TensorFlow is an open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. While working with TensorFlow many times we need to generate evenly-spaced values in an interval.
- tensorflow.linspace(): This method takes starting tensor, ending tensor, number of values and axis and returns a Tensor with specified number of evenly spaced values.
Example 1:
python3
# importing the libraryimport tensorflow as tf# Initializing Inputstart = tf.constant(1, dtype = tf.float64)end = tf.constant(5, dtype = tf.float64)num = 5# Printing the Inputprint("start: ", start)print("end: ", end)print("num: ", num)# Getting evenly spaced valuesres = tf.linspace(start, end, num)# Printing the resulting tensorprint("Result: ", res) |
Output:
start: tf.Tensor(1.0, shape=(), dtype=float64) end: tf.Tensor(5.0, shape=(), dtype=float64) num: 5 Result: tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Example 2: This example uses 2-D tensors and on providing different axis value different Tensors will be generated. This type of evenly-spaced value generation is currently allowed in nightly version.
python3
# importing the libraryimport tensorflow as tf# Initializing Inputstart = tf.constant((1, 15), dtype = tf.float64)end = tf.constant((10, 35), dtype = tf.float64)num = 5# Printing the Inputprint("start: ", start)print("end: ", end)print("num: ", num)# Getting evenly spaced valuesres = tf.linspace(start, end, num, axis = 0)# Printing the resulting tensorprint("Result 1: ", res)# Getting evenly spaced valuesres = tf.linspace(start, end, num, axis = 1)# Printing the resulting tensorprint("Result 2: ", res) |
Output:
start: tf.Tensor([ 1. 15.], shape=(2, ), dtype=float64) end: tf.Tensor([10. 35.], shape=(2, ), dtype=float64) num: 5 Result 1: tf.Tensor( [[ 1. 15. ] [ 3.25 20. ] [ 5.5 25. ] [ 7.75 30. ] [10. 35. ]], shape=(5, 2), dtype=float64) Result 2: tf.Tensor( [[ 1. 3.25 5.5 7.75 10. ] [15. 20. 25. 30. 35. ]], shape=(2, 5), dtype=float64)
