Tensorflow reshape on convolution output gives TypeError
<p>When I try to reshape the output of a convolution using <code>tf.reshape()</code>, I get a TypeError</p>

<pre><code>TypeError: Expected binary or unicode string, got -1
</code></pre>

<p>The model I have written is:</p>

<pre><code>with tf.name_scope('conv1'):
    filter = tf.Variable(tf.truncated_normal([5, 5, 1, self.num_hidden / 2], mean=0.0,
                                             stddev=0.02, dtype=tf.float32),
                         name='filter')
    b = tf.Variable(tf.zeros([self.num_hidden / 2], dtype=tf.float32),
                    name='b')
    h1 = tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(inp, filter,
                                   [1, 2, 2, 1], padding='SAME'), b))
with tf.name_scope('conv2'):
    filter = tf.Variable(tf.truncated_normal([5, 5, self.num_hidden / 2, self.num_hidden], mean=0.0,
                                             stddev=0.02, dtype=tf.float32),
                         name='filter')
    b = tf.Variable(tf.zeros([self.num_hidden], dtype=tf.float32),
                    name='b')
    h2 = tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(h1, filter,
                                   [1, 2, 2, 1], padding='SAME'), b))
    # h2 -&gt; [-1, 7, 7, 32]
    # num_units -&gt; [-1, 1568]
    shape = h2.get_shape()
    num_units = shape[1]*shape[2]*shape[3]
with tf.name_scope('reshape'):
    h2_flattened = tf.reshape(h2, [-1, num_units])
    h2_flattened = tf.nn.dropout(h2_flattened, keep_prob=0.9)
with tf.name_scope('prediction'):
    W = tf.Variable(tf.truncated_normal([num_units, 1], mean=0.0, stddev=0.01,
                                        dtype=tf.float32), name='W')
    b = tf.Variable(tf.zeros([1], dtype=tf.float32), name='b')
    self.pred = tf.matmul(h2_flattened, W) + b
</code></pre>

<p>And the exact error I am getting is:</p>

<pre><code>Traceback (most recent call last):
  File "single_model_conv.py", line 108, in &lt;module&gt;
    gan = GAN(num_latent, 28, 'single')
  File "single_model_conv.py", line 23, in __init__
    self.adversary(self.gen_image)
  File "single_model_conv.py", line 93, in adversary
    h2_flattened = tf.reshape(h2, [-1, num_units])
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1977, in reshape
    name=name)
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 490, in apply_op
    preferred_dtype=default_dtype)
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 657, in convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 180, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 163, in constant
    tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape))
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 422, in make_tensor_proto
    tensor_proto.string_val.extend([compat.as_bytes(x) for x in proto_values])
  File "/nfs/nemo/u3/idurugkar/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/util/compat.py", line 64, in as_bytes
    (bytes_or_text,))
TypeError: Expected binary or unicode string, got -1
</code></pre>

<p>I don't understand why this is happening. It seems as if there is some error in converting the shape array into a tensor, but when I try and convert an arbitrary array to tensor it works.
I also tried converting all the dimensions to actual values (batch_size instead of -1), and that doesn't work either.</p>

<p>My tensorflow version is 0.11 and I am running it on a Linux machine with GPU support.</p>

<p>I had to do this before. Change this</p>

<pre><code>shape = h2.get_shape()
</code></pre>

<p>to this:</p>

<pre><code>shape = h2.get_shape().as_list()
</code></pre>

python tensorflow