<jupyter_start><jupyter_text><jupyter_code>import torch
w = torch.tensor(3.0, requires_grad=True)
b = torch.tensor(1.0, requires_grad=True)
def forward(x):
  y = w*x + b
  return y
x = torch.tensor([[4],[7]])
forward(x)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.17269076305220885, 'fraction_numerical': 0.024096385542168676, 'mean_word_length': 6.8125, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '61317', 'license': 'MIT', 'n_tokens_mistral': 108, 'n_tokens_neox': 106, 'n_words': 18, 'path': 'Chapter4_Making_Predictions.ipynb', 'repo_name': 'SokichiFujita/PyTorch-for-Deep-Learning-and-Computer-Vision', 'size': '249'}