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Functions132 in github.com/JiahuiYu/slimmable_networks

⨍ Functions 132◇ Types & classes 38
↓ 18 callersFunctionmake_divisible
forked from slim: https://github.com/tensorflow/models/blob/\ 0344c5503ee55e24f0de7f37336a6e08f10976fd/\ research/slim/nets/mobilenet
models/slimmable_ops.py:76
↓ 17 callersFunctionpop_channels
(autoslim_channels)
models/slimmable_ops.py:200
↓ 10 callersFunctionforward_loss
forward model and return loss
train.py:362
↓ 10 callersFunctionis_master
check if current process is the master
utils/distributed.py:55
↓ 6 callersMethod__repr__
Print all variables.
utils/config.py:81
↓ 6 callersFunctionrun_one_epoch
run one epoch for train/val/test/cal
train.py:398
↓ 5 callersMethod__init__
(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, dep
models/slimmable_ops.py:93
↓ 5 callersFunctionrun_forward
(self, input)
utils/model_profiling.py:41
↓ 4 callersMethodcache
(self, value, pstep=1)
utils/meters.py:20
↓ 4 callersFunctionget_meters
util function for meters
train.py:290
↓ 4 callersFunctionget_rank
()
utils/distributed.py:29
↓ 4 callersFunctionmodel_profiling
Pytorch model profiling with input image size (batch, channel, height, width). The function exams the number of multiply-accumulates (n_macs)
utils/model_profiling.py:145
↓ 3 callersFunctionget_params
get number of params in module
utils/model_profiling.py:35
↓ 3 callersFunctionget_world_size
()
utils/distributed.py:37
↓ 3 callersFunctionprofiling
profiling on either gpu or cpu
train.py:315
↓ 2 callersMethod__init__
(self, stream)
utils/config.py:24
↓ 2 callersMethod__init__
(self, inp, outp, stride)
models/s_shufflenet.py:26
↓ 2 callersMethod_dist_broadcast_coalesced
(self, tensors, buffer_size)
utils/distributed.py:136
↓ 2 callersFunctionconv_module_name_filter
filter module name to have a short view
utils/model_profiling.py:49
↓ 2 callersFunctionflush_scalar_meters
Docstring for flush_scalar_meters
utils/meters.py:44
↓ 2 callersFunctionget_lr_scheduler
get learning rate
train.py:203
↓ 2 callersFunctionget_model
get model
train.py:26
↓ 2 callersFunctionget_single_meter
(phase, suffix='')
train.py:292
↓ 2 callersMethodreset
(self)
utils/meters.py:17
↓ 2 callersMethodscatter
(self, inputs, kwargs, device_ids)
utils/distributed.py:155
↓ 2 callersFunctionset_random_seed
set random seed
train.py:278
↓ 1 callersMethod__init__
(self, name)
utils/meters.py:12
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/s_mobilenet_v1.py:32
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/autoslim_mobilenet_v1.py:33
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/autoslim_mobilenet_v2.py:48
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/us_mobilenet_v1.py:32
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/autoslim_mnasnet.py:48
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/s_mobilenet_v2.py:48
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224)
models/us_mobilenet_v2.py:54
↓ 1 callersMethod__init__
(self, inp, outp, midp1, midp2, stride)
models/autoslim_resnet.py:12
↓ 1 callersMethod__init__
(self, inp, outp, stride)
models/s_resnet.py:11
↓ 1 callersFunction_allreduce_coalesced
(tensors, world_size, bucket_size_mb=-1)
utils/distributed.py:89
↓ 1 callersMethod_sync_params
(self)
utils/distributed.py:144
↓ 1 callersFunctionadd_profiling_hooks
(m, verbose)
utils/model_profiling.py:131
↓ 1 callersFunctionallreduce_grads
(model, coalesce=True, bucket_size_mb=-1)
utils/distributed.py:111
↓ 1 callersFunctionapp
Load app via stdin from subprocess
utils/config.py:153
↓ 1 callersFunctionbn_calibration_init
calculating post-statistics of batch normalization
models/slimmable_ops.py:204
↓ 1 callersMethodcache_list
(self, value_list, pstep=1)
utils/meters.py:24
↓ 1 callersFunctiondata_loader
get data loader
train.py:139
↓ 1 callersFunctiondata_transforms
get transform of dataset
train.py:43
↓ 1 callersFunctiondataset
get dataset for classification
train.py:93
↓ 1 callersFunctiondist_all_reduce_tensor
Reduce to all ranks
utils/distributed.py:78
↓ 1 callersMethodflush
(self, value, reset=True)
utils/meters.py:28
↓ 1 callersMethodforward
(self, output, target)
utils/loss_ops.py:8
↓ 1 callersFunctionget_conv_layers
(m)
train.py:544
↓ 1 callersFunctionget_optimizer
get optimizer
train.py:249
↓ 1 callersFunctioninit_dist
(launcher='pytorch', backend='nccl', **kwargs)
utils/distributed.py:16
↓ 1 callersFunctioninit_multiprocessing
()
train.py:790
↓ 1 callersFunctionlr_schedule_per_iteration
function for learning rate scheuling per iteration
train.py:337
↓ 1 callersFunctionmain
train and eval model
train.py:798
↓ 1 callersFunctionmodule_profiling
(self, input, output, verbose)
utils/model_profiling.py:63
↓ 1 callersFunctionremove_profiling_hooks
()
utils/model_profiling.py:138
↓ 1 callersMethodreset_parameters
(self)
models/s_mobilenet_v1.py:102
↓ 1 callersMethodreset_parameters
(self)
models/autoslim_mobilenet_v1.py:100
↓ 1 callersMethodreset_parameters
(self)
models/autoslim_mobilenet_v2.py:118
↓ 1 callersMethodreset_parameters
(self)
models/us_mobilenet_v1.py:94
↓ 1 callersMethodreset_parameters
(self)
models/autoslim_mnasnet.py:136
↓ 1 callersMethodreset_parameters
(self)
models/s_mobilenet_v2.py:125
↓ 1 callersMethodreset_parameters
(self)
models/us_mobilenet_v2.py:128
↓ 1 callersMethodreset_parameters
(self)
models/autoslim_resnet.py:143
↓ 1 callersMethodreset_parameters
(self)
models/s_shufflenet.py:216
↓ 1 callersMethodreset_parameters
(self)
models/s_resnet.py:115
↓ 1 callersFunctionslimming
network slimming by slimmable network
train.py:556
↓ 1 callersFunctiontrain_val_test
train and val
train.py:611
Method__call__
(self, img)
utils/transforms.py:28
Method__enter__
(self)
utils/model_profiling.py:24
Method__exit__
(self, *args)
utils/model_profiling.py:28
Method__init__
(self, name)
utils/meters.py:36
Method__init__
(self, *args, **kwargs)
utils/config.py:47
Method__init__
(self, filename=None, verbose=False)
utils/config.py:139
Method__init__
(self, alphastd, eigval=imagenet_pca['eigval'], eigvec=imagenet_pca['eigvec'
utils/transforms.py:19
Method__init__
(self, verbose=False)
utils/model_profiling.py:19
Method__init__
(self, module, dim=0, broadcast_buffers=True, bucket_cap_mb=25)
utils/distributed.py:126
Method__init__
(self, num_features_list)
models/slimmable_ops.py:8
Method__init__
(self, in_channels_list, out_channels_list, kernel_size, stride=1, padding=0, dilation=1,
models/slimmable_ops.py:26
Method__init__
(self, in_features_list, out_features_list, bias=True)
models/slimmable_ops.py:57
Method__init__
(self, in_features, out_features, bias=True, us=[True, True])
models/slimmable_ops.py:133
Method__init__
(self, num_features, ratio=1)
models/slimmable_ops.py:157
Method__init__
(self, inp, outp, stride)
models/s_mobilenet_v1.py:11
Method__init__
(self, inp, outp, stride)
models/autoslim_mobilenet_v1.py:12
Method__init__
(self, inp, outp, cmid, stride)
models/autoslim_mobilenet_v2.py:12
Method__init__
(self, inp, outp, stride)
models/us_mobilenet_v1.py:10
Method__init__
(self, inp, outp, stride, cmid, kernel_size)
models/autoslim_mnasnet.py:12
Method__init__
(self, inp, outp, stride, expand_ratio)
models/s_mobilenet_v2.py:11
Method__init__
(self, inp, outp, stride, expand_ratio)
models/us_mobilenet_v2.py:10
Method__init__
(self, num_classes=1000, input_size=224)
models/autoslim_resnet.py:50
Method__init__
(self, groups)
models/s_shufflenet.py:12
Method__init__
(self, num_classes=1000, input_size=224)
models/s_shufflenet.py:139
Method__init__
(self, num_classes=1000, input_size=224)
models/s_resnet.py:50
Method__new__
Add include constructer to class.
utils/config.py:13
Method__repr__
(self)
utils/transforms.py:44
Methodconstruct_include
Include file referenced at node.
utils/config.py:31
Functiondist_reduce_tensor
Reduce to rank 0
utils/distributed.py:66
Methodflush
(self, value, step=-1, reset=True)
utils/meters.py:39
Methodforward
(self, *inputs, **kwargs)
utils/distributed.py:158
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