stackoverflowuser2010 - 1 year ago 922

Python Question

Suppose I have a Tensorflow tensor. How do I get the the dimensions (shape) of the tensor as integer values? I know there are two methods,

`tensor.get_shape()`

`tf.shape(tensor)`

For example, in the code 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()`

`(num_rows * num_cols, 1)`

`tensor.get_shape()`

`Dimension`

`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[0] # ???

num_cols = tensor_shape[1] # ???

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.

Answer Source

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.