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Matrix Operation.ipynb

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Matrix Operations using Tensors

In [2]:
import tensorflow as tf

A = tf.constant([[1, 2, 3, 4]])
B = tf.constant([[3],
                  [4],
                  [5],
                  [5]])
C = tf.multiply(A, B)  # Equivalent to A*B, element wise product
tf.print(C)
[[3 6 9 12]
 [4 8 12 16]
 [5 10 15 20]
 [5 10 15 20]]
In [3]:
import tensorflow as tf

A = tf.constant([[1, 2, 3, 4]])
B = tf.constant([[3], [4], [5], [5]])
C = tf.matmul(A, B)
tf.print(C)
[[46]]
In [4]:
A = tf.constant([[2, 24], 
                 [2, 26], 
                 [2, 57]])
B = tf.constant([[1000], 
                 [150]])
C = tf.matmul(A, B)
tf.print(C)
[[5600]
 [5900]
 [10550]]
In [9]:
A = tf.constant([1,2,3])
B = tf.constant([1,2,3])
C = tf.add(A, B)  # Element wise addition.
tf.print(C)
[2 4 6]
In [10]:
x = tf.constant([[1, 2, 3], [4, 5, 6]])
tf.transpose(x)
<tf.Tensor: shape=(3, 2), dtype=int32, numpy=
array([[1, 4],
       [2, 5],
       [3, 6]])>
In [ ]: