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PyTorch Test
Test duration:
20
min
No. of questions:
10
Level of experience:
Entry/Mid/Senior

PyTorch Test

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PyTorch Skills Test

PyTorch is developed by Facebook's AI Research lab and is known as an open-source machine learning library based on the Torch library. It is mostly used for applications like computer vision and Natural Language Processing. PyTorch library can be used with both languages- Python and C++.

PyTorch uses core Python concepts such as classes, structures, and conditional loops that are familiar and more intuitive to understand. It mainly uses the primary and familiar programming paradigms rather than inventing its own.

PyTorch skills test helps tech recruiters and hiring managers assess candidates' PyTorch skills. The PyTorch online test is designed by experienced subject matter experts (SMEs) to evaluate and hire PyTorch experts as per industry standards.

PyTorch skills test helps to screen the candidates who possess traits as follows:

  • Good knowledge of various computations in the PyTorch library
  • Experience with PyTorch model methods and PyTorch tensor
  • Understanding of new network models, GPU devices, and optimizers
  • Familiarity with terms like functions, objects, and classes  

The PyTorch skills test is a secure and reliable way of candidate assessment. You can use our role-based access control feature to restrict system access based on the roles of individual users within the recruiting team. Features like window violation, image, audio, and video proctoring help detect cheating during the test.

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Test Summary

This test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, AI-LogicBox (AI-based Pseudo-Coding Platform), Coding Simulators, True or False Questions, etc.

Useful for hiring
  • Data Scientist
  • Deep Learning
  • Python Developer
  • Machine Learning Engineer
Test Duration
20
min
No. of Questions
10
Level of Expertise
Entry/Mid/Senior
Topics Covered
Shuffle

PyTorch Tensor

Modular Implementation

Shuffle

Computation in PyTorch

Shuffle

Network Models

Shuffle

Functions

Shuffle

Objects

Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.
Question type
Multiple Option
Topics covered
PyTorch
Difficulty
Easy

Question:

You are training a binarized neural network in PyTorch. Clamping of neuron outputs is an extremely important step in training such networks. Which of the following functions lets you clamp a given tensor in the range [-1, 1]?
A) torch.clamp(a, min=-1, max=1)
B) torch.limit(a, min=-1, max=1)


Options

  • A
  • B
  • Both A and B
  • None of the options
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