TensorFlow是Google设计的开源Python库,用于开发机器学习模型和深度学习神经网络。
tensorflow.eye()用于生成单位矩阵。
用法:tensorflow.eye( num_rows, num_columns, batch_shape, dtype, name)
参数:
- num_rows:它是int32标量张量,它定义了结果矩阵中存在的行数。
- num_columns(可选):它是int32标量张量,它定义了结果矩阵中存在的列数。默认值为num_rows。
- batch_shape(可选):它是Python整数或一维int32 Tensor的列表或元组。如果不是全部,返回的Tensor将具有这种形状的前导批量尺寸。
- dtype(optional):它定义了返回张量的dtype。默认值为float32。
- name(optional):它定义了操作的名称。
返回:它返回形状为batch_shape + [num_rows,num_columns]的张量。
范例1:
Python3
# Importing the library
import tensorflow as tf
# Initializing the input
num_rows = 5
# Printing the input
print('num_rows:', num_rows)
# Calculating result
res = tf.eye(num_rows)
# Printing the result
print('res:', res)
输出:
num_rows:5 res: tf.Tensor( [[1. 0. 0. 0. 0.] [0. 1. 0. 0. 0.] [0. 0. 1. 0. 0.] [0. 0. 0. 1. 0.] [0. 0. 0. 0. 1.]], shape=(5, 5), dtype=float32)
范例2:
Python3
# Importing the library
import tensorflow as tf
# Initializing the input
num_rows = 5
num_columns = 6
batch_shape = [3]
# Printing the input
print('num_rows:', num_rows)
print('num_columns:', num_columns)
print('batch_shape:', batch_shape)
# Calculating result
res = tf.eye(num_rows, num_columns, batch_shape)
# Printing the result
print('res:', res)
输出:
num_rows:5 num_columns:6 batch_shape:[3] res: tf.Tensor( [[[1. 0. 0. 0. 0. 0.] [0. 1. 0. 0. 0. 0.] [0. 0. 1. 0. 0. 0.] [0. 0. 0. 1. 0. 0.] [0. 0. 0. 0. 1. 0.]] [[1. 0. 0. 0. 0. 0.] [0. 1. 0. 0. 0. 0.] [0. 0. 1. 0. 0. 0.] [0. 0. 0. 1. 0. 0.] [0. 0. 0. 0. 1. 0.]] [[1. 0. 0. 0. 0. 0.] [0. 1. 0. 0. 0. 0.] [0. 0. 1. 0. 0. 0.] [0. 0. 0. 1. 0. 0.] [0. 0. 0. 0. 1. 0.]]], shape=(3, 5, 6), dtype=float32)
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