tensorflow: tf.reshape does not accept Dimension objects for the shape parameter

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System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10 x64
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): 1.2.1
• Python version: 3.6.1 (Anaconda 4.4.0 64-bit)
• Bazel version (if compiling from source):
• CUDA/cuDNN version:
• GPU model and memory: GTX 780
• Exact command to reproduce: tf.reshape()

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https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh

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python -c “import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)”

Describe the problem

Describe the problem clearly here. Be sure to convey here why it’s a bug in TensorFlow or a feature request.

tf.reshape does not accept a list with mixed Integer and Dimension() as elements for the shape parameter. It should accept shapes that have Dimension as elements since tensor shapes consist of dimensions. Specifically, tf.tensor.shape returns a list of Dimensions, therefore using a similar object to specify a shape in tf.reshape should not cause an error.

Source code / logs

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Example code:

X = tf.placeholder("float", [1,784])
X = tf.reshape(X, [1, X.shape[-1]])

results in

TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [1, Dimension(784)]. Consider casting elements to a supported type.

This is rectified by casting X.shape[-1] to int before passing to tf.reshape.

A similar unrelated issue is that X.shape returns (784,) while it should return (1,784). This requires reshaping to turn the placeholder back into a 2D tensor. I haven’t determined if this is a bug but it occurs when the tensor is explicitly specified as a 2D tensor so it is probably worth changing.