforward
(self, data, rois)
modules/deformable/modules/deform_pool.py:66
Methodforward
(self, data, rois)
modules/deformable/modules/deform_pool.py:128
Methodforward
(self, input, offset)
modules/deformable/modules/deform_conv.py:53
Methodforward
(self, input, offset, mask)
modules/deformable/modules/deform_conv.py:100
Methodforward
(self, input)
modules/deformable/modules/deform_conv.py:136
Methodforward
(ctx, data, rois, offset, spatial_scale,
modules/deformable/functions/deform_pool.py:10
Methodforward
(ctx, input, offset, weight, stride=1,
modules/deformable/functions/deform_conv.py:11
Methodforward
(ctx, input, offset, mask, weight,
modules/deformable/functions/deform_conv.py:111
Methodforward
(self, x)
modules/inplace_abn/iabn.py:61
Methodforward
(self, x)
modules/inplace_abn/iabn.py:107
Methodforward
(self, x)
modules/inplace_abn/iabn.py:117
Methodforward
(cls, ctx, x, weight, bias, running_mean, running_var, training=True, momentum=0.1, eps=1e-05,
modules/inplace_abn/functions.py:145
Methodforward
(ctx, num_inputs, *inputs)
utils/parallel.py:36
Methodforward
(ctx, *inputs)
utils/parallel.py:59
Methodforward
(self, inputs, *targets, **kwargs)
utils/parallel.py:127
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:43
Methodforward
(self, predictions, targets)
utils/losses.py:120
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:218
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:322
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets
utils/losses.py:428
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:459
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:572
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:644
Methodforward
:param predictions: <torch.FloatTensor> Network Predictions of size [N, C, H, W], where C = number of classes :param targets: <torch
utils/losses.py:718
Methodforward
(self, x)
models/shufflenetv2plus.py:131
Methodforward
(self, x)
models/mixnetseg.py:59
Methodforward
(self, x)
models/mixnetseg.py:76
Methodforward
(self, x)
models/mixnetseg.py:98
Methodforward
(self, x)
models/mixnetseg.py:119
Methodforward
(self, x)
models/mixnetseg.py:148
Methodforward
(self, x)
models/mixnetseg.py:202
Methodforward
(self, x)
models/mixnetseg.py:257
Methodforward
(self, inputs)
models/mixnetseg.py:317
Methodforward
(self, feat1, feat2, feat3, feat4, feat5)
models/mixnetseg.py:357
Methodforward
(self, x)
models/mixnetseg.py:517
Methodforward
(self, x)
models/mobilenetv2plus.py:134
Functionfreeze_bn
(m, freeze_bn_affine=False)
utils/utils.py:90
Methodgather
(self, outputs, output_device)
utils/parallel.py:98
Functiongauss_kernel
(kernel_size, sigma)
modules/usm.py:9
Functionget_dims
modules/inplace_abn/src/inplace_abn.h:39
Methodget_input_array
(self, m, i, o)
netviz/feat_viz.py:18
Methodget_output_array
(self, m, i, o)
netviz/feat_viz.py:27
Methodget_scores
Returns score about: - overall accuracy - mean accuracy - mean IU - fwavacc For refe
utils/metrics.py:88
Functioninit_weights
(net, init_type='normal')
utils/utils.py:65
Functionleaky_relu_backward
modules/inplace_abn/src/inplace_abn.cpp:62
Functionleaky_relu_forward
modules/inplace_abn/src/inplace_abn.cpp:58
Functionmean_var
modules/inplace_abn/src/inplace_abn.cpp:7
Functionmodulated_deform_conv_cuda_backward
modules/deformable/src/deform_conv_cuda.cpp:566
Functionmodulated_deform_conv_cuda_forward
modules/deformable/src/deform_conv_cuda.cpp:486
Functionnew_replicate
(module, device_ids)
utils/parallel.py:257
Methodout_channels
(self)
modules/dense.py:31
Functionpatch_replication_callback
Monkey-patch an existing `DataParallel` object. Add the replication callback. Useful when you have customized `DataParallel` implementation.
utils/parallel.py:238
Functionreduce
modules/inplace_abn/src/inplace_abn.h:55
Methodreset
(self)
utils/metrics.py:26
Methodreset
Reset Confusion Matrix :return:
utils/metrics.py:81
Methodstep
Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model
utils/adabound.py:50
Functionstep_topk_scheduler
(init_topk1, init_topk2, epoch, step_size, limit=(384, 384), ratio=0.875)
utils/utils.py:79
Methodtrain
(self, mode=True, freeze_bn=False, freeze_bn_affine=False)
models/shufflenetv2plus.py:117
Methodtrain
(self, mode=True, freeze_bn=False, freeze_bn_affine=False)
models/mobilenetv2plus.py:120
Methodupdate
Compute Confusion Matrix For reference, please see: https://en.wikipedia.org/wiki/Confusion_matrix :param label_gts: <np.nda
utils/metrics.py:69
Functionweights_init_kaiming
(m)
utils/utils.py:41
Functionweights_init_normal
(m)
utils/utils.py:17
Functionweights_init_orthogonal
(m)
utils/utils.py:53
Functionweights_init_xavier
(m)
utils/utils.py:29
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