TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
tensorflow.eye() is used to generate identity matrix.
Syntax: tensorflow.eye( num_rows, num_columns, batch_shape, dtype, name)
Parameters:
- num_rows: It is int32 scalar Tensor which defines the number of rows to be present in resulting matrix.
- num_columns(optional): It is int32 scalar Tensor which defines the number of columns to be present in resulting matrix. It’s default value is num_rows.
- batch_shape(optional): It is list or tuple of Python integers or a 1-D int32 Tensor. If it’s not none the returned Tensor will have leading batch dimensions of this shape.
- dtype(optional): It defines the dtype of returned tensor. Default value is float32.
- name(optional): It defines the name for the operation.
Return : It returns a Tensor of shape batch_shape + [num_rows, num_columns].
Example 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) |
Output:
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)
Example 2:
Python3
# Importing the library import tensorflow as tf # Initializing the input num_rows = 5num_columns = 6batch_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) |
Output:
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)
