<jupyter_start><jupyter_text>GPU Environment This tutorial is available as an IPython notebook at [malaya-speech/example/gpu-environment](https://github.com/huseinzol05/malaya-speech/tree/master/example/gpu-environment).<jupyter_code>%%time

import malaya_speech
import logging
logging.basicConfig(level = logging.INFO)<jupyter_output>CPU times: user 4.7 s, sys: 1.5 s, total: 6.19 s
Wall time: 14.1 s<jupyter_text>List available GPU<jupyter_code>malaya_speech.utils.available_gpu()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11328125, 'fraction_numerical': 0.0234375, 'mean_word_length': 7.55, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '358200', 'license': 'MIT', 'n_tokens_mistral': 191, 'n_tokens_neox': 178, 'n_words': 34, 'path': 'example/gpu-environment/gpu-environment.ipynb', 'repo_name': 'ishine/malaya-speech', 'size': '512'}