In [1]:

    

# Import the required libs
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt


    

In [2]:

    

# Load the MNIST data
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)


    

    




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Extracting MNIST_data/t10k-labels-idx1-ubyte.gz

In [19]:

    

# Hyper-parameters
learn_rate = 0.01
train_epoches = 1
batch_size = 256
display_step = 1
example_to_show = 10

# NN structrue
num_hidden = 128
num_input = 784

# Input data
x = tf.placeholder(tf.float32, [None, num_input])

W = {
    'encoder': tf.Variable(tf.random_normal([num_input, num_hidden])),
    'decoder': tf.Variable(tf.random_normal([num_hidden, num_input]))
}
b = {
    'encoder': tf.Variable(tf.random_normal([num_hidden])),
    'decoder': tf.Variable(tf.random_normal([num_input]))
}


    

In [11]:

    

# Define the encoder and the decoder
def encoder(data, W, b):
    return tf.nn.sigmoid(tf.add(tf.matmul(data, W['encoder']),
                                b['encoder']))

def decoder(data, W, b):
    return tf.nn.sigmoid(tf.add(tf.matmul(data, W['decoder']),
                                b['decoder']))


    

In [14]:

    

# Prepare for the training
feature = encoder(x, W, b)
decoding = decoder(feature, W, b)

# Validation
y_expect = x
y_output = decoding

# Loss function and optimizer
cost = tf.reduce_mean(tf.pow(y_expect - y_output, 2))
optimizer = tf.train.RMSPropOptimizer(learn_rate).minimize(cost)

# Initialize all the adjustable variables
init = tf.global_variables_initializer()


    

In [20]:

    

# Start training
sess = tf.InteractiveSession()
sess.run(init)

total_batch = int(mnist.train.num_examples/batch_size)

for epoch in range(train_epoches):
    # Loop over all batches
    for i in range(total_batch):
        batch_xs, batch_ys = mnist.train.next_batch(batch_size)
        # Run optimization op (backprop) and cost op (to get loss value)
        _, c = sess.run([optimizer, cost], feed_dict={x: batch_xs})
    # Display logs per epoch step
    if epoch % display_step == 0:
        print("Epoch:", '%04d' % (epoch+1),
              "cost=", "{:.9f}".format(c))

print("Optimization Finished!")

# Applying encode and decode over test set
encode_decode = sess.run(
    y_pred, feed_dict={x: mnist.test.images[:examples_to_show]})
# Compare original images with their reconstructions
f, a = plt.subplots(2, 10, figsize=(10, 2))
for i in range(examples_to_show):
    a[0][i].imshow(np.reshape(mnist.test.images[i], (28, 28)))
    a[1][i].imshow(np.reshape(encode_decode[i], (28, 28)))
f.show()
plt.draw()


    

    




---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1020     try:
-> 1021       return fn(*args)
   1022     except errors.OpError as e:

/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
   1002                                  feed_dict, fetch_list, target_list,
-> 1003                                  status, run_metadata)
   1004 

/usr/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
     65             try:
---> 66                 next(self.gen)
     67             except StopIteration:

/usr/local/lib/python3.5/dist-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:

InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_3' with dtype float
	 [[Node: Placeholder_3 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-20-8ce4aad85bf4> in <module>()
     10         batch_xs, batch_ys = mnist.train.next_batch(batch_size)
     11         # Run optimization op (backprop) and cost op (to get loss value)
---> 12         _, c = sess.run([optimizer, cost], feed_dict={x: batch_xs})
     13     # Display logs per epoch step
     14     if epoch % display_step == 0:

/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    764     try:
    765       result = self._run(None, fetches, feed_dict, options_ptr,
--> 766                          run_metadata_ptr)
    767       if run_metadata:
    768         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
    962     if final_fetches or final_targets:
    963       results = self._do_run(handle, final_targets, final_fetches,
--> 964                              feed_dict_string, options, run_metadata)
    965     else:
    966       results = []

/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1012     if handle is None:
   1013       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1014                            target_list, options, run_metadata)
   1015     else:
   1016       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1032         except KeyError:
   1033           pass
-> 1034       raise type(e)(node_def, op, message)
   1035 
   1036   def _extend_graph(self):

InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_3' with dtype float
	 [[Node: Placeholder_3 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'Placeholder_3', defined at:
  File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/usr/local/lib/python3.5/dist-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "/usr/local/lib/python3.5/dist-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/usr/local/lib/python3.5/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/usr/local/lib/python3.5/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/usr/local/lib/python3.5/dist-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-9-d43173ba056b>", line 13, in <module>
    x = tf.placeholder('float', [None, num_input])
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 1512, in placeholder
    name=name)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 2043, in _placeholder
    name=name)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_3' with dtype float
	 [[Node: Placeholder_3 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]