** NumPy inner() Function:**

**Numpy inner: **The inner product of two arrays is returned by the inner() function of the NumPy module. It returns the ordinary inner product for 1-D arrays (without complex conjugation). A sum product over the last axes is returned for higher dimensions.

**Syntax:**

numpy.inner(a, b)

**Parameters**

**a:** This is required. It is the first array_like parameter given as input. If a and b are nonscalar, they must have the same last dimension.

**b:** This is required. It is the second array_like parameter given as input.

**Return Value: **

The inner product of a and b is returned.

**Note: **If the last dimension of a and b are different sizes, a ValueError exception is thrown.

## NumPy inner() Function in Python

**Example1**

**np.inner: **Here the two scalars passed as arguments for the inner() function.

**Approach:**

- Import numpy module using the import keyword.
- Pass two random numbers as the arguments to the inner () function of numpy module to calculate the inner product of the given two numbers.
- Store it in a variable.
- Print the inner product of the given two numbers.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Pass two random numbers as the arguments to the inner() function # of numpy module to calculate the inner product of given two numbers # Store it in a variable. rslt = np.inner(4, 6) # Print the inner product of the given two numbers print("The inner product of given two numbers = ", rslt)

**Output:**

The inner product of given two numbers = 24

**Example2**

**Approach:**

- Import numpy module using the import keyword.
- Give the first array as static input and store it in a variable.
- Give the second array as static input and store it in another variable.
- Pass the given two array’s as an argument to the inner() function of numpy module to get the inner product of the given two arrays.
- Store it in another variable.
- Print the inner product of the given two arrays.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Give the first array as static input and store it in a variable. fst_arry = [3, 9, 2] # Give the second array as static input and store it in another variable. scnd_arry = [4, 3, 5] # Pass the given two array's as an argument to the inner() function of numpy module # to get the inner product of the given two arrays. # Store it in another variable. rslt = np.inner(fst_arry, scnd_arry) # Print the inner product of the given two arrays. print("The inner product of the given two arrays = ", rslt)

**Output:**

The inner product of the given two arrays = 49

**Example3**

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Pass the random list of complex numbers as an argument to the array() function # to create an array. # Store it in a variable. fst_arry = np.array([1+4j, 1+3j]) # Pass the random list of complex numbers as an argument to the array() function # to create another array. # Store it in another variable. scnd_arry = np.array([2+1j, 3+2j]) # Pass the given two array's as the argument to the inner() function of numpy module # to get the inner product of the given two arrays of complex numbers. # Store it in another variable. rslt = np.inner(fst_arry, scnd_arry) # Print the inner product of the given two arrays of complex numbers. print("The inner product of the given two arrays of complex numbers = ") print(rslt)

**Output:**

The inner product of the given two arrays of complex numbers = (-5+20j)

**Example4**

The function does inner product on the matrix’s last axes when two matrices are used.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Pass the random list(2D) as an argument to the array() function # to create an array. # Store it in a variable. fst_arry = np.array([[5, 6], [1, 7]]) # Pass the random list(2D) as an argument to the array() function # to create another array. # Store it in another variable. scnd_arry = np.array([[2, 4], [8, 7]]) # Pass the given two array's as the argument to the inner() function of numpy module # to get the inner product of the given two 2D arrays # Here it does the inner product on last axes of the matrix. # Store it in another variable. rslt = np.inner(fst_arry, scnd_arry) # Print the inner product of given two arrays(matrices) print("The inner product of given two arrays(matrices) = ") print(rslt)

**Output:**

The inner product of given two arrays(matrices) = [[34 82] [30 57]]