Distance Calculation Create a tensor among the following types float 3 2 , float 6 4 , complex 6 4 , complex 1 2 8 Mentioned link details the meaning of each variable create two tensors of shape 2 x 3 tensor a tf constant ( 1 , 2 , 3 , 4 , 5 , 6 , dtype tf float 3 2 , name 'template' ) tensor b tf constant ( 1 , 1 , 1 , 1 , 1 , 1 , dtype tf float 3 2 , name 'template' ) 1 Calculating euclidean distance or the l 2 norm eucledian distance tf norm ( tensor a tensor b , ord 'euclidean', axis None, keepdims None ) tf print ( Euclidean distance , eucledian distance ) 2 Calculating the Manhattan distance manhattan distance tf norm ( tensor a tensor b , ord 1 , axis None, keepdims None ) tf print ( Manhattan distance , manhattan distance ) 1 Calculating Euclidean Distance def euclidean distance ( tensor 1 , tensor 2 ) implement your code below ( 1 line ) euc distance your code ends here return euc distance 2 Calculating Manhattan distance def manhattan distance ( tensor 1 , tensor 2 ) implement your code below ( 1 line ) manh distance your code ends here return manh distance tf print ( Euclidean distance , euclidean distance ( tensor a , tensor b ) ) tf print ( Manhattan distance , manhattan distance ( tensor a , tensor b ) )

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Question: # Distance Calculation # # Create a tensor among the following types : float 3 2 , float 6 4 , complex 6 4 ,

# Distance Calculation

# Create a tensor among the following types : float

32,

float

64,

complex

64,

complex

128

# Mentioned link details the meaning of each variable :

# create two tensors of shape

2

3 .

tensor

_

=

.

constant

([[1, 2, 3], [4, 5, 6]],

dtype

=

.

float

32,

name

=

'template'

)

tensor

_

=

.

constant

([[1, 1, 1], [1, 1, 1]],

dtype

=

.

float

32,

name

=

'template'

)

1 .

Calculating euclidean distance or the l

2

norm.

eucledian

_

distance

=

.

norm

(

tensor

_

-

tensor

_

,

ord

=

'euclidean', axis

=

None, keepdims

=

None

)

.

("

Euclidean distance:", eucledian

_

distance

)

2 .

Calculating the Manhattan distance

manhattan

_

distance

=

.

norm

(

tensor

_

-

tensor

_

,

ord

= 1,

axis

=

None, keepdims

=

None

)

.

("

Manhattan distance:", manhattan

_

distance

)

1 .

Calculating Euclidean Distance

def euclidean

_

distance

(

tensor

_1,

tensor

_2)

% % % % % % % % % % % % % %

implement your code below

(1

line

) % % % % % % % % % % % % % %

euc

_

distance

=

% % % % % % % % % % % % % %

your code ends here

% % % % % % % % % % % % % %

return euc

_

distance

2 .

Calculating Manhattan distance

def manhattan

_

distance

(

tensor

_1,

tensor

_2)

% % % % % % % % % % % % % %

implement your code below

(1

line

) % % % % % % % % % % % % % %

manh

_

distance

=

% % % % % % % % % % % % % %

your code ends here

% % % % % % % % % % % % % %

return manh

_

distance

.

("

Euclidean distance:", euclidean

_

distance

(

tensor

_

,

tensor

_

))

.

("

Manhattan distance:", manhattan

_

distance

(

tensor

_

,

tensor

_

))

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