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Functions153 in github.com/XiaLiPKU/EMANet

↓ 11 callersMethodput
(self, result)
bn_lib/nn/modules/comm.py:26
↓ 10 callersMethodassertTensorClose
(self, a, b, atol=1e-3, rtol=1e-3)
bn_lib/nn/modules/unittest.py:24
↓ 8 callersMethodget
(self)
bn_lib/nn/modules/comm.py:32
↓ 6 callersFunction_find_bn
(module)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:30
↓ 6 callersMethod_make_layer
(self, block, planes, blocks, stride=1, dilation=1, grids=None)
network.py:99
↓ 5 callersMethod__init__
(self, c, k, stage_num=3)
network.py:194
↓ 5 callersMethod_checkBatchNormResult
Check the forward and backward for the customized batch normalization.
bn_lib/nn/modules/tests/test_sync_batchnorm.py:44
↓ 5 callersFunction_unsqueeze_ft
add new dementions at the front and the tail
bn_lib/nn/modules/batchnorm.py:29
↓ 3 callersFunctionget_params
(model, key)
train.py:22
↓ 3 callersMethodsave_checkpoints
(self, name)
train.py:107
↓ 2 callersMethod_check_input_dim
(self, input)
bn_lib/nn/modules/batchnorm.py:189
↓ 2 callersMethod_l2norm
Normlize the inp tensor with l2-norm. Returns a tensor where each sub-tensor of input along the given dim is normalized such that th
network.py:250
↓ 2 callersMethod_process_next_batch
(self, batch)
bn_lib/utils/data/dataloader.py:299
↓ 2 callersMethod_put_indices
(self)
bn_lib/utils/data/dataloader.py:290
↓ 2 callersMethod_shutdown_workers
(self)
bn_lib/utils/data/dataloader.py:314
↓ 2 callersFunction_sum_ft
sum over the first and last dimention
bn_lib/nn/modules/batchnorm.py:24
↓ 2 callersFunctionas_numpy
(v)
bn_lib/nn/modules/unittest.py:17
↓ 2 callersFunctionasync_copy_to
(obj, dev, main_stream=None)
bn_lib/nn/parallel/data_parallel.py:12
↓ 2 callersFunctioncal_scores
(hist)
metric.py:41
↓ 2 callersFunctionensure_dir
(dir_path)
train.py:39
↓ 2 callersFunctionexecute_replication_callbacks
Execute an replication callback `__data_parallel_replicate__` on each module created by original replication. The callback will be invoked w
bn_lib/nn/modules/replicate.py:27
↓ 2 callersFunctionfetch
(image_path, label_path=None)
dataset.py:15
↓ 2 callersFunctionhandy_var
(a, unbias=True)
bn_lib/nn/modules/tests/test_numeric_batchnorm.py:18
↓ 2 callersFunctionpin_memory_batch
(batch)
bn_lib/utils/data/dataloader.py:142
↓ 1 callersMethod__data_parallel_replicate__
(self, ctx, copy_id)
bn_lib/nn/modules/batchnorm.py:83
↓ 1 callersMethod__init__
(self, data_root=settings.DATA_ROOT, split='val')
dataset.py:127
↓ 1 callersMethod__init__
(self, dataset, indices)
bn_lib/utils/data/dataset.py:94
↓ 1 callersFunction_async_copy_stream
(inputs, device_ids)
bn_lib/nn/parallel/data_parallel.py:83
↓ 1 callersMethod_compute_mean_std
Compute the mean and standard-deviation with sum and square-sum. This method also maintains the moving average on the master device.
bn_lib/nn/modules/batchnorm.py:118
↓ 1 callersMethod_get_batch
(self)
bn_lib/utils/data/dataloader.py:249
↓ 1 callersMethod_get_item
(self, idx)
dataset.py:104
↓ 1 callersFunction_get_stream
Gets a background stream for copying between CPU and GPU
bn_lib/nn/parallel/data_parallel.py:105
↓ 1 callersFunction_set_SIGCHLD_handler
()
bn_lib/utils/data/dataloader.py:160
↓ 1 callersMethod_syncParameters
(self, bn1, bn2)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:37
↓ 1 callersFunctioncrop
(image, label=None)
dataset.py:68
↓ 1 callersMethodcumsum
(sequence)
bn_lib/utils/data/dataset.py:61
↓ 1 callersFunctiondict_gather
Gathers variables from different GPUs on a specified device (-1 means the CPU), with dictionary support.
bn_lib/nn/parallel/data_parallel.py:28
↓ 1 callersFunctionfast_hist
(label_true, label_pred)
metric.py:6
↓ 1 callersFunctionflip
(image, label=None)
dataset.py:80
↓ 1 callersFunctiongather_map
(outputs)
bn_lib/nn/parallel/data_parallel.py:33
↓ 1 callersMethodinf_batch
(self, image, label)
eval.py:46
↓ 1 callersMethodload_checkpoints
(self, name)
eval.py:34
↓ 1 callersMethodload_checkpoints
(self, name)
train.py:115
↓ 1 callersFunctionmain
(ckp_name='final.pth')
eval.py:56
↓ 1 callersFunctionmain
(ckp_name='latest.pth')
train.py:145
↓ 1 callersFunctionpad
(image, label=None)
dataset.py:42
↓ 1 callersFunctionpad_inf
(image, label=None)
dataset.py:55
↓ 1 callersFunctionpatch_replication_callback
Monkey-patch an existing `DataParallel` object. Add the replication callback. Useful when you have customized `DataParallel` implementation.
bn_lib/nn/modules/replicate.py:70
↓ 1 callersFunctionpoly_lr_scheduler
(opt, init_lr, iter, lr_decay_iter, max_iter, power)
train.py:44
↓ 1 callersMethodregister_slave
Register an slave device. Args: identifier: an identifier, usually is the device id. Returns: a `SlavePipe` obj
bn_lib/nn/modules/comm.py:78
↓ 1 callersFunctionresnet
(n_layers, stride)
network.py:149
↓ 1 callersMethodrun_master
Main entry for the master device in each forward pass. The messages were first collected from each devices (including the master devi
bn_lib/nn/modules/comm.py:96
↓ 1 callersMethodrun_slave
(self, msg)
bn_lib/nn/modules/comm.py:49
↓ 1 callersFunctionscale
(image, label=None)
dataset.py:33
↓ 1 callersFunctiontest_dt
()
dataset.py:141
↓ 1 callersFunctiontest_net
()
network.py:321
↓ 1 callersMethodtrain_batch
(self, image, label)
train.py:128
↓ 1 callersMethodwrite
(self, out)
train.py:96
Method__add__
(self, other)
bn_lib/utils/data/dataset.py:22
Method__del__
(self)
bn_lib/utils/data/dataloader.py:333
Method__getitem__
(self, idx)
dataset.py:100
Method__getitem__
(self, index)
bn_lib/utils/data/dataset.py:16
Method__getitem__
(self, index)
bn_lib/utils/data/dataset.py:42
Method__getitem__
(self, idx)
bn_lib/utils/data/dataset.py:78
Method__getitem__
(self, idx)
bn_lib/utils/data/dataset.py:98
Method__getstate__
(self)
bn_lib/utils/data/dataloader.py:306
Method__init__
(self, inplanes, planes, stride=1, dilation=1, downsample=None, previous_dilation=1)
network.py:19
Method__init__
(self, block, layers, num_classes=1000, stride=8)
network.py:58
Method__init__
(self, c_in, c_out, kernel_size, stride, padding, dilation)
network.py:171
Method__init__
(self, n_classes, n_layers)
network.py:268
Method__init__
(self, weight=None, reduction='none', ignore_index=-1)
network.py:311
Method__init__
(self, dt_split)
eval.py:21
Method__init__
(self, dt_split)
train.py:54
Method__init__
(self, data_root, split)
dataset.py:89
Method__init__
(self, data_root=settings.DATA_ROOT, split='trainaug')
dataset.py:109
Method__init__
(self, exc_info)
bn_lib/utils/data/dataloader.py:25
Method__init__
(self, loader)
bn_lib/utils/data/dataloader.py:188
Method__init__
(self, dataset, batch_size=1, shuffle=False, sampler=None, batch_sampler=None, num_workers=0,
bn_lib/utils/data/dataloader.py:380
Method__init__
(self, dataset, num_replicas=None, rank=None)
bn_lib/utils/data/distributed.py:25
Method__init__
(self, data_tensor, target_tensor)
bn_lib/utils/data/dataset.py:37
Method__init__
(self, datasets)
bn_lib/utils/data/dataset.py:69
Method__init__
(self, data_source)
bn_lib/utils/data/sampler.py:12
Method__init__
(self, data_source)
bn_lib/utils/data/sampler.py:29
Method__init__
(self, data_source)
bn_lib/utils/data/sampler.py:46
Method__init__
(self, indices)
bn_lib/utils/data/sampler.py:63
Method__init__
(self, weights, num_samples, replacement=True)
bn_lib/utils/data/sampler.py:84
Method__init__
(self, sampler, batch_size, drop_last)
bn_lib/utils/data/sampler.py:112
Method__init__
(self)
bn_lib/nn/modules/comm.py:21
Method__init__
Args: master_callback: a callback to be invoked after having collected messages from slave devices.
bn_lib/nn/modules/comm.py:67
Method__init__
(self, num_features, eps=1e-5, momentum=3e-4, affine=True)
bn_lib/nn/modules/batchnorm.py:39
Method__iter__
(self)
bn_lib/utils/data/dataloader.py:287
Method__iter__
(self)
bn_lib/utils/data/dataloader.py:418
Method__iter__
(self)
bn_lib/utils/data/distributed.py:37
Method__iter__
(self)
bn_lib/utils/data/sampler.py:15
Method__iter__
(self)
bn_lib/utils/data/sampler.py:32
Method__iter__
(self)
bn_lib/utils/data/sampler.py:49
Method__iter__
(self)
bn_lib/utils/data/sampler.py:66
Method__iter__
(self)
bn_lib/utils/data/sampler.py:89
Method__iter__
(self)
bn_lib/utils/data/sampler.py:117
Method__len__
(self)
dataset.py:97
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