【tensorflow】shape与ndim

最新推荐文章于 2025-11-02 12:29:56 发布

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本文详细介绍了在TensorFlow中如何获取张量的形状和维度。通过使用`tensor.shape`和`tensor.get_shape()`可以得到张量的形状，而`tensor.shape.ndims`和`tensor.get_shape().ndims`则能获取张量的维度数。同时，文章指出`tf.shape(tensor)`返回的是维度数，而非形状。

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获取shape

import tensorflow as tf

tensor = tf.placeholder(dtype=tf.float32, shape=[200, 200, 3])

print('\n=========== get shape ============')
print('tensor                   : ', tensor)
print('tensor.shape             : ', tensor.shape)
print('tensor.get_shape()       : ', tensor.get_shape())

Print：

=========== get shape ============
tensor                   :  Tensor("Placeholder:0", shape=(200, 200, 3), dtype=float32)
tensor.shape             :  (200, 200, 3)
tensor.get_shape()       :  (200, 200, 3)

获取ndim

import tensorflow as tf

tensor = tf.placeholder(dtype=tf.float32, shape=[200, 200, 3])

print('\n=========== get dims ============')
print('tf.shape(tensor)         : ', tf.shape(tensor))
print('tensor.shape.ndims       : ', tensor.shape.ndims)
print('tensor.get_shape().ndims : ', tensor.get_shape().ndims)

Print：

=========== get dims ============
tf.shape(tensor)         :  Tensor("Shape:0", shape=(3,), dtype=int32)
tensor.shape.ndims       :  3
tensor.get_shape().ndims :  3