Name		Name	Last commit message	Last commit date
parent directory ..
gen_img		gen_img
model		model
cogan_model.py		cogan_model.py
cogan_tb.png		cogan_tb.png
cogan_train.py		cogan_train.py
readme.md		readme.md

readme.md

Coupled Generative Adversarial Networks

Loss Function

used sce loss at D/G nets.

Architecture Networks

Same as CoGAN paper.

DIFFS	CoGAN Paper	ME
Pooling	`max_pooling2d`	`conv2d pooling`
G net	`5 fc layers`	`2 fc + 3 deconv2d layers`
conv2d filters	`D[20, 50]`	`D[32, 64]`
fc units	`D[500]`	`D[512]`

HE Initializer parameters : (factor = 1, FAN_AVG, uniform)

Tensorboard

Elapsed Time : 1h 3m 44s with GTX 1060 6GB x 1

Result

Name	Global Step 2.5k	Global Step 5k	Global Step 12.5k
Gen 1 (original)
Gen 2 (90° rotated)

To-Do