@samimoftheworld I don't deny the importance of getting gpu support in WSL, but TF does work with GPU in Windows. A quick test on my laptop:

2017-03-28 10:32:53.513855: I c:\tf_jenkins\home\workspace\nightly-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:887] Found device 0 with properties:
name: Quadro K1100M
major: 3 minor: 0 memoryClockRate (GHz) 0.7055
pciBusID 0000:02:00.0
Total memory: 2.00GiB
Free memory: 1.67GiB
2017-03-28 10:32:53.514049: I c:\tf_jenkins\home\workspace\nightly-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:908] DMA: 0
2017-03-28 10:32:53.517198: I c:\tf_jenkins\home\workspace\nightly-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:918] 0:   Y
2017-03-28 10:32:53.517950: I c:\tf_jenkins\home\workspace\nightly-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Quadro K1100M, pci bus id: 0000:02:00.0)
WARNING:tensorflow:Passing a `GraphDef` to the SummaryWriter is deprecated. Pass a `Graph` object instead, such as `sess.graph`.
Iteration: 0001 cost= 30.943873109
Iteration: 0003 cost= 21.104235386
Iteration: 0005 cost= 20.133856106
Iteration: 0007 cost= 19.718502910
Iteration: 0009 cost= 19.381666216`

GPU not accesssible for running tensorflow and installing CUDA #1788

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