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:
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.
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.
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)