#0153

Batch Dot Products

MediumNumPy25 min20 XP

Problem

Given a 2D matrix X and vector w, return the dot product of each row of X with w.

Why This Matters

Batch dot products appear in similarity search, linear models, attention scores, and embedding comparisons.

Function Signature

def batch_dot(X, w):

Examples

Example 1

InputX = np.array([[1,2],[3,4]]), w = np.array([10,1])

Outputnp.array([12, 34])

Rows produce 1*10+2*1=12 and 3*10+4*1=34.

Constraints

Return the exact requested value.
Handle empty or small inputs when the prompt allows them.
Keep the code readable and deterministic.

CodePython

import numpy as np

def batch_dot(X, w):
    """
    Input example: X = np.array([[1,2],[3,4]]), w = np.array([10,1])
    Return: np.array([12, 34])
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return np.array([])

import numpy as np

def batch_dot(X, w):
    """
    Input example: X = np.array([[1,2],[3,4]]), w = np.array([10,1])
    Return: np.array([12, 34])
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return np.array([])

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

InputX = np.array([[1,2],[3,4]]), w = np.array([10,1])

Expectednp.array([12, 34])

Rows produce 1*10+2*1=12 and 3*10+4*1=34.

Hidden Test Categories

empty or smallest inputduplicates or repeated valueslarger realistic input