MCPcopy Create free account

hub / github.com/NVlabs/stylegan2 / functions

Functions345 in github.com/NVlabs/stylegan2

⨍ Functions 345◇ Types & classes 28
FunctionD_stylegan2
( images_in, # First input: Images [minibatch, channel, height, width]. label
training/networks_stylegan2.py:613
FunctionD_wgan
(G, D, opt, training_set, minibatch_size, reals, labels, wgan_epsilon=0.001)
training/loss.py:101
FunctionD_wgan_gp
(G, D, opt, training_set, minibatch_size, reals, labels, wgan_lambda=10.0, wgan_epsilon=0.001, wgan_target=1.0
training/loss.py:119
FunctionG_logistic
(G, D, opt, training_set, minibatch_size)
training/loss.py:18
FunctionG_logistic_ns
(G, D, opt, training_set, minibatch_size)
training/loss.py:27
FunctionG_logistic_ns_pathreg
(G, D, opt, training_set, minibatch_size, pl_minibatch_shrink=2, pl_decay=0.01, pl_weight=2.0)
training/loss.py:148
FunctionG_main
( latents_in, # First input: Latent vectors (Z) [minibatch, latent
training/networks_stylegan2.py:151
FunctionG_mapping
( latents_in, # First input: Latent vectors (Z) [minibatch, latent_size].
training/networks_stylegan2.py:251
FunctionG_mapping
( latents_in, # First input: Latent vectors (Z) [minibatch, latent_size].
training/networks_stylegan.py:383
FunctionG_style
( latents_in, # First input: Latent vectors (Z) [minibatch, latent_siz
training/networks_stylegan.py:301
FunctionG_synthesis
( dlatents_in, # Input: Disentangled latents (W) [minibatch, num_layers, dlatent_si
training/networks_stylegan.py:439
FunctionG_synthesis_stylegan2
( dlatents_in, # Input: Disentangled latents (W) [minibatch, num_layers, dlatent_si
training/networks_stylegan2.py:417
FunctionG_synthesis_stylegan_revised
( dlatents_in, # Input: Disentangled latents (W) [minibatch, num_layers, dlatent_si
training/networks_stylegan2.py:307
FunctionG_wgan
(G, D, opt, training_set, minibatch_size)
training/loss.py:92
Method__delattr__
(self, name: str)
dnnlib/util.py:47
Method__enter__
(self)
dataset_tool.py:97
Method__enter__
(self)
dataset_tool.py:158
Method__enter__
(self)
dnnlib/util.py:67
Method__exit__
(self, *args)
dataset_tool.py:100
Method__exit__
(self, *excinfo)
dataset_tool.py:161
Method__exit__
(self, exc_type: Any, exc_value: Any, traceback: Any)
dnnlib/util.py:70
Method__exit__
(self, exc_type: Any, exc_value: Any, traceback: Any)
dnnlib/submission/run_context.py:60
Method__getattr__
(self, name: str)
dnnlib/util.py:38
Method__getstate__
Pickle export.
dnnlib/tflib/network.py:255
Method__init__
(self, tfrecord_dir, expected_images, print_progress=True, progress_interval=10)
dataset_tool.py:33
Method__init__
(self)
dataset_tool.py:106
Method__init__
(self, task_queue)
dataset_tool.py:113
Method__init__
(self)
projector.py:17
Method__init__
(self, name)
metrics/metric_base.py:24
Method__init__
(self, metric_kwarg_list)
metrics/metric_base.py:146
Method__init__
(self, num_features, num_gpus)
metrics/precision_recall.py:40
Method__init__
Find an estimate of the manifold of given feature vectors.
metrics/precision_recall.py:63
Method__init__
(self, num_images, nhood_size, minibatch_per_gpu, row_batch_size, col_batch_size, **kwargs)
metrics/precision_recall.py:172
Method__init__
(self, num_images, num_splits, minibatch_per_gpu, **kwargs)
metrics/inception_score.py:19
Method__init__
(self, num_samples, epsilon, space, sampling, crop, minibatch_per_gpu, Gs_overrides, **kwargs)
metrics/perceptual_path_length.py:35
Method__init__
(self, num_samples, num_keep, attrib_indices, minibatch_per_gpu, **kwargs)
metrics/linear_separability.py:104
Method__init__
(self, num_images, minibatch_per_gpu, **kwargs)
metrics/frechet_inception_distance.py:21
Method__init__
(self, tfrecord_dir, # Directory containing a collection of tfrecords files. res
training/dataset.py:20
Method__init__
(self, file_name: str = None, file_mode: str = "w", should_flush: bool = True)
dnnlib/util.py:54
Method__init__
(self, name: str = None, func_name: Any = None, **static_kwargs)
dnnlib/tflib/network.py:73
Method__init__
(self, name: str = "Train", # Name string that will app
dnnlib/tflib/optimizer.py:38
Method__init__
(self, name="Adam", learning_rate=0.001, beta1=0.9, beta2=0.999, epsilon=1e-8)
dnnlib/tflib/optimizer.py:327
Method__init__
(self, submit_config: submit.SubmitConfig, config_module: types.ModuleType = None)
dnnlib/submission/run_context.py:35
Method__init__
(self)
dnnlib/submission/submit.py:57
Method__init__
(self)
dnnlib/submission/submit.py:87
Method__init__
(self)
dnnlib/submission/internal/local.py:8
Method__init__
(self)
dnnlib/submission/internal/local.py:12
Method__setattr__
(self, name: str, value: Any)
dnnlib/util.py:44
Method__setstate__
Pickle import.
dnnlib/tflib/network.py:267
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/metric_base.py:164
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/precision_recall.py:180
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/inception_score.py:25
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/perceptual_path_length.py:47
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/linear_separability.py:112
Method_evaluate
(self, Gs, Gs_kwargs, num_gpus)
metrics/frechet_inception_distance.py:26
Function_fused_bias_act_cuda
Fast CUDA implementation of `fused_bias_act()` using custom ops.
dnnlib/tflib/ops/fused_bias_act.py:100
Method_iterate_fakes
(self, Gs, minibatch_size, num_gpus)
metrics/metric_base.py:132
Function_legacy_output_transform_func
(*expr, out_mul=1.0, out_add=0.0, out_shrink=1, out_dtype=None)
dnnlib/tflib/network.py:575
Function_parse_comma_sep
(s)
run_training.py:134
Function_parse_num_range
Accept either a comma separated list of numbers 'a,b,c' or a range 'a-c' and return as a list of ints.
run_projector.py:73
Function_parse_num_range
Accept either a comma separated list of numbers 'a,b,c' or a range 'a-c' and return as a list of ints.
run_generator.py:90
Function_str_to_bool
(v)
run_training.py:124
Function_str_to_bool
(v)
run_metrics.py:31
Function_upfirdn_2d_cuda
Fast CUDA implementation of `upfirdn_2d()` using custom ops.
dnnlib/tflib/ops/upfirdn_2d.py:105
Function_upfirdn_2d_ref
Slow reference implementation of `upfirdn_2d()` using standard TensorFlow ops.
dnnlib/tflib/ops/upfirdn_2d.py:66
Functionabsolute_variable_scope
Forcefully enter the specified variable scope, ignoring any surrounding scopes.
dnnlib/tflib/tfutil.py:79
Functionapply_mirror_augment
(minibatch)
training/misc.py:76
Functionask_yes_no
Ask the user the question until the user inputs a valid answer.
dnnlib/util.py:125
Functioncall_func_by_name
Finds the python object with the given name and calls it as a function.
dnnlib/util.py:251
Functioncompare
(tfrecord_dir_a, tfrecord_dir_b, ignore_labels)
dataset_tool.py:245
Methodconfigure_progress_reports
(self, plo, phi, pmax, psec=15)
metrics/metric_base.py:55
Methodconvert
Create new network with the given parameters, and copy all variables from this network.
dnnlib/tflib/network.py:331
Functionconvert_images_from_uint8
Convert a minibatch of images from uint8 to float32 with configurable dynamic range. Can be used as an input transformation for Network.run().
dnnlib/tflib/tfutil.py:230
Functionconvert_images_to_uint8
Convert a minibatch of images from float32 to uint8 with configurable dynamic range. Can be used as an output transformation for Network.run().
dnnlib/tflib/tfutil.py:240
Functioncopy_files_and_create_dirs
Takes in a list of tuples of (src, dst) paths and copies files. Will create all necessary directories.
dnnlib/util.py:312
Methodcopy_own_vars_from
Copy the values of all variables from the given network, excluding sub-networks.
dnnlib/tflib/network.py:316
Methodcopy_trainables_from
Copy the values of all trainable variables from the given network, including sub-networks.
dnnlib/tflib/network.py:326
Functioncreate_celeba
(tfrecord_dir, celeba_dir, cx=89, cy=121)
dataset_tool.py:483
Functioncreate_cifar10
(tfrecord_dir, cifar10_dir)
dataset_tool.py:329
Functioncreate_cifar100
(tfrecord_dir, cifar100_dir)
dataset_tool.py:356
Functioncreate_from_hdf5
(tfrecord_dir, hdf5_filename, shuffle)
dataset_tool.py:530
Functioncreate_from_images
(tfrecord_dir, image_dir, shuffle)
dataset_tool.py:502
Functioncreate_lsun
(tfrecord_dir, lmdb_dir, resolution=256, max_images=None)
dataset_tool.py:405
Functioncreate_lsun_wide
(tfrecord_dir, lmdb_dir, width=512, height=384, max_images=None)
dataset_tool.py:438
Functioncreate_mnist
(tfrecord_dir, mnist_dir)
dataset_tool.py:288
Functioncreate_mnistrgb
(tfrecord_dir, mnist_dir, num_images=1000000, random_seed=123)
dataset_tool.py:312
Functioncreate_svhn
(tfrecord_dir, svhn_dir)
dataset_tool.py:378
Functioncreate_var_with_large_initial_value
Create tf.Variable with large initial value without bloating the tf graph.
dnnlib/tflib/tfutil.py:220
Functiondisplay
(tfrecord_dir)
dataset_tool.py:192
Functionexp2
Exponent in base 2.
dnnlib/tflib/tfutil.py:56
Functionextract
(tfrecord_dir, output_dir)
dataset_tool.py:218
Functionfilter_2d
r"""Filter a batch of 2D images with the given FIR filter. Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]` and fil
dnnlib/tflib/ops/upfirdn_2d.py:144
Functionflatten
Shortcut function for flattening a tensor.
dnnlib/tflib/tfutil.py:44
Functionformat_time
Convert the seconds to human readable string with days, hours, minutes and seconds.
dnnlib/util.py:111
Functiongenerate_images
(network_pkl, seeds, truncation_psi)
run_generator.py:19
Functionget_dtype_and_ctype
Given a type name string (or an object having a __name__ attribute), return matching Numpy and ctypes types that have the same size in bytes.
dnnlib/util.py:159
Functionget_module_dir_by_obj_name
Get the directory path of the module containing the given object name.
dnnlib/util.py:259
Functionget_plugin
(cuda_file)
dnnlib/tflib/custom_ops.py:87
Methodget_random_labels_np
(self, minibatch_size)
training/dataset.py:155
Methodget_result_str
(self)
metrics/metric_base.py:153
← previousnext →201–300 of 345, ranked by callers