In [7]:

    

import numpy as np
import tensorflow as tf

xy = np.loadtxt('data/xor_data.txt', unpack=True)

x_data = np.transpose( xy[0:-1] )
y_data = np.reshape( xy[-1], (4,1) )

X = tf.placeholder(tf.float32, name = 'X-input')
Y = tf.placeholder(tf.float32, name = 'Y-input')

# Deep network configuration.: Use more layers. 
W1 = tf.Variable(tf.random_uniform( [2,5], -1.0, 1.0),name = 'weight1')
W2 = tf.Variable(tf.random_uniform( [5,4], -1.0, 1.0),name = 'weight2')
W3 = tf.Variable(tf.random_uniform( [4,1], -1.0, 1.0),name = 'weight3')

b1 = tf.Variable(tf.zeros([5]), name="bias1")
b2 = tf.Variable(tf.zeros([4]), name="bias2")
b3 = tf.Variable(tf.zeros([1]), name="bias3")

# Add histogram
w1_hist = tf.summary.histogram("weights1", W1)
w2_hist = tf.summary.histogram("weights2", W2)
w3_hist = tf.summary.histogram("weights3", W3)

b1_hist = tf.summary.histogram("biases1", b1)
b2_hist = tf.summary.histogram("biases2", b2)
b3_hist = tf.summary.histogram("biases3", b3)

y_hist = tf.summary.histogram("y", Y)


# Hypotheses 
with tf.name_scope("layer2") as scope:
    L2 =  tf.sigmoid(tf.matmul(X,W1)+b1)

with tf.name_scope("layer3") as scope:
    L3 =  tf.sigmoid(tf.matmul(L2,W2)+b2)

with tf.name_scope("layer4") as scope:
    hypothesis = tf.sigmoid( tf.matmul(L3,W3) + b3)

# Cost function 
with tf.name_scope("cost") as scope:
    cost = -tf.reduce_mean( Y*tf.log(hypothesis)+(1-Y)* tf.log(1.-hypothesis) )
    cost_summ = tf.summary.scalar("cost", cost)
    
# Minimize cost.
a = tf.Variable(0.1)
with tf.name_scope("train") as scope:
    optimizer = tf.train.GradientDescentOptimizer(a)
    train = optimizer.minimize(cost)

# Initializa all variables.
init = tf.global_variables_initializer()


# Launch the graph
with tf.Session() as sess:

    # tensorboard merge
    merged = tf.summary.merge_all()
    writer = tf.summary.FileWriter("./logs/xor_logs", sess.graph)
    
    sess.run(init)

    # Run graph.
    for step in range(20001):
        sess.run(train, feed_dict={X:x_data, Y:y_data})
        if step % 2000 == 0:
            summary, _ = sess.run( [merged, train], feed_dict={X:x_data, Y:y_data})
            writer.add_summary(summary, step)
    
    # Test model
    correct_prediction = tf.equal( tf.floor(hypothesis+0.5), Y)
    accuracy = tf.reduce_mean(tf.cast( correct_prediction, "float" ) )
    
    # Check accuracy
    print( sess.run( [hypothesis, tf.floor(hypothesis+0.5), correct_prediction, accuracy], 
                   feed_dict={X:x_data, Y:y_data}) )
    print( "Accuracy:", accuracy.eval({X:x_data, Y:y_data}) )


    

    




---------------------------------------------------------------------------
InternalError                             Traceback (most recent call last)
/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1021     try:
-> 1022       return fn(*args)
   1023     except errors.OpError as e:

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
   1003                                  feed_dict, fetch_list, target_list,
-> 1004                                  status, run_metadata)
   1005 

/usr/local/lib/python3.6/contextlib.py in __exit__(self, type, value, traceback)
     88             try:
---> 89                 next(self.gen)
     90             except StopIteration:

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
    468           compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 469           pywrap_tensorflow.TF_GetCode(status))
    470   finally:

InternalError: Blas SGEMM launch failed : a.shape=(4, 2), b.shape=(2, 5), m=4, n=5, k=2
	 [[Node: layer2_3/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](_recv_X-input_4_0/_3, weight1_4/read)]]

During handling of the above exception, another exception occurred:

InternalError                             Traceback (most recent call last)
<ipython-input-7-8e7a0f0a8425> in <module>()
     67     # Run graph.
     68     for step in range(20001):
---> 69         sess.run(train, feed_dict={X:x_data, Y:y_data})
     70         if step % 2000 == 0:
     71             summary, _ = sess.run( [merged, train], feed_dict={X:x_data, Y:y_data})

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    765     try:
    766       result = self._run(None, fetches, feed_dict, options_ptr,
--> 767                          run_metadata_ptr)
    768       if run_metadata:
    769         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
    963     if final_fetches or final_targets:
    964       results = self._do_run(handle, final_targets, final_fetches,
--> 965                              feed_dict_string, options, run_metadata)
    966     else:
    967       results = []

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1013     if handle is None:
   1014       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1015                            target_list, options, run_metadata)
   1016     else:
   1017       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1033         except KeyError:
   1034           pass
-> 1035       raise type(e)(node_def, op, message)
   1036 
   1037   def _extend_graph(self):

InternalError: Blas SGEMM launch failed : a.shape=(4, 2), b.shape=(2, 5), m=4, n=5, k=2
	 [[Node: layer2_3/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](_recv_X-input_4_0/_3, weight1_4/read)]]

Caused by op 'layer2_3/MatMul', defined at:
  File "/usr/local/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/local/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/zmq/eventloop/ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-7-8e7a0f0a8425>", line 35, in <module>
    L2 =  tf.sigmoid(tf.matmul(X,W1)+b1)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 1855, in matmul
    a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 1454, in _mat_mul
    transpose_b=transpose_b, name=name)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
    op_def=op_def)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/jhdybpark/.virtualenvs/python36/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1264, in __init__
    self._traceback = _extract_stack()

InternalError (see above for traceback): Blas SGEMM launch failed : a.shape=(4, 2), b.shape=(2, 5), m=4, n=5, k=2
	 [[Node: layer2_3/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](_recv_X-input_4_0/_3, weight1_4/read)]]