MNIST Error (autoencoder)

MNIST error

In [10]: %run CNN_autoencoder.py
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\dso_loader.cc:128] successfully opened CUDA library cublas64_80.dll
locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\dso_loader.cc:119] Couldn't open CUDA library cudnn64_5.dll
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\cuda\cuda_dnn.cc:3459] Unable to load cuDNN DSO
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\dso_loader.cc:128] successfully opened CUDA library cufft64_80.dll l
ocally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\dso_loader.cc:128] successfully opened CUDA library nvcuda.dll local
ly
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\dso_loader.cc:128] successfully opened CUDA library curand64_80.dll
locally
Extracting MNIST_data/train-images-idx3-ubyte.gz
Extracting MNIST_data/train-labels-idx1-ubyte.gz
Extracting MNIST_data/t10k-images-idx3-ubyte.gz
Extracting MNIST_data/t10k-labels-idx1-ubyte.gz
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core
\common_runtime\gpu\gpu_device.cc:885] Found device 0 with properties:
name: GeForce GTX 965M
major: 5 minor: 2 memoryClockRate (GHz) 0.9495
pciBusID 0000:01:00.0
Total memory: 2.00GiB
Free memory: 1.86GiB
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core
\common_runtime\gpu\gpu_device.cc:906] DMA: 0
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core
\common_runtime\gpu\gpu_device.cc:916] 0:   Y
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core
\common_runtime\gpu\gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (d
evice: 0, name: GeForce GTX 965M, pci bus id: 0000:01:00.0)
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core
\common_runtime\gpu\gpu_device.cc:586] Could not identify NUMA node of /job:loca
lhost/replica:0/task:0/gpu:0, defaulting to 0.  Your kernel may not have been bu
ilt with NUMA support.
WARNING:tensorflow:From C:\Users\Gregoty\Programming\cs231n\repo\project\tensorf
low\autoencoder\CNN_autoencoder.py:188 in <module>.: initialize_all_variables (f
rom tensorflow.python.ops.variables) is deprecated and will be removed after 201
7-03-02.
Instructions for updating:
Use `tf.global_variables_initializer` instead.
number of test       =  10000
number of train      =  55000
number_of validation =  5000
Done splitting up test data set;
Starting training loop.
Epoch:  0
Shuffling the training data;
F c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stre
am_executor\cuda\cuda_dnn.cc:221] Check failed: s.ok() could not find cudnnCreat
e in cudnn DSO; dlerror: cudnnCreate not found

Getting same error. Have you resolved this problem?

EDIT: Solved this problem by downloading CUDNN from here

I downloaded CUDNN from NVIDIA but I am still having this same error. I added the bin folder to the PATH env variable, but still same issue.