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Functions153 in github.com/XiaLiPKU/EMANet

⨍ Functions 153◇ Types & classes 39
Method__len__
(self)
bn_lib/utils/data/dataloader.py:246
Method__len__
(self)
bn_lib/utils/data/dataloader.py:421
Method__len__
(self)
bn_lib/utils/data/distributed.py:54
Method__len__
(self)
bn_lib/utils/data/dataset.py:19
Method__len__
(self)
bn_lib/utils/data/dataset.py:45
Method__len__
(self)
bn_lib/utils/data/dataset.py:75
Method__len__
(self)
bn_lib/utils/data/dataset.py:101
Method__len__
(self)
bn_lib/utils/data/sampler.py:18
Method__len__
(self)
bn_lib/utils/data/sampler.py:35
Method__len__
(self)
bn_lib/utils/data/sampler.py:52
Method__len__
(self)
bn_lib/utils/data/sampler.py:69
Method__len__
(self)
bn_lib/utils/data/sampler.py:92
Method__len__
(self)
bn_lib/utils/data/sampler.py:127
Method__next__
(self)
bn_lib/utils/data/dataloader.py:258
Method_add_weighted
return *dest* by `dest := dest*alpha + delta*beta + bias`
bn_lib/nn/modules/batchnorm.py:114
Function_async_copy
(inputs, device_ids)
bn_lib/nn/parallel/data_parallel.py:70
Method_check_input_dim
(self, input)
bn_lib/nn/modules/batchnorm.py:252
Method_check_input_dim
(self, input)
bn_lib/nn/modules/batchnorm.py:316
Method_data_parallel_master
Reduce the sum and square-sum, compute the statistics, and broadcast it.
bn_lib/nn/modules/batchnorm.py:93
Method_get_item
(self, image_id)
dataset.py:112
Method_get_item
(self, image_id)
dataset.py:130
Function_worker_loop
(dataset, index_queue, data_queue, collate_fn, seed, init_fn, worker_id)
bn_lib/utils/data/dataloader.py:34
Function_worker_manager_loop
(in_queue, out_queue, done_event, pin_memory, device_id)
bn_lib/utils/data/dataloader.py:64
Functionas_numpy
(obj)
bn_lib/utils/th.py:18
Functionas_variable
(obj)
bn_lib/utils/th.py:8
Functioncal_scores
(hist)
bn_lib/metric.py:41
Methodcummulative_sizes
(self)
bn_lib/utils/data/dataset.py:87
Functiondefault_collate
Puts each data field into a tensor with outer dimension batch size
bn_lib/utils/data/dataloader.py:101
Functionfast_hist
(label_true, label_pred)
bn_lib/metric.py:6
Methodforward
(self, x)
network.py:34
Methodforward
(self, x)
network.py:131
Methodforward
(self, x)
network.py:179
Methodforward
(self, x)
network.py:218
Methodforward
(self, img, lbl=None, size=None)
network.py:292
Methodforward
(self, inputs, targets)
network.py:316
Methodforward
(self, input)
bn_lib/nn/modules/batchnorm.py:51
Methodgather
(self, outputs, output_device)
bn_lib/nn/parallel/data_parallel.py:50
Functionhandler
(signum, frame)
bn_lib/utils/data/dataloader.py:174
Functionhandy_var
(a, unbias=True)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:19
Functionmark_volatile
(obj)
bn_lib/utils/th.py:30
Functionnew_replicate
(module, device_ids)
bn_lib/nn/modules/replicate.py:89
Methodnr_slaves
(self)
bn_lib/nn/modules/comm.py:130
Functionrandom_split
Randomly split a dataset into non-overlapping new datasets of given lengths ds Arguments: dataset (Dataset): Dataset to be split
bn_lib/utils/data/dataset.py:105
Methodreplicate
(self, module, device_ids)
bn_lib/nn/modules/replicate.py:64
Methodscatter
(self, inputs, kwargs, device_ids)
bn_lib/nn/parallel/data_parallel.py:55
Methodset_epoch
(self, epoch)
bn_lib/utils/data/distributed.py:57
MethodtestNumericBatchNorm
(self)
bn_lib/nn/modules/tests/test_numeric_batchnorm.py:30
MethodtestSyncBatchNorm2DSyncTrain
(self)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:99
MethodtestSyncBatchNormNormalEval
(self)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:73
MethodtestSyncBatchNormNormalTrain
(self)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:67
MethodtestSyncBatchNormSyncEval
(self)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:89
MethodtestSyncBatchNormSyncTrain
(self)
bn_lib/nn/modules/tests/test_sync_batchnorm.py:79
Functionuser_scattered_collate
(batch)
bn_lib/nn/parallel/data_parallel.py:66
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