<jupyter_start><jupyter_text>Load network<jupyter_code>net = caffe.Net(path_test_prototxt, caffe.TEST)<jupyter_output><empty_output><jupyter_text>blobs<jupyter_code>a = [(k, v.data.shape) for k, v in net.blobs.items()]<jupyter_output><empty_output><jupyter_text>layers<jupyter_code>[(k, v[0].data.shape, v[1].data.shape) for k, v in net.params.items()]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.16753926701570682, 'fraction_numerical': 0.005235602094240838, 'mean_word_length': 10.96875, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '472125', 'license': 'BSD-2-Clause', 'n_tokens_mistral': 169, 'n_tokens_neox': 164, 'n_words': 18, 'path': 'tools/analyse network.ipynb', 'repo_name': 'jorisgu/jg_pfr', 'size': '382'}