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Functions563 in github.com/SizheAn/PanoHead

Methodextra_repr
(self)
training/dual_discriminator.py:74
Methodextra_repr
(self)
training/dual_discriminator.py:166
Methodextra_repr
(self)
training/dual_discriminator.py:239
Methodextra_repr
(self)
training/dual_discriminator.py:339
Methodextra_repr
(self)
training/dual_discriminator.py:418
Functionfid50k
(opts)
metrics/metric_main.py:133
Functionfid50k_full
(opts)
metrics/metric_main.py:89
Functionfilter2d
r"""Filter a batch of 2D images using the given 2D FIR filter. By default, the result is padded so that its shape matches the input. User-spe
torch_utils/ops/upfirdn2d.py:279
Functionfiltered_lrelu
r"""Filtered leaky ReLU for a batch of 2D images. Performs the following sequence of operations for each channel: 1. Add channel-specific bi
torch_utils/ops/filtered_lrelu.py:58
Methodfind_class
(self, module, name)
legacy.py:68
Functionfma
(a, b, c)
torch_utils/ops/fma.py:17
Functionfolder_write_bytes
(fname: str, data: Union[bytes, str])
dataset_tool_seg.py:190
Functionfolder_write_bytes
(fname: str, data: Union[bytes, str])
dataset_tool.py:314
Methodfont_size
(self)
gui_utils/imgui_window.py:63
Functionformat_time
Convert the seconds to human readable string with days, hours, minutes and seconds.
dnnlib/util.py:141
Functionformat_time_brief
Convert the seconds to human readable string with days, hours, minutes and seconds.
dnnlib/util.py:155
Methodforward
(ctx, x, fu, fd, b, si, sx, sy)
torch_utils/ops/filtered_lrelu.py:182
Methodforward
(ctx, input, grid)
torch_utils/ops/grid_sample_gradfix.py:42
Methodforward
(ctx, grad_output, input, grid)
torch_utils/ops/grid_sample_gradfix.py:59
Methodforward
(ctx, x, b)
torch_utils/ops/bias_act.py:146
Methodforward
(ctx, dy, x, b, y)
torch_utils/ops/bias_act.py:179
Methodforward
(ctx, x, f)
torch_utils/ops/upfirdn2d.py:235
Methodforward
(ctx, a, b, c)
torch_utils/ops/fma.py:24
Methodforward
(ctx, input, weight, bias)
torch_utils/ops/conv2d_gradfix.py:109
Methodforward
(ctx, grad_output, input, weight)
torch_utils/ops/conv2d_gradfix.py:157
Methodforward
(self, c)
metrics/perceptual_path_length.py:50
Methodforward
(self, x)
training/networks_stylegan3.py:91
Methodforward
(self, z, c, truncation_psi=1, truncation_cutoff=None, update_emas=False)
training/networks_stylegan3.py:137
Methodforward
(self, w)
training/networks_stylegan3.py:200
Methodforward
(self, x, w, noise_mode='random', force_fp32=False, update_emas=False)
training/networks_stylegan3.py:331
Methodforward
(self, ws, **layer_kwargs)
training/networks_stylegan3.py:466
Methodforward
(self, z, c, truncation_psi=1, truncation_cutoff=None, update_emas=False, **synthesis_kwargs)
training/networks_stylegan3.py:512
Methodforward
(self, rgb, x, ws, **block_kwargs)
training/superresolution.py:45
Methodforward
(self, rgb, x, ws, **block_kwargs)
training/superresolution.py:77
Methodforward
(self, rgb, x, ws, **block_kwargs)
training/superresolution.py:110
Methodforward
(self, rgb, x, ws, **block_kwargs)
training/superresolution.py:142
Methodforward
(self, x, img, ws, force_fp32=False, fused_modconv=None, update_emas=False, **layer_kwargs)
training/superresolution.py:210
Methodforward
(self, rgb, x, ws, **block_kwargs)
training/superresolution.py:279
Methodforward
(self, x)
training/networks_stylegan2.py:114
Methodforward
(self, x, gain=1)
training/networks_stylegan2.py:174
Methodforward
(self, z, c, truncation_psi=1, truncation_cutoff=None, update_emas=False)
training/networks_stylegan2.py:237
Methodforward
(self, x, w, noise_mode='random', fused_modconv=True, gain=1)
training/networks_stylegan2.py:315
Methodforward
(self, x, w, fused_modconv=True)
training/networks_stylegan2.py:357
Methodforward
(self, x, img, ws, force_fp32=False, fused_modconv=None, update_emas=False, **layer_kwargs)
training/networks_stylegan2.py:421
Methodforward
(self, ws, **block_kwargs)
training/networks_stylegan2.py:507
Methodforward
(self, z, c, truncation_psi=1, truncation_cutoff=None, update_emas=False, **synthesis_kwargs)
training/networks_stylegan2.py:553
Methodforward
(self, x, img, force_fp32=False)
training/networks_stylegan2.py:612
Methodforward
(self, x)
training/networks_stylegan2.py:656
Methodforward
(self, x, img, cmap, force_fp32=False)
training/networks_stylegan2.py:706
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/networks_stylegan2.py:784
Methodforward
(self, z, c, truncation_psi=1, truncation_cutoff=None, neural_rendering_resolution=None, update_emas=False, ca
training/triplane.py:154
Methodforward
(self, sampled_features, ray_directions)
training/triplane.py:177
Methodforward
(self, images, debug_percentile=None)
training/augment.py:188
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/dual_discriminator.py:59
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/dual_discriminator.py:149
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/dual_discriminator.py:221
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/dual_discriminator.py:310
Methodforward
(self, img, c, update_emas=False, **block_kwargs)
training/dual_discriminator.py:399
Methodforward
(self, planes, decoder, ray_origins, ray_directions, rendering_options, triplane_crop=0.1, cull_clouds=None, b
training/volumetric_rendering/renderer.py:100
Methodforward
Create batches of rays and return origins and directions. cam2world_matrix: (N, 4, 4) intrinsics: (N, 3, 3) resoluti
training/volumetric_rendering/ray_sampler.py:24
Methodforward
(self, colors, densities, depths, rendering_options)
training/volumetric_rendering/ray_marcher.py:60
Methodframe_delta
(self)
gui_utils/glfw_window.py:95
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:203
Functionget_mask
(model, batch, cid)
gen_interpolation.py:48
Functionget_module_dir_by_obj_name
Get the directory path of the module containing the given object name.
dnnlib/util.py:308
Functionget_plugin
(module_name, sources, headers=None, source_dir=None, **build_kwargs)
torch_utils/custom_ops.py:61
Functionget_ray_limits_box
Author: Petr Kellnhofer Intersects rays with the [-1, 1] NDC volume. Returns min and max distance of entry. Returns -1 for no interse
training/volumetric_rendering/math_utils.py:46
Functionget_texture
(string, bilinear=True, mipmap=True, **kwargs)
gui_utils/text_utils.py:122
Functionget_top_level_function_name
Return the fully-qualified name of a top-level function.
dnnlib/util.py:319
Functiongrid_sample
(input, grid)
torch_utils/ops/grid_sample_gradfix.py:28
Methodhas_labels
(self)
training/dataset.py:152
Methodhas_onehot_labels
(self)
training/dataset.py:156
Methodimage_shape
(self)
training/dataset.py:122
Functionimport_hook
r"""Register an import hook that is called whenever a persistent object is being unpickled. A typical use case is to patch the pickled source
torch_utils/persistence.py:149
Methodinit_args
(self)
torch_utils/persistence.py:113
Functioninit_egl
()
gui_utils/gl_utils.py:21
Methodinit_kwargs
(self)
torch_utils/persistence.py:117
Functioninit_multiprocessing
r"""Initializes `torch_utils.training_stats` for collecting statistics across multiple processes. This function must be called after `tor
torch_utils/training_stats.py:36
Functioninput_text
(label, value, buffer_length, flags, width=None, help_text='')
gui_utils/imgui_utils.py:122
Functionis50k
(opts)
metrics/metric_main.py:151
Functionis_pickleable
(obj: Any)
dnnlib/util.py:226
Methodis_skipping_frames
(self)
gui_utils/glfw_window.py:138
Functionkid50k
(opts)
metrics/metric_main.py:139
Functionkid50k_full
(opts)
metrics/metric_main.py:95
Methodlabel_dim
(self)
training/dataset.py:147
Methodlabel_shape
(self)
training/dataset.py:137
Functionlinspace
Creates a tensor of shape [num, *start.shape] whose values are evenly spaced from start to end, inclusive. Replicates but the multi-dimension
training/volumetric_rendering/math_utils.py:101
Functionlist_dir_recursively_with_ignore
List all files recursively in a given directory while ignoring given file and directory names. Returns list of tuples containing both absolute and
dnnlib/util.py:331
Functionlist_valid_metrics
()
metrics/metric_main.py:39
Functionmake_transform
(translate: Tuple[float,float], angle: float)
gen_samples_forID.py:60
Functionmake_transform
(translate: Tuple[float,float], angle: float)
gen_samples.py:60
Methodmonitor_height
(self)
gui_utils/glfw_window.py:90
Methodmonitor_width
(self)
gui_utils/glfw_window.py:85
Methodname
(self)
training/dataset.py:118
Functionno_weight_gradients
(disable=True)
torch_utils/ops/conv2d_gradfix.py:27
Functionnormalize_vecs
Normalize vector lengths.
training/volumetric_rendering/math_utils.py:33
Methodnum_channels
(self)
training/dataset.py:126
Functionopen_url
Download the given URL and return a binary-mode file object to access the data.
dnnlib/util.py:398
Functionparams_and_buffers
(module)
torch_utils/misc.py:149
Functionparse_comma_separated_list
(s)
train.py:113
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