title: Tensorflow: runn error with reader_test.py in models.tutorials.rnn
body: <p>I use anaconda2 with python 3.5 based tensorflow-gpu environment in wind10. I test the installation of tensorflow (v1.2) by run:</p>
  
  <pre><code>import tensorflow as tf
  hello = tf.constant('Hello, TensorFlow!')
  sess = tf.Session()
  print(sess.run(hello))
  </code></pre>
  
  <p>There is no problem with the installation. </p>
  
  <p>Then I further test it by running two the provided examples: </p>
  
  <pre><code>reader_test.py 
  ptb_word_lm.py #this is to use LSTM to model penntree bank data
  </code></pre>
  
  <p>But the two programs cannot be run successfully:</p>
  
  <p>For the first case:
  <a href="https://i.stack.imgur.com/js1zG.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/js1zG.png" alt="enter image description here"></a></p>
  
  <p>For the second case:</p>
  
  <pre><code>#implementation in anaconda prompt
  (tensorflow-gpu) D:\Research\Manuscript\Simplified LSTM\models-master\models-master\tutorials\rnn\ptb&gt;python ptb_word_lm.py --data_path=D:\simple-examples\data
  </code></pre>
  
  <p>Resultant error messages:</p>
  
  <pre><code>2017-06-30 18:06:05.819002: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819089: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819770: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819816: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819843: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819866: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819889: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:05.819911: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
  2017-06-30 18:06:06.317871: I c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:940] Found device 0 with properties:
  name: GeForce 940M
  major: 5 minor: 0 memoryClockRate (GHz) 1.176
  pciBusID 0000:01:00.0
  Total memory: 2.00GiB
  Free memory: 1.66GiB
  2017-06-30 18:06:06.317961: I c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:961] DMA: 0
  2017-06-30 18:06:06.321380: I c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:971] 0:   Y
  2017-06-30 18:06:06.322688: I c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\core\common_runtime\gpu\gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -&gt; (device: 0, name: GeForce 940M, pci bus id: 0000:01:00.0)
  WARNING:tensorflow:Standard services need a 'logdir' passed to the SessionManager
  Epoch: 1 Learning rate: 1.000
  2017-06-30 18:06:11.106452: E c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\stream_executor\cuda\cuda_blas.cc:365] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
  2017-06-30 18:06:11.106573: W c:\tf_jenkins\home\workspace\release-win\m\windows-gpu\py\35\tensorflow\stream_executor\stream.cc:1601] attempting to perform BLAS operation using StreamExecutor without BLAS support
  Traceback (most recent call last):
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1139, in _do_call
      return fn(*args)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1121, in _run_fn
      status, run_metadata)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\contextlib.py", line 66, in __exit__
      next(self.gen)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\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.InternalError: Blas GEMM launch failed : a.shape=(20, 400), b.shape=(400, 800), m=20, n=800, k=400
           [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/concat, Model/RNN/multi_rnn_cell/cell_0/basic_lstm_cell/kernel/read)]]
           [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39/_123 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_6049_Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
  
  During handling of the above exception, another exception occurred:
  
  Traceback (most recent call last):
    File "ptb_word_lm.py", line 395, in &lt;module&gt;
      tf.app.run()
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\platform\app.py", line 48, in run
      _sys.exit(main(_sys.argv[:1] + flags_passthrough))
    File "ptb_word_lm.py", line 381, in main
      verbose=True)
    File "ptb_word_lm.py", line 310, in run_epoch
      vals = session.run(fetches, feed_dict)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 789, in run
      run_metadata_ptr)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 997, in _run
      feed_dict_string, options, run_metadata)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1132, in _do_run
      target_list, options, run_metadata)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _do_call
      raise type(e)(node_def, op, message)
  tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(20, 400), b.shape=(400, 800), m=20, n=800, k=400
           [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/concat, Model/RNN/multi_rnn_cell/cell_0/basic_lstm_cell/kernel/read)]]
           [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39/_123 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_6049_Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
  
  Caused by op 'Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/MatMul', defined at:
    File "ptb_word_lm.py", line 395, in &lt;module&gt;
      tf.app.run()
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\platform\app.py", line 48, in run
      _sys.exit(main(_sys.argv[:1] + flags_passthrough))
    File "ptb_word_lm.py", line 357, in main
      m = PTBModel(is_training=True, config=config, input_=train_input)
    File "ptb_word_lm.py", line 157, in __init__
      (cell_output, state) = cell(inputs[:, time_step, :], state)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 180, in __call__
      return super(RNNCell, self).__call__(inputs, state)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\layers\base.py", line 441, in __call__
      outputs = self.call(inputs, *args, **kwargs)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 916, in call
      cur_inp, new_state = cell(cur_inp, cur_state)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 180, in __call__
      return super(RNNCell, self).__call__(inputs, state)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\layers\base.py", line 441, in __call__
      outputs = self.call(inputs, *args, **kwargs)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 383, in call
      concat = _linear([inputs, h], 4 * self._num_units, True)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 1021, in _linear
      res = math_ops.matmul(array_ops.concat(args, 1), weights)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1816, in matmul
      a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1217, in _mat_mul
      transpose_b=transpose_b, name=name)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
      op_def=op_def)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\framework\ops.py", line 2506, in create_op
      original_op=self._default_original_op, op_def=op_def)
    File "C:\Users\Y L\Anaconda2\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\framework\ops.py", line 1269, in __init__
      self._traceback = _extract_stack()
  
  
  
  InternalError (see above for traceback): Blas GEMM launch failed : a.shape=(20, 400), b.shape=(400, 800), m=20, n=800, k=400
                   [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Train/Model/RNN/RNN/multi_rnn_cell/cell_0/cell_0/basic_lstm_cell/basic_lstm_cell/concat, Model/RNN/multi_rnn_cell/cell_0/basic_lstm_cell/kernel/read)]]
                   [[Node: Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39/_123 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_6049_Train/Model/RNN/RNN/multi_rnn_cell/cell_1/cell_1/basic_lstm_cell/add_39", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
  </code></pre>