# How to get Tensorflow tensor dimensions (shape) as int values?

Suppose I have a Tensorflow tensor. How do I get the dimensions (shape) of the tensor as integer values? I know there are two methods, `tensor.get_shape()` and `tf.shape(tensor)`, but I can't get the shape values as integer `int32` values.

For example, below I've created a 2-D tensor, and I need to get the number of rows and columns as `int32` so that I can call `reshape()` to create a tensor of shape `(num_rows * num_cols, 1)`. However, the method `tensor.get_shape()` returns values as `Dimension` type, not `int32`.

```    import tensorflow as tf
import numpy as np

sess = tf.Session()
tensor = tf.convert_to_tensor(np.array([[1001,1002,1003],[3,4,5]]), dtype=tf.float32)

sess.run(tensor)
# array([[ 1001.,  1002.,  1003.],
#        [    3.,     4.,     5.]], dtype=float32)

tensor_shape = tensor.get_shape()
tensor_shape
# TensorShape([Dimension(2), Dimension(3)])
print tensor_shape
# (2, 3)

num_rows = tensor_shape # ???
num_cols = tensor_shape # ???

tensor2 = tf.reshape(tensor, (num_rows*num_cols, 1))
# Traceback (most recent call last):
#   File "<stdin>", line 1, in <module>
#   File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1750, in reshape
#     name=name)
#   File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 454, in apply_op
#     as_ref=input_arg.is_ref)
#   File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 621, in convert_to_tensor
#     ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
#   File "/usr/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 "/usr/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 "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 353, in make_tensor_proto
#     _AssertCompatible(values, dtype)
#   File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 290, in _AssertCompatible
#     (dtype.name, repr(mismatch), type(mismatch).__name__))
# TypeError: Expected int32, got Dimension(6) of type 'Dimension' instead.
```

To get the shape as a list of ints, do `tensor.get_shape().as_list()`.

To complete your `tf.shape()` call, try `tensor2 = tf.reshape(tensor, tf.TensorShape([num_rows*num_cols, 1]))`. Or you can directly do `tensor2 = tf.reshape(tensor, tf.TensorShape([-1, 1]))` where its first dimension can be inferred.

From: stackoverflow.com/q/40666316