Functions — github.com/anantzoid/Conditional-PixelCNN-decoder

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Functions19 in github.com/anantzoid/Conditional-PixelCNN-decoder

⨍ Functions 19 ◇ Types & classes 3

↓ 9 callersFunctionget_weights

(shape, name, horizontal, mask_mode='noblind', mask=None)

↓ 7 callersFunctionget_bias

↓ 7 callersMethodoutput

↓ 6 callersFunctionconv_op

↓ 5 callersFunctionbinarize

↓ 3 callersFunctionget_batch

(data, pointer, batch_size)

↓ 2 callersFunctiongenerate_ae

(sess, encoder_X, decoder_X, y, data, conf, suff='')

↓ 2 callersFunctiongenerate_samples

(sess, X, h, pred, conf, suff)

↓ 2 callersFunctionmax_pool_2x2

↓ 2 callersFunctionone_hot

(batch_y, num_classes)

↓ 2 callersFunctionsave_images

(samples, n_row, n_col, conf, suff)

↓ 2 callersFunctiontrain

↓ 1 callersMethodgated_conv

↓ 1 callersFunctionmakepaths

↓ 1 callersMethodsimple_conv

↓ 1 callersFunctiontrainAE

autoencoder.py:6

(self, W_shape, fan_in, horizontal, gated=True, payload=None, mask=None, activation=True, conditional=None, co

(self, X, conf, full_horizontal=True, h=None)

This is the 6-layer architecture for Convolutional Autoencoder mentioned in the original paper: Stacked Convolut