<jupyter_start><jupyter_text><jupyter_code>import tensorflow as tf
a = tf.add(3, 5)
sess = tf.Session()
print(sess.run(a))
sess.close()
with tf.Session() as sess:
  print(sess.run(a))
x = 2
y = 3
op1 = tf.add(x, y)
op2 = tf.multiply(x, y)
op3 = pow(op1, op2)
useless = multiply (x , op1)

with tf.Session()as sess:
  print(sess.run(op3))
print(tf.test.is_gpu_available())
print(tf.test.gpu_device_name())
with tf.device('/gpu:0'):
  a = tf.constant([1.0, 2.0, 3.0], name = 'a')
  b = tf.constant([1.0, 2.0, 3.0], name = 'b')
  c = tf.multiply(a, b)
  sess = tf.Session(config = tf.ConfigProto(log_device_placement = 1))
  print(sess.run(c))
import calendar
c = calendar.TextCalendar(calendar.MONDAY)
#c = calendar.HTMLCalendar(calendar.MONDAY)
str = c.formatmonth(2019, 3)
print(str)
for name in calendar.month_name:
  print(name)<jupyter_output>January
February
March
April
May
June
July
August
September
October
November
December
{'fraction_non_alphanumeric': 0.16541353383458646, 'fraction_numerical': 0.0322234156820623, 'mean_word_length': 4.89873417721519, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, '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': '33030', 'license': 'Apache-2.0', 'n_tokens_mistral': 416, 'n_tokens_neox': 387, 'n_words': 87, 'path': 'diegogarcia.ipynb', 'repo_name': 'diegogarce/TensorFlow', 'size': '931'}