Create Constant Tensor using TensorFlow 2.0 Python Tutorial

In TensorFlow 2.0 Python Tutorial in Hindi, We will Learn about the TensorFlow Programming element to build Constant Tensor using tf.constant()

In this tutorial going to cover:

  1. What is constant in TensorFlow?
  2. What is TF constant?
  3. How do you print a constant in TensorFlow?
  4. Is TF constant trainable?

tf.constant(): Creates a constant tensor from a tensor-like object.

Syntax:
tf.constant(value, dtype=None, shape=None, name='Const')

Args:   
value: A constant value (or list) of output type `dtype`.   
dtype: The type of the elements of the resulting tensor.   
shape: Optional dimensions of resulting tensor.   
name: Optional name for the tensor. 

Returns:   A Constant Tensor.

Note:

  1. tf.Session() not in 2.x
  2. Most of TensorFlow syntax same like Numpy
  3. Use: While building neural network graph need constant varibale like input data,
    it never change while training

Create Constant Tensor in Different Way

# Impost TensorFlow
import tensorflow as tf


# TensorFlow Version
tf.__version__

# Check GPU availability
tf.test.is_gpu_available()

# Create Integer Constant

a = tf.constant(10)
a

# Create Float Constant
b = tf.constant(10.2)
b

# Create String Constant
c = tf.constant("Indian Ai Production")
c

# Creat Bool Constant
d = tf.constant(True)
d

# Creat Constant Numpy array / List / Tuple
import numpy as np
np_array = tf.constant(np.array([1,2,3,4]))
np_array

# Create 1D constant
t_1d = tf.constant([1,2,3,4])
t_1d

# Create 2D constant
t_2d = tf.constant([[1,2],[3,4]])
t_2d

t_2d_1 = tf.constant([1,2,3,4], shape=(2,2), dtype="float32")
t_2d_1

# Create N-D constant
t_3d_1 = tf.constant([[[1,2],[2,3],[4,5]]], dtype="float32")
t_3d_1

# Type of Constant
type(t_3d_1)

# Shape of Constant
t_3d_1.shape

t_2d.shape

# Access constant value
t_1d.numpy()

t_1d.numpy()[2]

# constant dtype
t_3d_1.dtype

# wrong synstax
tf.constant([1,23.4,"Indian"])

Reference: https://www.tensorflow.org/api_docs/python/tf/constant

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