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BigCodeBench / BigCodeBench v0.1.0_hf 00ccb5af-df61-5472-9a82-38b688e94bdc

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import numpy as np
import seaborn as sns


def task_func(P, T):
    """
    Calculate the product of a matrix 'P' and a 3D tensor 'T' using numpy and visualize the results as a heatmap.
    Note: This function only accepts numpy matrices/arrays.

    Parameters:
    - P (numpy.ndarray): Input matrix of shape (M, 3), where M can be any positive integer.
    - T (numpy.ndarray): Input tensor of shape (3, 3, 3).

    Returns:
    - numpy.ndarray: Resultant product after matrix-tensor multiplication.
    - matplotlib.axes.Axes: Axes object displaying the heatmap of the 2D result.

    Requirements:
    - numpy
    - seaborn

    Example:
    >>> np.random.seed(0)
    >>> P = np.array([[6, 2, 7], [1, 1, 8]])
    >>> T = np.random.rand(3, 3, 3)
    >>> product, heatmap = task_func(P, T)
    >>> product
    array([[[ 9.50686132, 11.96467131, 11.52469849],
            [ 9.99949817,  7.62347761,  9.48114103],
            [ 3.62770285,  9.87052195,  8.45068927]],
    <BLANKLINE>
           [[ 7.15750903,  8.46701159,  8.96060503],
            [ 7.50619626,  5.04108634,  6.96116358],
            [ 1.47091192,  6.03135957,  2.94310891]]])
    >>> type(heatmap)
    <class 'matplotlib.axes._axes.Axes'>
    """

instruct prompt

Calculate the product of a matrix 'P' and a 3D tensor 'T' using numpy and visualize the results as a heatmap.
Note that: This function only accepts numpy matrices/arrays.
The function should output with:
    numpy.ndarray: Resultant product after matrix-tensor multiplication.
    matplotlib.axes.Axes: Axes object displaying the heatmap of the 2D result.
You should write self-contained code starting with:

Code

import numpy as np
import seaborn as sns
def task_func(P, T):

code prompt

Code

import numpy as np
import seaborn as sns
def task_func(P, T):

entry point

task_func

libs

  • numpy
  • seaborn

Discussion

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Source and history

task_id
00ccb5af-df61-5472-9a82-38b688e94bdc
task_key
default--v0~2e1~2e0~5fhf--00ccb5af-df61-5472-9a82-38b688e94bdc
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import