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Functions44 in github.com/NVIDIA/waveglow

↓ 5 callersFunctionremove
(conv_list)
glow.py:306
↓ 3 callersMethod__init__
(self, n_in_channels, n_mel_channels, n_layers, n_channels, kernel_size)
glow.py:111
↓ 3 callersFunctionfiles_to_list
Takes a text file of filenames and makes a list of filenames
mel2samp.py:42
↓ 2 callersMethodget_mel
(self, audio)
mel2samp.py:78
↓ 2 callersMethodinfer
(self, spect, sigma=1.0)
glow.py:251
↓ 2 callersFunctionload_wav_to_torch
Loads wavdata into torch array
mel2samp.py:52
↓ 1 callersMethod__init__
(self, n_in_channels, n_mel_channels, n_layers, n_channels, kernel_size)
glow_old.py:22
↓ 1 callersFunction_check_model_old_version
(model)
convert_model.py:5
↓ 1 callersFunction_flatten_dense_tensors
Flatten dense tensors into a contiguous 1D buffer. Assume tensors are of same dense type. Since inputs are dense, the resulting tensor will be
distributed.py:55
↓ 1 callersFunction_unflatten_dense_tensors
View a flat buffer using the sizes of tensors. Assume that tensors are of same dense type, and that flat is given by _flatten_dense_tensors. A
distributed.py:71
↓ 1 callersFunction_update_model_cond
(old_model, new_model)
convert_model.py:37
↓ 1 callersFunction_update_model_res_skip
(old_model, new_model)
convert_model.py:12
↓ 1 callersFunctionapply_gradient_allreduce
Modifies existing model to do gradient allreduce, but doesn't change class so you don't need "module"
distributed.py:90
↓ 1 callersFunctionfused_add_tanh_sigmoid_multiply
(input_a, input_b, n_channels)
glow.py:34
↓ 1 callersFunctionfused_add_tanh_sigmoid_multiply
(input_a, input_b, n_channels)
glow_old.py:7
↓ 1 callersFunctioninit_distributed
(rank, num_gpus, group_name, dist_backend, dist_url)
distributed.py:43
↓ 1 callersFunctionload_checkpoint
(checkpoint_path, model, optimizer)
train.py:41
↓ 1 callersFunctionmain
(config, stdout_dir, args_str)
distributed.py:145
↓ 1 callersFunctionmain
(mel_files, waveglow_path, sigma, output_dir, sampling_rate, is_fp16, denoiser_strength)
inference.py:34
↓ 1 callersFunctionreduce_tensor
(tensor, num_gpus)
distributed.py:37
↓ 1 callersMethodremove_weightnorm
(model)
glow.py:296
↓ 1 callersFunctionsave_checkpoint
(model, optimizer, learning_rate, iteration, filepath)
train.py:52
↓ 1 callersFunctiontrain
(num_gpus, rank, group_name, output_directory, epochs, learning_rate, sigma, iters_per_checkpoint, b
train.py:62
↓ 1 callersFunctionupdate_model
(old_model)
convert_model.py:56
Method__getitem__
(self, index)
mel2samp.py:86
Method__init__
(self, training_files, segment_length, filter_length, hop_length, win_length, sampling_rate,
mel2samp.py:65
Method__init__
(self, sigma=1.0)
glow.py:44
Method__init__
(self, c)
glow.py:68
Method__init__
(self, n_mel_channels, n_flows, n_group, n_early_every, n_early_size, WN_config)
glow.py:179
Method__init__
(self, n_mel_channels, n_flows, n_group, n_early_every, n_early_size, WN_config)
glow_old.py:90
Method__init__
(self, waveglow, filter_length=1024, n_overlap=4, win_length=1024, mode='zeros')
denoiser.py:10
Method__len__
(self)
mel2samp.py:107
Functionallreduce_hook
(*unused)
distributed.py:132
Functionallreduce_params
()
distributed.py:105
Methodforward
(self, model_output)
glow.py:48
Methodforward
(self, z, reverse=False)
glow.py:82
Methodforward
(self, forward_input)
glow.py:153
Methodforward
forward_input[0] = mel_spectrogram: batch x n_mel_channels x frames forward_input[1] = audio: batch x time
glow.py:207
Methodforward
(self, forward_input)
glow_old.py:65
Methodforward
(self, forward_input)
glow_old.py:118
Methodforward
(self, audio, strength=0.1)
denoiser.py:35
Methodinfer
(self, spect, sigma=1.0)
glow_old.py:172
Methodremove_weightnorm
(model)
glow_old.py:226
Functionset_needs_reduction
(self, input, output)
distributed.py:138