I want to run `tensorflow` code on my GPU but its not working. I have Cuda and cuDNN installed and have a compatible GPU as well.

I took this sample from the official website tutorial for GPUs here [Tensorflow tutorial for GPU](https://www.tensorflow.org/tutorials/using_gpu)

```
# Creates a graph.
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)
# Creates a session with log_device_placement set to True.
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
# Runs the op.
print(sess.run(c))

```

Here is my output of it:

```
Device mapping: no known devices.
2017-10-31 16:15:40.298845: I tensorflow/core/common_runtime/direct_session.cc:300] Device mapping:

MatMul: (MatMul): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.895802: I tensorflow/core/common_runtime/simple_placer.cc:872] MatMul: (MatMul)/job:localhost/replica:0/task:0/cpu:0
b: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.895910: I tensorflow/core/common_runtime/simple_placer.cc:872] b: (Const)/job:localhost/replica:0/task:0/cpu:0
a_1: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.895961: I tensorflow/core/common_runtime/simple_placer.cc:872] a_1: (Const)/job:localhost/replica:0/task:0/cpu:0
a: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-10-31 16:15:56.896006: I tensorflow/core/common_runtime/simple_placer.cc:872] a: (Const)/job:localhost/replica:0/task:0/cpu:0
[[ 22.  28.]
 [ 49.  64.]]

```

There is no option for running on my GPU. I tried to force it to run on GPU manually using this:

```
with tf.device('/gpu:0'):
...

```

It gave a bunch of errors:

```
Traceback (most recent call last):
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
    return fn(*args)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1297, in _run_fn
    self._extend_graph()
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1358, in _extend_graph
    self._session, graph_def.SerializeToString(), status)
  File "/home/abhor/anaconda3/lib/python3.6/contextlib.py", line 88, in __exit__
    next(self.gen)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation 'MatMul_1': Operation was explicitly assigned to /device:GPU:0 but available devices are [ /job:localhost/replica:0/task:0/cpu:0 ]. Make sure the device specification refers to a valid device.
     [[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/device:GPU:0"](a_2, b_1)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 895, in run
    run_metadata_ptr)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1124, in _run
    feed_dict_tensor, options, run_metadata)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
    options, run_metadata)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for operation 'MatMul_1': Operation was explicitly assigned to /device:GPU:0 but available devices are [ /job:localhost/replica:0/task:0/cpu:0 ]. Make sure the device specification refers to a valid device.
     [[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/device:GPU:0"](a_2, b_1)]]

Caused by op 'MatMul_1', defined at:
  File "<stdin>", line 4, in <module>
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 1844, in matmul
    a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 1289, in _mat_mul
    transpose_b=transpose_b, name=name)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/abhor/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1204, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Cannot assign a device for operation 'MatMul_1': Operation was explicitly assigned to /device:GPU:0 but available devices are [ /job:localhost/replica:0/task:0/cpu:0 ]. Make sure the device specification refers to a valid device.
     [[Node: MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/device:GPU:0"](a_2, b_1)]]

```

I see that in some lines it says only CPU is available.

Here are my graphic card details and Cuda versions.

Output for `nvidia-smi`:

```
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.81                 Driver Version: 384.81                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce 940MX       Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   43C    P0    N/A /  N/A |    274MiB /  2002MiB |     10%      Default |
+-------------------------------+----------------------+----------------------+

```

Output for `nvcc -V`

```
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176

```

I don't know how to check for cuDNN, but I installed it the way it was given in the official documentation, so I am guessing it should be working as well.

EDIT:
Output for `pip3 list | grep tensorflow`

```
tensorflow-gpu (1.3.0)
tensorflow-tensorboard (0.1.8)

```