CUDA availability check in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to check if CUDA is available in PyTorch.

PyTorch

import torch

cuda_available = torch.cuda.[1]()
print(f"CUDA available: {cuda_available}")

Drag options to blanks, or click blank then click option'

Acuda_available

Bavailable

Cis_available

Dcheck

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.cuda.available() which does not exist.

Trying to access a property instead of calling a function.

The correct PyTorch function to check CUDA availability is torch.cuda.is_available().

2fill in blank

medium

Complete the code to get the name of the current CUDA device.

PyTorch

import torch

if torch.cuda.is_available():
    device_name = torch.cuda.get_device_[1](torch.cuda.current_device())
    print(f"Current CUDA device: {device_name}")

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Adevice

Binfo

Cid

Dname

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.cuda.get_device_id() which does not exist.

Using torch.cuda.get_device_info() which is incorrect.

The function torch.cuda.get_device_name(device_id) returns the name of the CUDA device.

3fill in blank

hard

Fix the error in the code to correctly check CUDA availability and print a message.

PyTorch

import torch

if torch.cuda.[1]:
    print("CUDA is available")
else:
    print("CUDA is not available")

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Ais_available

Bis_available()

Cavailable()

Davailable

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting parentheses after is_available.

Using a non-existent attribute like available.

torch.cuda.is_available() is a function and must be called with parentheses to get a boolean result.

4fill in blank

hard

Fill both blanks to create a tensor on the CUDA device if available, otherwise on CPU.

PyTorch

import torch

device = torch.device("cuda" if torch.cuda.[1]() else "[2]")
tensor = torch.tensor([1, 2, 3], device=device)
print(tensor.device)

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Ais_available

Bcpu

Ccuda

Dis_ready

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'cuda' instead of 'cpu' as fallback device.

Using a non-existent function like is_ready.

Use torch.cuda.is_available() to check CUDA, and 'cpu' as fallback device string.

5fill in blank

hard

Fill all three blanks to print the number of CUDA devices and the name of the first device if available.

PyTorch

import torch

if torch.cuda.[1]():
    count = torch.cuda.[2]()
    name = torch.cuda.get_device_[3](0)
    print(f"CUDA devices: {count}, First device: {name}")
else:
    print("No CUDA devices found.")

Drag options to blanks, or click blank then click option'

Ais_available

Bdevice_count

Cname

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.cuda.count() which does not exist.

Using torch.cuda.get_device_id() instead of get_device_name().

Use torch.cuda.is_available() to check availability, torch.cuda.device_count() to get number of devices, and torch.cuda.get_device_name() to get device name.