Functions — github.com/SubmissionsIn/DEMVC

CodeHub MCPcopy Create free account

hub / github.com/SubmissionsIn/DEMVC / functions

Functions24 in github.com/SubmissionsIn/DEMVC

⨍ Functions 24 ◇ Types & classes 3

↓ 2 callersMethod__init__

(self, filters=[32, 64, 128, 10], # view=2, n_clusters

↓ 2 callersFunction_make_data_and_model

↓ 2 callersMethodcompile

(self, optimizer='sgd', loss=['kld', 'mse'], loss_weights=[0.1, 1.0])

↓ 2 callersMethodfit

(self, arg, x, y, maxiter=2e4, batch_size=256, tol=1e-3, UpdateCoo=200, save_dir='./results/tmp')

↓ 2 callersMethodload_weights

(self, weights)

↓ 2 callersMethodtarget_distribution

↓ 1 callersFunctionBDGP

Load_data.py:90

↓ 1 callersFunctionFAE

(dims, act='relu', view=1)

↓ 1 callersFunctionGet_MNIST_USPS_COMIC

Load_data.py:18

↓ 1 callersFunctionMAE

(view=2, filters=[32, 64, 128, 10], view_shape = [1, 2, 3])

↓ 1 callersFunctionload_data_conv

Load_data.py:101

↓ 1 callersMethodpredict_label

↓ 1 callersMethodpretrain

(self, x, y, optimizer='adam', epochs=200, batch_size=256, save_dir='results/temp', verbose=

↓ 1 callersFunctiontest

↓ 1 callersFunctiontrain

↓ 1 callersMethodtrain_on_batch

(self, xin, yout, sample_weight=None)

(self, n_clusters, weights=None, alpha=1.0, **kwargs)

(self, x, y, flag=1)

Calculate clustering accuracy. Require scikit-learn installed # Arguments y: true labels, numpy.array with shape `(n_samples,)`

(self, input_shape)

student t-distribution, as same as used in t-SNE algorithm. q_ij = 1/(1+dist(x_i, u_j)^2), then normalize it. Arguments:

Methodcompute_output_shape

(self, input_shape)

Methodget_config

Methodon_epoch_end

(self, epoch, logs=None)