MCPcopy Create free account

hub / github.com/SchafferZhang/DADA / functions

Functions199 in github.com/SchafferZhang/DADA

⨍ Functions 199◇ Types & classes 30
↓ 9 callersMethod__init__
(self, incoming, noise_dim, z=lasagne.init.Normal(0.05), sig=lasagne.init.Constant(-1.), **kwargs)
cifar100/nn.py:187
↓ 9 callersMethod__init__
(self, incoming, noise_dim, z=lasagne.init.Normal(0.05), sig=lasagne.init.Constant(-1.), **kwargs)
cifar10-svhn/nn.py:187
↓ 9 callersMethod__init__
(self, incoming, noise_dim, z=lasagne.init.Normal(0.05), sig=lasagne.init.Constant(-1.), **kwargs)
DDSM/nn.py:187
↓ 4 callersFunctionload_dict
(fname)
cifar100/utils/checkpoints.py:35
↓ 4 callersFunctionload_dict
(fname)
cifar10-svhn/utils/checkpoints.py:35
↓ 2 callersFunctionconvert2dict
(params)
cifar100/utils/checkpoints.py:9
↓ 2 callersFunctionconvert2dict
(params)
cifar10-svhn/utils/checkpoints.py:9
↓ 2 callersFunctioncreate_ssl_data
(x, y, n_classes, n_labelled, seed)
cifar100/utils/create_ssl_data.py:6
↓ 2 callersFunctioncreate_ssl_data
(x, y, n_classes, n_labelled, seed)
cifar10-svhn/utils/create_ssl_data.py:6
↓ 2 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
cifar100/train_cifar100.py:47
↓ 2 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
cifar10-svhn/train_cifar_svhn.py:48
↓ 2 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
DDSM/train_ddsm.py:37
↓ 2 callersFunctionimg_stretch
(img)
cifar100/plotting.py:15
↓ 2 callersFunctionimg_stretch
(img)
cifar10-svhn/plotting.py:15
↓ 2 callersFunctionimg_stretch
(img)
DDSM/plotting.py:15
↓ 2 callersFunctionrescale
(mat)
cifar10-svhn/svhn_data.py:17
↓ 2 callersFunctionunpickle
(file)
cifar100/cifar100_data.py:5
↓ 2 callersFunctionunpickle
(file)
cifar10-svhn/cifar10_data.py:25
↓ 1 callersFunctionassign_weights
(params, param_dict)
cifar100/utils/checkpoints.py:97
↓ 1 callersFunctionassign_weights
(params, param_dict)
cifar10-svhn/utils/checkpoints.py:97
↓ 1 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
cifar100/classification.py:27
↓ 1 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
cifar10-svhn/classification.py:28
↓ 1 callersFunctiongen_minibatches
(x,y,batch_size,shuffle=False)
DDSM/classification.py:32
↓ 1 callersFunctionget_list_name
(obj)
cifar100/utils/checkpoints.py:115
↓ 1 callersFunctionget_list_name
(obj)
cifar10-svhn/utils/checkpoints.py:115
↓ 1 callersFunctionget_nonlin
(nonlin)
cifar100/utils/others.py:21
↓ 1 callersFunctionget_nonlin
(nonlin)
cifar10-svhn/utils/others.py:21
↓ 1 callersFunctionget_pad
(pad)
cifar100/utils/others.py:6
↓ 1 callersFunctionget_pad
(pad)
cifar10-svhn/utils/others.py:6
↓ 1 callersFunctionimg_tile
Tile images in a grid. If tile_shape is provided only as many images as specified in tile_shape will be included in the output.
cifar100/plotting.py:21
↓ 1 callersFunctionimg_tile
Tile images in a grid. If tile_shape is provided only as many images as specified in tile_shape will be included in the output.
cifar10-svhn/plotting.py:21
↓ 1 callersFunctionimg_tile
Tile images in a grid. If tile_shape is provided only as many images as specified in tile_shape will be included in the output.
DDSM/plotting.py:21
↓ 1 callersFunctionscale_to_unit_interval
Scales all values in the ndarray ndar to be between 0 and 1
cifar100/plotting.py:83
↓ 1 callersFunctionscale_to_unit_interval
Scales all values in the ndarray ndar to be between 0 and 1
cifar100/utils/paramgraphics.py:19
↓ 1 callersFunctionscale_to_unit_interval
Scales all values in the ndarray ndar to be between 0 and 1
cifar10-svhn/plotting.py:83
↓ 1 callersFunctionscale_to_unit_interval
Scales all values in the ndarray ndar to be between 0 and 1
cifar10-svhn/utils/paramgraphics.py:19
↓ 1 callersFunctionscale_to_unit_interval
Scales all values in the ndarray ndar to be between 0 and 1
DDSM/plotting.py:83
↓ 1 callersFunctiontile_raster_images
Transform an array with one flattened image per row, into an array in which images are reshaped and layed out like tiles on a floor. Thi
cifar100/utils/paramgraphics.py:27
↓ 1 callersFunctiontile_raster_images
Transform an array with one flattened image per row, into an array in which images are reshaped and layed out like tiles on a floor. Thi
cifar10-svhn/utils/paramgraphics.py:27
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
cifar100/nn.py:53
Method__init__
(self, incoming, target_shape, filter_size, stride=(2, 2), W=lasagne.init.Normal(0.05), b=las
cifar100/nn.py:112
Method__init__
(self, incoming, num_kernels, dim_per_kernel=5, theta=lasagne.init.Normal(0.05), log_weight_s
cifar100/nn.py:144
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), nonlinearity=relu, **kwargs)
cifar100/nn.py:206
Method__init__
(self, incoming, sigma=0.1, **kwargs)
cifar100/nn.py:264
Method__init__
(self, incoming, num_units, theta=lasagne.init.Normal(0.1), b=lasagne.init.Constant(0.), weig
cifar100/nn.py:301
Method__init__
(self, incomings, num_cls, **kwargs)
cifar100/nn.py:340
Method__init__
(self, incomings, num_cls, **kwargs)
cifar100/nn.py:361
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
cifar100/nn.py:380
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
cifar10-svhn/nn.py:53
Method__init__
(self, incoming, target_shape, filter_size, stride=(2, 2), W=lasagne.init.Normal(0.05), b=las
cifar10-svhn/nn.py:112
Method__init__
(self, incoming, num_kernels, dim_per_kernel=5, theta=lasagne.init.Normal(0.05), log_weight_s
cifar10-svhn/nn.py:144
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), nonlinearity=relu, **kwargs)
cifar10-svhn/nn.py:206
Method__init__
(self, incoming, sigma=0.1, **kwargs)
cifar10-svhn/nn.py:264
Method__init__
(self, incoming, num_units, theta=lasagne.init.Normal(0.1), b=lasagne.init.Constant(0.), weig
cifar10-svhn/nn.py:301
Method__init__
(self, incomings, num_cls, **kwargs)
cifar10-svhn/nn.py:340
Method__init__
(self, incomings, num_cls, **kwargs)
cifar10-svhn/nn.py:361
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
cifar10-svhn/nn.py:380
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
DDSM/nn.py:53
Method__init__
(self, incoming, target_shape, filter_size, stride=(2, 2), W=lasagne.init.Normal(0.05), b=las
DDSM/nn.py:112
Method__init__
(self, incoming, num_kernels, dim_per_kernel=5, theta=lasagne.init.Normal(0.05), log_weight_s
DDSM/nn.py:144
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), nonlinearity=relu, **kwargs)
DDSM/nn.py:206
Method__init__
(self, incoming, sigma=0.1, **kwargs)
DDSM/nn.py:264
Method__init__
(self, incoming, num_units, theta=lasagne.init.Normal(0.1), b=lasagne.init.Constant(0.), weig
DDSM/nn.py:301
Method__init__
(self, incomings, num_cls, **kwargs)
DDSM/nn.py:340
Method__init__
(self, incomings, num_cls, **kwargs)
DDSM/nn.py:361
Method__init__
(self, incoming, b=lasagne.init.Constant(0.), g=lasagne.init.Constant(1.), W=lasagne.init.Nor
DDSM/nn.py:380
Function_progress
(count, block_size, total_size)
cifar10-svhn/svhn_data.py:12
Function_progress
(count, block_size, total_size)
cifar10-svhn/cifar10_data.py:15
Functionadam_updates
(params, cost, lr=0.001, mom1=0.9, mom2=0.999)
cifar100/nn.py:32
Functionadam_updates
(params, cost, lr=0.001, mom1=0.9, mom2=0.999)
cifar10-svhn/nn.py:32
Functionadam_updates
(params, cost, lr=0.001, mom1=0.9, mom2=0.999)
DDSM/nn.py:32
Functionarray2file_2D
(array, logfile)
cifar100/utils/others.py:49
Functionarray2file_2D
(array, logfile)
cifar10-svhn/utils/others.py:49
Functionbatch_norm
adapted from https://gist.github.com/f0k/f1a6bd3c8585c400c190
cifar100/nn.py:248
Functionbatch_norm
adapted from https://gist.github.com/f0k/f1a6bd3c8585c400c190
cifar10-svhn/nn.py:248
Functionbatch_norm
adapted from https://gist.github.com/f0k/f1a6bd3c8585c400c190
DDSM/nn.py:248
Functionbernoullisample
(x)
cifar100/utils/others.py:45
Functionbernoullisample
(x)
cifar10-svhn/utils/others.py:45
Functionbuild_log_file
(cfg)
cifar100/utils/checkpoints.py:126
Functionbuild_log_file
(cfg)
cifar10-svhn/utils/checkpoints.py:126
Functionbuild_model
()
DDSM/alexnet.py:6
Functioncentered_softplus
(x)
cifar100/nn.py:23
Functioncentered_softplus
(x)
cifar10-svhn/nn.py:23
Functioncentered_softplus
(x)
DDSM/nn.py:23
Functionconv_filter_tile
(filters)
cifar100/plotting.py:68
Functionconv_filter_tile
(filters)
cifar10-svhn/plotting.py:68
Functionconv_filter_tile
(filters)
DDSM/plotting.py:68
Functioncreate_ssl_data_subset
(x, y, n_classes, n_labelled, n_labelled_per_time, seed)
cifar100/utils/create_ssl_data.py:43
Functioncreate_ssl_data_subset
(x, y, n_classes, n_labelled, n_labelled_per_time, seed)
cifar10-svhn/utils/create_ssl_data.py:43
Functionget_cfg
(args)
cifar100/utils/checkpoints.py:158
Functionget_cfg
(args)
cifar10-svhn/utils/checkpoints.py:158
Functionget_nonlin_list
(nonlin_list)
cifar100/utils/others.py:38
Functionget_nonlin_list
(nonlin_list)
cifar10-svhn/utils/others.py:38
Methodget_output_for
(self, input, init=False, **kwargs)
cifar100/nn.py:88
Methodget_output_for
(self, input, **kwargs)
cifar100/nn.py:128
Methodget_output_for
(self, input, init=False, **kwargs)
cifar100/nn.py:157
Methodget_output_for
(self, input, **kwargs)
cifar100/nn.py:195
Methodget_output_for
(self, input, deterministic=False, **kwargs)
cifar100/nn.py:223
Methodget_output_for
(self, input, deterministic=False, use_last_noise=False, **kwargs)
cifar100/nn.py:269
Methodget_output_for
(self, input, init=False, deterministic=False, **kwargs)
cifar100/nn.py:315
next →1–100 of 199, ranked by callers