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Functions109 in github.com/bahjat-kawar/snips_torch

⨍ Functions 109◇ Types & classes 28
↓ 12 callersMethod__init__
(self, features, n_stages, act=nn.ReLU(), maxpool=True, spec_norm=False)
models/layers.py:63
↓ 12 callersFunctionconv3x3
3x3 convolution with padding
models/layers.py:37
↓ 8 callersFunctiondilated_conv3x3
(in_planes, out_planes, dilation, bias=True, spec_norm=False)
models/layers.py:55
↓ 8 callersFunctionspectral_norm
(layer, n_iters=1)
models/layers.py:25
↓ 7 callersMethod__init__
(self, num_features, bias=True)
models/normalization.py:143
↓ 7 callersFunctionmat_by_vec
(M, v)
models/__init__.py:20
↓ 6 callersMethod_compute_cond_module
(self, module, x)
models/ncsnv2.py:264
↓ 5 callersMethod_compute_cond_module
(self, module, x)
models/ncsnv2.py:162
↓ 4 callersMethod_compute_cond_module
(self, module, x)
models/ncsnv2.py:70
↓ 4 callersFunctionget_sigmas
(config)
models/__init__.py:5
↓ 4 callersMethodload_state_dict
(self, state_dict)
models/ema.py:46
↓ 3 callersFunctioncheck_integrity
(fpath, md5=None)
datasets/utils.py:20
↓ 3 callersFunctionget_act
(config)
models/layers.py:11
↓ 3 callersFunctionget_normalization
(config, conditional=True)
models/normalization.py:5
↓ 3 callersFunctioninverse_data_transform
(config, X)
datasets/__init__.py:76
↓ 3 callersMethodupdate
(self, module)
models/ema.py:16
↓ 2 callersMethod__init__
(self, config)
models/ncsnv2.py:12
↓ 2 callersMethod_format_transform_repr
(self, transform, head)
datasets/vision.py:35
↓ 2 callersMethodema
(self, module)
models/ema.py:23
↓ 2 callersFunctiongen_bar_updater
()
datasets/utils.py:8
↓ 2 callersFunctionget_custom_kernel
(type = "gauss", dim = 64)
filter_builder.py:193
↓ 2 callersFunctionmakedir_exist_ok
Python2 support for os.makedirs(.., exist_ok=True)
datasets/utils.py:36
↓ 2 callersMethodstate_dict
(self)
models/ema.py:43
↓ 1 callersMethod__len__
(self)
datasets/vision.py:17
↓ 1 callersMethod__repr__
(self)
datasets/vision.py:20
↓ 1 callersMethod_check_integrity
(self)
datasets/celeba.py:108
↓ 1 callersFunction_get_confirm_token
(response)
datasets/utils.py:169
↓ 1 callersFunction_save_response_content
(response, destination, chunk_size=32768)
datasets/utils.py:177
↓ 1 callersFunctiondata_transform
(config, X)
datasets/__init__.py:60
↓ 1 callersFunctiondict2namespace
(config)
main.py:86
↓ 1 callersFunctiondownload_file_from_google_drive
Download a Google Drive file from and place it in root. Args: file_id (str): id of file to be downloaded root (str): Directory t
datasets/utils.py:134
↓ 1 callersMethodextra_repr
(self)
datasets/vision.py:40
↓ 1 callersFunctiongeneral_anneal_Langevin_dynamics
(H, y_0, x_mod, scorenet, sigmas, n_steps_each=200, step_lr=0.000008, final_only=
models/__init__.py:36
↓ 1 callersFunctionget_dataset
(args, config)
datasets/__init__.py:9
↓ 1 callersFunctionget_model
(config)
runners/ncsn_runner.py:20
↓ 1 callersFunctioninvert_diag
(M)
models/__init__.py:29
↓ 1 callersFunctionkernel_to_matrix
Arg: F -- numpy 2D matrix - kernel of the blur I_row_num - number of rows in signal I_col_num - number of cols in signal Ret
filter_builder.py:131
↓ 1 callersFunctionlogit_transform
(image, lam=1e-6)
datasets/__init__.py:56
↓ 1 callersFunctionmain
()
main.py:97
↓ 1 callersFunctionmatrix_to_vector
Converts the input matrix to a vector by stacking the rows in a specific way explained here Arg: input -- a numpy matrix Re
filter_builder.py:6
↓ 1 callersFunctionparse_args_and_config
()
main.py:17
↓ 1 callersMethodregister
(self, module)
models/ema.py:9
↓ 1 callersMethodsample
(self)
runners/ncsn_runner.py:140
↓ 1 callersMethodsample_general
(self, score, samples, init_samples, sigma_0, sigmas, num_variations = 8, deg = 'sr4')
runners/ncsn_runner.py:33
↓ 1 callersFunctionvec_to_image
(v, img_dim)
models/__init__.py:26
↓ 1 callersFunctionvector_to_matrix
Reshapes the output of the maxtrix multiplication to the shape "output_shape" Arg: input -- a numpy vector Returns: out
filter_builder.py:27
Method__getitem__
(self, index)
datasets/vision.py:14
Method__getitem__
(self, index)
datasets/celeba.py:133
Method__init__
(self, args, config)
runners/ncsn_runner.py:27
Method__init__
(self, root)
datasets/vision.py:9
Method__init__
(self, root, split="train", target_type="attr", transform=N
datasets/celeba.py:50
Method__init__
(self, features, n_stages, num_classes, normalizer, act=nn.ReLU(), spec_norm=False)
models/layers.py:87
Method__init__
(self, features, n_blocks, n_stages, act=nn.ReLU(), spec_norm=False)
models/layers.py:113
Method__init__
(self, features, n_blocks, n_stages, num_classes, normalizer, act=nn.ReLU(), spec_norm=False)
models/layers.py:138
Method__init__
:param in_planes: tuples of input planes
models/layers.py:166
Method__init__
:param in_planes: tuples of input planes
models/layers.py:188
Method__init__
(self, in_planes, features, act=nn.ReLU(), start=False, end=False, maxpool=True, spec_norm=False)
models/layers.py:215
Method__init__
(self, in_planes, features, num_classes, normalizer, act=nn.ReLU(), start=False, end=False, spec_norm=False)
models/layers.py:254
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True, adjust_padding=False, spec_norm=False)
models/layers.py:292
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True, spec_norm=False)
models/layers.py:316
Method__init__
(self, input_dim, output_dim, kernel_size=3, biases=True, spec_norm=False)
models/layers.py:330
Method__init__
(self, input_dim, output_dim, num_classes, resample=None, act=nn.ELU(), normalization=Conditi
models/layers.py:345
Method__init__
(self, input_dim, output_dim, resample=None, act=nn.ELU(), normalization=nn.BatchNorm2d, adju
models/layers.py:402
Method__init__
(self, mu=0.999)
models/ema.py:5
Method__init__
(self, config)
models/ncsnv2.py:105
Method__init__
(self, config)
models/ncsnv2.py:199
Method__init__
(self, num_features, num_classes, bias=True)
models/normalization.py:37
Method__init__
(self, num_features, num_classes, bias=True)
models/normalization.py:62
Method__init__
(self, num_features, num_classes, bias=False)
models/normalization.py:87
Method__init__
(self, num_features, bias=False)
models/normalization.py:104
Method__init__
(self, num_features, num_classes, bias=True)
models/normalization.py:120
Method__init__
(self, num_features, bias=True)
models/normalization.py:151
Method__init__
(self, num_features, num_classes, bias=True)
models/normalization.py:180
Method__len__
(self)
datasets/celeba.py:158
Functionbar_update
(count, block_size, total_size)
datasets/utils.py:11
Functionconv1x1
1x1 convolution
models/layers.py:28
Functionconvolution_as_maultiplication
Performs 2D convolution between input I and filter F by converting the F to a toeplitz matrix and multiply it with vectorizes version of I
filter_builder.py:48
Methoddownload
(self)
datasets/celeba.py:120
Functiondownload_url
Download a file from a url and place it in root. Args: url (str): URL to download file from root (str): Directory to place downlo
datasets/utils.py:49
Methodema_copy
(self, module)
models/ema.py:30
Methodextra_repr
(self)
datasets/celeba.py:161
Methodforward
(self, x)
models/layers.py:76
Methodforward
(self, x, y)
models/layers.py:100
Methodforward
(self, x)
models/layers.py:126
Methodforward
(self, x, y)
models/layers.py:153
Methodforward
(self, xs, shape)
models/layers.py:178
Methodforward
(self, xs, y, shape)
models/layers.py:204
Methodforward
(self, xs, output_shape)
models/layers.py:234
Methodforward
(self, xs, y, output_shape)
models/layers.py:273
Methodforward
(self, inputs)
models/layers.py:309
Methodforward
(self, inputs)
models/layers.py:322
Methodforward
(self, inputs)
models/layers.py:337
Methodforward
(self, x, y)
models/layers.py:385
Methodforward
(self, x)
models/layers.py:443
Methodforward
(self, x, y)
models/ncsnv2.py:75
Methodforward
(self, x, y)
models/ncsnv2.py:167
Methodforward
(self, x, y)
models/ncsnv2.py:269
Methodforward
(self, x, y)
models/normalization.py:50
Methodforward
(self, x, y)
models/normalization.py:75
Methodforward
(self, x, y)
models/normalization.py:94
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