<commit_before>import tensorflow as tf
import construct_graph
from dataloader import DataLoader
from distribution_to_image import get_colorized_image

def run_training(BATCH_SIZE = 1, ITERATIONS = 3000):
  saver = tf.train.Saver()
  dataset = DataLoader()
  f = open('log.txt', 'w')

  with tf.Session() as sess:
    x, y_, y_output = construct_graph.setup_tensorflow_graph(BATCH_SIZE)

    loss = construct_graph.loss_function()
    prediction = construct_graph.get_prediction(output)<commit_msg>Move saver down<commit_after>import tensorflow as tf
import construct_graph
from dataloader import DataLoader
from distribution_to_image import get_colorized_image

def run_training(BATCH_SIZE = 1, ITERATIONS = 3000):
  f = open('log.txt', 'w')

  with tf.Session() as sess:
    x, y_, y_output = construct_graph.setup_tensorflow_graph(BATCH_SIZE)

    saver = tf.train.Saver()
    dataset = DataLoader()

    loss = construct_graph.loss_function()
    prediction = construct_graph.get_prediction(output)
{'fraction_non_alphanumeric': 0.08791208791208792, 'fraction_numerical': 0.00999000999000999, 'mean_word_length': 5.341772151898734, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, '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}}
{'dir': 'git-commits-cleaned', 'id': '320552', 'n_tokens_mistral': 335, 'n_tokens_neox': 316, 'n_words': 77}