MCPcopy Create free account

hub / github.com/anirudh9119/zforcing_nips17 / functions

Functions80 in github.com/anirudh9119/zforcing_nips17

↓ 12 callersMethodconcatenate
(self, batch)
blizzard_data.py:750
↓ 5 callersMethodinit_hidden
(self, bsz)
model.py:235
↓ 5 callersFunctionlog_prob_gaussian
(x, mu, log_vars, mean=False)
model.py:20
↓ 4 callersFunctionsegment_axis
Generate a new array that chops the given array along the given axis into overlapping frames. This code has been implemented by Anne Archibald
blizzard_data.py:32
↓ 3 callersMethod__init__
(self, c=1./3)
model.py:135
↓ 3 callersMethod_iter_data
(self, u, x, mask=None)
load.py:65
↓ 3 callersMethodload
(self, path)
blizzard_data.py:516
↓ 3 callersMethodload
(cls, filename)
model.py:218
↓ 3 callersMethodslices
(self)
blizzard_data.py:519
↓ 2 callersFunctionP2R
(magnitude, phase)
blizzard_data.py:828
↓ 2 callersFunctionR2P
(x)
blizzard_data.py:832
↓ 2 callersMethod__init__
(self, name=None, path=None, multi_process=0)
blizzard_data.py:500
↓ 2 callersMethodbwd_pass
(self, x, y, hidden)
model.py:330
↓ 2 callersFunctionevaluate
(dataset, model, split='valid')
train_timit.py:18
↓ 2 callersFunctionevaluate
(dataset, model, split='valid')
eval_timit.py:18
↓ 2 callersFunctionevaluate
(dataset, model)
train_blizzard.py:13
↓ 2 callersMethodfwd_pass
(self, x_fwd, hidden, bwd_states=None, z_step=None)
model.py:240
↓ 2 callersMethodget_test_batch
(self)
load.py:82
↓ 2 callersMethodget_valid_batch
(self)
load.py:79
↓ 2 callersMethodreparametrize
(self, mu, logvar, eps=None)
model.py:229
↓ 2 callersMethodsave
(self, filename)
model.py:198
↓ 1 callersMethodapply_fft
(self, batch)
blizzard_data.py:693
↓ 1 callersMethodapply_window
(self, batch)
blizzard_data.py:685
↓ 1 callersFunctionchunk
Yield successive n-sized chunks from sequence.
load.py:10
↓ 1 callersFunctioncomplex_to_real
WRITEME Parameters ---------- X : list of complex vectors Notes ----- This function assumes X as 2D
blizzard_data.py:132
↓ 1 callersFunctionfetch_blizzard
(data_path, shuffle=0, sz=32000, file_name="full_blizzard.h5")
blizzard_data.py:155
↓ 1 callersFunctionfetch_blizzard_tbptt
(data_path, sz=8000, batch_size=100, file_name="blizzard_tbptt.h5")
blizzard_data.py:220
↓ 1 callersFunctiongaussian_kld
Compute KL divergence between a bunch of univariate Gaussian distributions with the given means and log-variances. We do KL(N(mu_left, lo
model.py:32
↓ 1 callersFunctionget_batch
()
train_timit.py:19
↓ 1 callersFunctionget_batch
()
eval_timit.py:19
↓ 1 callersMethodget_train_batch
(self)
load.py:76
↓ 1 callersMethodinit_weights
Initialize parameters following the way proposed in the paper.
model.py:92
↓ 1 callersMethodirfft
Apply real inverse FFT to X (scipy) Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:371
↓ 1 callersFunctionis_power2
States if a number is a power of two (Author: A.Polino)
blizzard_data.py:836
↓ 1 callersMethodlog_magnitude
(self, batch)
blizzard_data.py:708
↓ 1 callersMethodnum_examples
(self)
blizzard_data.py:523
↓ 1 callersMethodnumpy_irfft
Apply real inverse FFT to X (numpy) Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:351
↓ 1 callersMethodnumpy_rfft
Apply real FFT to X (numpy) Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:341
↓ 1 callersMethodrfft
Apply real FFT to X (scipy) Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:361
↓ 1 callersFunctionrun
(model, data)
eval_timit.py:45
↓ 1 callersFunctiontotuple
(arg)
blizzard_data.py:23
↓ 1 callersFunctiontrain
(expname, nlayers, seed, num_epochs, rnn_dim, data, bsz, lr, z_dim, emb_dim, mlp_dim, aux_end, aux_s
train_timit.py:58
↓ 1 callersFunctiontrain
(expname, nlayers, seed, num_epochs, rnn_dim, data, bsz, lr, z_dim, emb_dim, mlp_dim, aux_sta, aux_e
train_blizzard.py:47
Method__init__
(self, X_mean=None, X_std=None, shuffle=0,
blizzard_data.py:585
Method__init__
(self, batch_size=100, file_name='blizzard_tbptt', range_st
blizzard_data.py:772
Method__init__
(self, fn, batch_size)
load.py:17
Method__init__
(self, data, batch_size=None, nbatch=None, start=0, end=None, shuffle=False, infinite_data=0,
load.py:88
Method__init__
(self, nb_features, eps=1e-5)
model.py:46
Method__init__
Most parts are copied from torch.nn.LSTMCell.
model.py:67
Method__init__
(self, inp_dim, emb_dim, rnn_dim, z_dim, mlp_dim, out_dim, out_type="gaussian",
model.py:144
Method__iter__
(self)
load.py:114
Method__repr__
(self)
model.py:129
Methodapply_ifft
(self, batch)
blizzard_data.py:702
Methodcreate_mask
(self, batch)
blizzard_data.py:544
Methodcreate_mask_and_zero_pad
(self, batch)
blizzard_data.py:560
Methodfill_zero
Given variable lengths sequences, pad zeros w.r.t to the maximum length sequences and create a dense design matrix
blizzard_data.py:430
Methodfill_zero1D
Given variable lengths sequences, pad zeros w.r.t to the maximum length sequences and create a dense design matrix
blizzard_data.py:401
Methodforward
(self, x, gain=None, bias=None)
model.py:52
Methodforward
Args: input_: A (batch, input_size) tensor containing input features. hx: A tuple (h_0, c_0), which c
model.py:103
Methodforward
(self, x)
model.py:139
Methodforward
(self, x, y, x_mask, hidden, return_stats=False)
model.py:345
Methodglobal_normalize
Globally normalize X into zero mean and unit variance Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:301
Methodinfer
Infer latent variables for a given batch of sentences ``x''.
model.py:320
Methodistft
Apply short-time Fourier transform to X Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:391
Methodload
(self, data_path)
blizzard_data.py:622
Methodload
(self, data_path)
blizzard_data.py:784
Functionlog_prob_bernoulli
(x, mu)
model.py:27
Methodmulti_process_slices
(self, mid=-1)
blizzard_data.py:512
Methodnorm_normalize
Unify the norm of each sequence in X Parameters ---------- X : list of lists or ndArrays avr_nom : Scal
blizzard_data.py:282
Methodpow_magnitude
(self, batch)
blizzard_data.py:729
Methodreverse
Reverse each sequence of X Parameters ---------- X : list of ndArrays or lists
blizzard_data.py:480
Methodslices
(self, start, end)
blizzard_data.py:540
Methodslices
(self, start, end)
blizzard_data.py:665
Methodstandardize
Standardize X such that X \in [0, 1] Parameters ---------- X : list of lists or ndArrays X_max : Scalar
blizzard_data.py:324
Methodstft
Apply short-time Fourier transform to X Parameters ---------- X : list of lists or ndArrays
blizzard_data.py:381
Methodtest_theano_vars
(self)
blizzard_data.py:662
Methodtheano_vars
(self)
blizzard_data.py:526
Methodtheano_vars
(self)
blizzard_data.py:659
Functiontolist
(arg)
blizzard_data.py:14
Methodzero_pad
(self, batch)
blizzard_data.py:552