Fixing errors in board.py associated with deprecated tf attributes

[hermano360]

    import input_data

    from tensorflow.examples.tutorials.mnist import input_data
    mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

    import tensorflow as tf

    # Set parameters
    learning_rate = 0.01
    training_iteration = 30
    batch_size = 100
    display_step = 2

    # TF graph input
    x = tf.placeholder("float", [None, 784]) # mnist data image of shape 28*28=784
    y = tf.placeholder("float", [None, 10]) # 0-9 digits recognition => 10 classes

    # Create a model

    # Set model weights
    W = tf.Variable(tf.zeros([784, 10]))
    b = tf.Variable(tf.zeros([10]))

    with tf.name_scope("Wx_b") as scope:
        # Construct a linear model
        model = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax

    # Add summary ops to collect data
    w_h = tf.summary.histogram("weights", W)
    b_h = tf.summary.histogram("biases", b)

    # More name scopes will clean up graph representation
    with tf.name_scope("cost_function") as scope:
        # Minimize error using cross entropy
        # Cross entropy
        cost_function = -tf.reduce_sum(y*tf.log(model))
        # Create a summary to monitor the cost function
        tf.summary.scalar("cost_function", cost_function)

    with tf.name_scope("train") as scope:
        # Gradient descent
        optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost_function)

    # Initializing the variables
    init = tf.global_variables_initializer()

    # Merge all summaries into a single operator
    merged_summary_op = tf.summary.merge_all()

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

        # Change this to a location on your computer
        summary_writer = tf.summary.FileWriter('/LOCATION/ON/YOUR/COMPUTER/', sess.graph)

        # Training cycle
        for iteration in range(training_iteration):
            avg_cost = 0.
            total_batch = int(mnist.train.num_examples/batch_size)
            # Loop over all batches
            for i in range(total_batch):
                batch_xs, batch_ys = mnist.train.next_batch(batch_size)
                # Fit training using batch data
                sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})
                # Compute the average loss
                avg_cost += sess.run(cost_function, feed_dict={x: batch_xs, y: batch_ys})/total_batch
                # Write logs for each iteration
                summary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys})
                summary_writer.add_summary(summary_str, iteration*total_batch + i)
            # Display logs per iteration step
            if iteration % display_step == 0:
                print("Iteration:", '%04d' % (iteration + 1), "cost=", "{:.9f}".format(avg_cost))

        print("Tuning completed!")

        # Test the model
        predictions = tf.equal(tf.argmax(model, 1), tf.argmax(y, 1))
        # Calculate accuracy
        accuracy = tf.reduce_mean(tf.cast(predictions, "float"))
        print("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels}))

[alphamupsiomega]

Does not work with Tensorflow 1.1

InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_4' with dtype float
     [[Node: Placeholder_4 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op u'Placeholder_4', defined at:
  File "/Users/MY/anaconda/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/Users/MY/anaconda/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/Users/MY/anaconda/lib/python2.7/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/Users/MY/anaconda/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/Users/MY/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/Users/MY/anaconda/lib/python2.7/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-b93adf5d2e29>", line 7, in <module>
    x = tf.placeholder('float', [None, 28*28])
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1507, in placeholder
    name=name)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1997, in _placeholder
    name=name)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/Users/MY/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_4' with dtype float
     [[Node: Placeholder_4 = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]