<jupyter_start><jupyter_text>5.5<jupyter_code># mask
x = np.array([[1.0,-0.5],[-2.0,3.0]])
print(x)
mask = (x<=0)
print(mask)<jupyter_output>[[False  True]
 [ True False]]<jupyter_text>5.7<jupyter_code>import sys, os
sys.path.append(os.pardir)
import numpy as np
from common.layers import *
from common.gradient import numerical_gradient
from collections import OrderedDict
class TwoLayerNet:<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14928909952606634, 'fraction_numerical': 0.030805687203791468, 'mean_word_length': 7.294117647058823, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 8, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '562366', 'license': 'MIT', 'n_tokens_mistral': 174, 'n_tokens_neox': 170, 'n_words': 31, 'path': 'ch05/ch05.ipynb', 'repo_name': 'satoshi3104satoshi/deep-learning-from-scratch', 'size': '422'}