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github.com/apple/ml-vivid
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Functions
212 in github.com/apple/ml-vivid
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Functions
212
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Types & classes
30
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Endpoints
4
Method
__call__
(self, x)
calculate_metrics.py:35
Method
__call__
(self, x)
calculate_metrics.py:49
Method
__call__
(self, x)
calculate_metrics.py:66
Method
__call__
(self, net, src, tgt, labels=None)
training/training_loop.py:46
Method
__call__
(self, net, src, tgt, labels=None)
training/training_loop.py:63
Method
__delattr__
(self, name: str)
dnnlib/util.py:53
Method
__enter__
(self)
dnnlib/util.py:73
Method
__exit__
(self, exc_type: Any, exc_value: Any, traceback: Any)
dnnlib/util.py:76
Method
__getattr__
(self, name: str)
dnnlib/util.py:44
Method
__getitem__
(self, index)
datautils.py:121
Method
__getitem__
(self, index)
datautils.py:158
Method
__getitem__
(self, index)
datautils.py:195
Method
__getitem__
r"""Convenience getter. `collector[name]` is a synonym for `collector.mean(name)`.
torch_utils/training_stats.py:232
Method
__init__
(self, device, seeds)
generate_images.py:98
Method
__init__
(self, split="train", imsize=64, data_root="data", sr_mult=4, range_selection=None, **kwargs)
datautils.py:104
Method
__init__
(self, imsize, data_root="data", sr_mult=4, **kwargs)
datautils.py:148
Method
__init__
(self, dir, max_size=None, random_seed=0)
datautils.py:186
Method
__init__
(self)
calculate_metrics.py:43
Method
__init__
(self, resize_mode='torch')
calculate_metrics.py:57
Method
__init__
(self, dataset, rank=0, num_replicas=1, shuffle=True, seed=0, start_idx=0)
torch_utils/misc.py:127
Method
__init__
(self, **kwargs)
torch_utils/distributed.py:94
Method
__init__
(self, *args, **kwargs)
torch_utils/persistence.py:111
Method
__init__
(self, regex='.*', keep_previous=False)
torch_utils/training_stats.py:139
Method
__init__
(self)
training/encoders.py:52
Method
__init__
(self, num_channels, bandwidth=1)
training/models.py:89
Method
__init__
(self, in_channels, out_channels, kernel)
training/models.py:107
Method
__init__
(self, in_channels, # Number of input channels. out_channels,
training/models.py:130
Method
__init__
(self, in_channels, # Number of input channels. out_channels,
training/models.py:205
Method
__init__
(self, img_resolution, # Image resolution. img_channels,
training/models.py:386
Method
__init__
(self, *args, no_cam=False, **kwargs)
training/models.py:490
Method
__init__
(self, img_resolution, *args, **kwargs)
training/models.py:534
Method
__init__
(self, img_resolution, # Image resolution. img_channels, # I
training/models.py:548
Method
__init__
(self, net, stds=[0.050, 0.100])
training/phema.py:96
Method
__init__
(self, net, halflife_Mimg=float('inf'), rampup_ratio=0.09)
training/phema.py:135
Method
__init__
(self, P_mean=-0.4, P_std=1.0, sigma_data=0.5)
training/training_loop.py:41
Method
__init__
(self, P_mean=-0.4, P_std=1.0, sigma_data=0.5)
training/training_loop.py:58
Method
__init__
(self, file_name: Optional[str] = None, file_mode: str = "w", should_flush: bool = True)
dnnlib/util.py:60
Method
__iter__
(self)
generate_images.py:201
Method
__iter__
(self)
calculate_metrics.py:189
Method
__iter__
(self)
torch_utils/misc.py:139
Method
__len__
(self)
generate_images.py:198
Method
__len__
(self)
datautils.py:118
Method
__len__
(self)
datautils.py:155
Method
__len__
(self)
datautils.py:192
Method
__len__
(self)
calculate_metrics.py:186
Method
__setattr__
(self, name: str, value: Any)
dnnlib/util.py:50
Function
_reconstruct_persistent_obj
r"""Hook that is called internally by the `pickle` module to unpickle a persistent object.
torch_utils/persistence.py:189
Function
assert_shape
(tensor, ref_shape)
torch_utils/misc.py:97
Function
calc
Calculate metrics for a given set of images.
calculate_metrics.py:390
Function
check_ddp_consistency
(module, ignore_regex=None)
torch_utils/misc.py:188
Function
const_like
(ref, value, shape=None, dtype=None, device=None, memory_format=None)
torch_utils/misc.py:59
Function
construct_class_by_name
Finds the python class with the given name and constructs it with the given arguments.
dnnlib/util.py:292
Function
copy_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:355
Function
copy_params_and_buffers
(src_module, dst_module, require_all=False)
torch_utils/misc.py:163
Function
ddp_sync
(module, sync)
torch_utils/misc.py:177
Method
decode
(self, x)
training/encoders.py:61
Function
decorator
(*args, **kwargs)
torch_utils/misc.py:116
Method
encode_latents
(self, x)
training/encoders.py:58
Method
encode_pixels
(self, x)
training/encoders.py:55
Function
exp_to_std
(exp)
training/phema.py:23
Function
format_time
Convert the seconds to human readable string with days, hours, minutes and seconds.
dnnlib/util.py:140
Function
format_time_brief
Convert the seconds to human readable string with days, hours, minutes and seconds.
dnnlib/util.py:154
Method
forward
(self, x)
training/models.py:94
Method
forward
(self, x, gain=1)
training/models.py:112
Method
forward
(self, x, emb)
training/models.py:162
Method
forward
(self, x, features, emb, geometry=None)
training/models.py:242
Method
forward
(self, x, noise_labels, geometry)
training/models.py:359
Method
forward
(self, x, features, noise_labels, geometry)
training/models.py:455
Method
forward
(self, x, noise_labels, geometry)
training/models.py:501
Method
forward
(self, src, dst, sigma, geometry=None, conditioning_image=None, force_fp32=False, return_logvar=False, return_
training/models.py:581
Function
gen
Calculate metrics for a given NVS model using default sampler settings.
calculate_metrics.py:419
Method
get
(self)
training/phema.py:116
Function
get_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:192
Function
get_module_dir_by_obj_name
Get the directory path of the module containing the given object name.
dnnlib/util.py:297
Function
get_top_level_function_name
Return the fully-qualified name of a top-level function.
dnnlib/util.py:308
Function
import_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:157
Function
init
()
torch_utils/distributed.py:23
Method
init_args
(self)
torch_utils/persistence.py:120
Method
init_kwargs
(self)
torch_utils/persistence.py:125
Function
init_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:37
Function
is_pickleable
(obj: Any)
dnnlib/util.py:215
Function
learning_rate_schedule
(cur_nimg, batch_size, ref_lr=100e-4, ref_batches=70e3, rampup_Mimg=10)
training/training_loop.py:81
Function
list_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:322
Method
load_state_dict
(self, state)
training/phema.py:125
Function
open_url
Download the given URL and return a binary-mode file object to access the data.
dnnlib/util.py:390
Function
params_and_buffers
(module)
torch_utils/misc.py:154
Function
parse_int_list
(s)
generate_images.py:267
Function
parse_metric_list
(s)
calculate_metrics.py:343
Function
parse_nimg
(s)
train_nvs.py:135
Function
pinned_buf
(shape, dtype)
torch_utils/misc.py:70
Function
post_hook
(mod, _inputs, outputs)
torch_utils/misc.py:215
Function
power_function_response
(ofs, std, len, axis=0)
training/phema.py:43
Function
pre_hook
(_mod, _inputs)
torch_utils/misc.py:213
Function
print_module_summary
(module, inputs, max_nesting=3, skip_redundant=True)
torch_utils/misc.py:205
Function
profiled_function
(fn)
torch_utils/misc.py:115
Method
randint
(self, *args, size, **kwargs)
generate_images.py:109
Function
report0
r"""Broadcasts the given set of scalars by the first process (`rank = 0`), but ignores any scalars provided by the other processes. See `repor
torch_utils/training_stats.py:109
Function
request_suspend
()
torch_utils/distributed.py:77
Method
reset
(self)
training/phema.py:103
Method
reset
(self)
training/phema.py:142
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