如何获取Tensorflow张量尺寸(形状)作为int值?
artificial-intelligence
machine-learning
python
tensorflow
6
0

假设我有一个Tensorflow张量。如何获取张量的尺寸(形状)为整数值?我知道有两种方法, tensor.get_shape()tf.shape(tensor) ,但我无法将形状值作为整数int32值获得。

例如,下面我创建了一个二维张量,我需要将行和列的数量获取为int32以便可以调用reshape()来创建一个形状为(num_rows * num_cols, 1)的张量。但是,方法tensor.get_shape()返回的值为Dimension类型,而不是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.
参考资料:
Stack Overflow
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共 3 个回答
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解决此问题的另一种方法是这样的:

tensor_shape[0].value

这将返回Dimension对象的int值。

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对于二维张量,可以使用以下代码将行和列的数量获取为int32:

rows, columns = map(lambda i: i.value, tensor.get_shape())
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要将形状作为一个整数列表,请执行tensor.get_shape().as_list()

要完成您的tf.shape()调用,请尝试tensor2 = tf.reshape(tensor, tf.TensorShape([num_rows*num_cols, 1])) 。或者,您可以直接执行tensor2 = tf.reshape(tensor, tf.TensorShape([-1, 1])) ,在此可以推断其第一维。

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