MCPcopy Create free account

hub / github.com/autonomousvision/stylegan-xl / functions

Functions736 in github.com/autonomousvision/stylegan-xl

⨍ Functions 736◇ Types & classes 120↳ Endpoints 8
↓ 62 callersMethodappend
(self, x)
metrics/metric_utils.py:108
↓ 47 callersFunctionkwarg
(tf_name, default=None, none=None)
legacy.py:120
↓ 45 callersMethodmean
r"""Returns the mean of the scalars that were accumulated for the given statistic between the last two calls to `update()`, or NaN if
torch_utils/training_stats.py:188
↓ 29 callersMethodload
(self, pkl, ignore_errors=False)
viz/pickle_widget.py:47
↓ 28 callersMethoddtype
(self)
feature_networks/clip/model.py:333
↓ 22 callersMethodupdate
(self, cur_items)
metrics/metric_utils.py:181
↓ 18 callersFunctionconv2d
(*args, **kwargs)
pg_modules/blocks.py:11
↓ 18 callersMethodeval
(self)
pg_modules/discriminator.py:192
↓ 14 callersMethod__init__
(self, output_size, input_size, which_linear, eps=1e-5, momentum=0.1)
pg_modules/blocks.py:260
↓ 14 callersFunction_make_resnet
(model)
feature_networks/pretrained_builder.py:22
↓ 12 callersMethod__init__
(self, z_dim, # Input latent (Z) dimensionality. c_dim,
training/networks_stylegan2.py:586
↓ 11 callersFunction_make_cspresnet
(model)
feature_networks/pretrained_builder.py:110
↓ 11 callersMethodsave
(self, pkl_file)
metrics/metric_utils.py:151
↓ 10 callersFunctionget_activation
(name)
feature_networks/vit.py:159
↓ 9 callersFunctionsinc
(x)
metrics/equivariance.py:22
↓ 9 callersMethodsub
(self, tag=None, num_items=None, flush_interval=1000, rel_lo=0, rel_hi=1)
metrics/metric_utils.py:196
↓ 8 callersFunctionerror
(msg)
dataset_tool.py:32
↓ 8 callersMethodupdate
(self, val, n=1)
run_stylemc.py:39
↓ 7 callersFunctionNormLayer
(c, mode='batch')
pg_modules/blocks.py:23
↓ 7 callersMethod__init__
(self, z_dim, # Input latent (Z) dimensionality. c_dim,
training/networks_stylegan3_resetting.py:568
↓ 7 callersFunction_feature_splitter
(model, idcs)
feature_networks/pretrained_builder.py:14
↓ 7 callersMethodbackward
(ctx, dy)
torch_utils/ops/bias_act.py:158
↓ 7 callersFunctionmatrix
(*rows, device=None)
training/augment.py:48
↓ 6 callersMethod__init__
(self, embed_dim: int, # vision image_resolution: int,
feature_networks/clip/model.py:240
↓ 6 callersMethod__init__
(self, z_dim, # Input latent (Z) dimensionality. c_dim,
training/networks_stylegan3.py:605
↓ 6 callersFunction_conv2d_wrapper
Wrapper for the underlying `conv2d()` and `conv_transpose2d()` implementations.
torch_utils/ops/conv2d_resample.py:29
↓ 6 callersFunction_make_efficientnet
(model)
feature_networks/pretrained_builder.py:118
↓ 6 callersFunction_parse_padding
(padding)
torch_utils/ops/upfirdn2d.py:44
↓ 6 callersFunction_parse_scaling
(scaling)
torch_utils/ops/upfirdn2d.py:35
↓ 6 callersMethodupdate
r"""Copies current values of the internal counters to the user-visible state and resets them for the next round. If `keep_previous=Tr
torch_utils/training_stats.py:147
↓ 6 callersMethodwrite
Write text to stdout (and a file) and optionally flush.
dnnlib/util.py:78
↓ 5 callersFunction_get_filter_size
(f)
torch_utils/ops/upfirdn2d.py:55
↓ 5 callersFunction_make_vit_b16_backbone
( model, features=[96, 192, 384, 768], size=[384, 384], hooks=[2, 5, 8, 11], vit_features=
feature_networks/vit.py:183
↓ 5 callersFunction_sinc
(x)
viz/renderer.py:44
↓ 5 callersFunctioniterate_images
()
dataset_tool.py:96
↓ 5 callersFunctionmaybe_min
(a: int, b: Optional[int])
dataset_tool.py:52
↓ 5 callersFunctionscale2d_inv
(sx, sy, **kwargs)
training/augment.py:108
↓ 5 callersMethodskip_frame
(self)
gui_utils/glfw_window.py:130
↓ 5 callersMethodtrain
(self, mode=True)
pg_modules/discriminator.py:187
↓ 4 callersMethod__init__
(self, nc=None, ndf=None, start_sz=256, end_sz=8, head=None, patch=False)
pg_modules/discriminator.py:15
↓ 4 callersFunction_conv2d_gradfix
(transpose, weight_shape, stride, padding, output_padding, dilation, groups)
torch_utils/ops/conv2d_gradfix.py:66
↓ 4 callersMethod_get_raw_labels
(self)
training/dataset.py:67
↓ 4 callersFunction_lanczos_window
(x, a)
viz/renderer.py:49
↓ 4 callersMethod_make_layer
(self, planes, blocks, stride=1)
feature_networks/clip/model.py:126
↓ 4 callersFunction_tuple_of_ints
(xs, ndim)
torch_utils/ops/conv2d_gradfix.py:55
↓ 4 callersMethodclose
Flush, close possible files, and remove stdout/stderr mirroring.
dnnlib/util.py:100
↓ 4 callersMethodencode
(self, text)
feature_networks/clip/simple_tokenizer.py:121
↓ 4 callersMethodencode_text
(self, text)
feature_networks/clip/model.py:339
↓ 4 callersMethodend_frame
(self)
gui_utils/glfw_window.py:198
↓ 4 callersMethodflush
Flush written text to both stdout and a file, if open.
dnnlib/util.py:93
↓ 4 callersFunctionforward_synthesis
pass through synthesis using style space, adjust blocks on the fly if needed
run_stylemc.py:94
↓ 4 callersMethodget_all
(self)
metrics/metric_utils.py:137
↓ 4 callersFunctionget_texture_format
(dtype, channels)
gui_utils/gl_utils.py:76
↓ 4 callersFunctionhas_same_layout
torch_utils/ops/bias_act.cpp:16
↓ 4 callersFunctionlanczos_window
(x, a)
metrics/equivariance.py:27
↓ 4 callersMethodrender
(self, **args)
viz/renderer.py:131
↓ 4 callersMethodstd
r"""Returns the standard deviation of the scalars that were accumulated for the given statistic between the last two calls to `update(
torch_utils/training_stats.py:198
↓ 3 callersMethod__init__
(self, start_index=1)
feature_networks/vit.py:10
↓ 3 callersMethod__init__
( self, z_dim=256, c_dim=0, w_dim=0, img_resolution=256, img_c
training/networks_fastgan.py:153
↓ 3 callersMethod_file_ext
(fname)
training/dataset.py:200
↓ 3 callersMethod_get_delta
r"""Returns the raw moments that were accumulated for the given statistic between the last two calls to `update()`, or zero if no scal
torch_utils/training_stats.py:170
↓ 3 callersFunction_make_densenet
(model)
feature_networks/pretrained_builder.py:84
↓ 3 callersFunction_unbroadcast
(x, shape)
torch_utils/ops/fma.py:49
↓ 3 callersMethodbind
(self)
gui_utils/gl_utils.py:173
↓ 3 callersMethoddecode
(self, tokens)
feature_networks/clip/simple_tokenizer.py:129
↓ 3 callersFunctionfile_ext
(name: Union[str, Path])
dataset_tool.py:59
↓ 3 callersFunctionget_feature_detector
(url, device=torch.device('cpu'), num_gpus=1, rank=0, verbose=False)
metrics/metric_utils.py:55
↓ 3 callersMethodget_label
(self, idx)
training/dataset.py:111
↓ 3 callersFunctionget_obj_from_module
Traverses the object name and returns the last (rightmost) python object.
dnnlib/util.py:277
↓ 3 callersMethodis_compatible
(self, *, image=None, width=None, height=None, channels=None, dtype=None)
gui_utils/gl_utils.py:201
↓ 3 callersMethodmake_context_current
(self)
gui_utils/glfw_window.py:157
↓ 3 callersFunctionnamed_params_and_buffers
(module)
torch_utils/misc.py:171
↓ 3 callersFunctionprepare_texture_data
(image)
gui_utils/gl_utils.py:81
↓ 3 callersFunctionrecurse
(prefix, tf_net)
legacy.py:82
↓ 3 callersFunctionrotate2d_inv
(theta, **kwargs)
training/augment.py:111
↓ 3 callersFunctionrotation_matrix
(angle)
metrics/equivariance.py:31
↓ 3 callersMethodrun_D
(self, img, c, blur_sigma=0, update_emas=False)
training/loss.py:76
↓ 3 callersMethodrun_G
(self, z, c, update_emas=False)
training/loss.py:66
↓ 3 callersFunctionsave_image_grid
(img, fname, drange, grid_size)
training/training_loop.py:74
↓ 3 callersFunctionscale2d
(sx, sy, **kwargs)
training/augment.py:73
↓ 3 callersMethodto_device
(self, buf)
viz/renderer.py:203
↓ 3 callersFunctiontranslate2d
(tx, ty, **kwargs)
training/augment.py:58
↓ 3 callersFunctiontranslate2d_inv
(tx, ty, **kwargs)
training/augment.py:105
↓ 3 callersFunctionupfirdn2d
r"""Pad, upsample, filter, and downsample a batch of 2D images. Performs the following sequence of operations for each channel: 1. Upsample
torch_utils/ops/upfirdn2d.py:118
↓ 3 callersFunctionw_s_converter
(G, ws, device='cuda', unit_test=False)
run_stylemc.py:256
↓ 2 callersMethod__init__
(self)
viz/renderer.py:120
↓ 2 callersMethod_adjust_font_size
(self)
visualizer.py:100
↓ 2 callersMethod_attach_glfw_callbacks
(self)
gui_utils/glfw_window.py:218
↓ 2 callersFunction_collect_tf_params
(tf_net)
legacy.py:79
↓ 2 callersFunction_filtered_lrelu_cuda
Fast CUDA implementation of `filtered_lrelu()` using custom ops.
torch_utils/ops/filtered_lrelu.py:159
↓ 2 callersFunction_get_array_priv
( string: str, *, size: int = 32, max_width: Optional[int]=None, max_height: Optional[int]=Non
gui_utils/text_utils.py:45
↓ 2 callersFunction_get_filter_size
(f)
torch_utils/ops/filtered_lrelu.py:35
↓ 2 callersMethod_get_pinned_buf
(self, ref)
viz/renderer.py:195
↓ 2 callersFunction_get_weight_shape
(w)
torch_utils/ops/conv2d_resample.py:21
↓ 2 callersMethod_get_zipfile
(self)
training/dataset.py:203
↓ 2 callersMethod_ignore_timing
(self)
viz/renderer.py:209
↓ 2 callersMethod_load_raw_labels
(self)
training/dataset.py:86
↓ 2 callersFunction_make_nfnet
(model)
feature_networks/pretrained_builder.py:42
↓ 2 callersMethod_open_file
(self, fname)
training/dataset.py:209
↓ 2 callersFunction_parse_padding
(padding)
torch_utils/ops/filtered_lrelu.py:42
next →1–100 of 736, ranked by callers