<jupyter_start><jupyter_text>tensorboard \    --logdir ~/Dropbox/Cours/tensorbayes \    --port 6006 \    --debugger_port 6064<jupyter_code>sess.run(tf.global_variables_initializer())
sess.run(ta_beta.eval(session=sess), feed_dict={ind: 0, Xj: x[:,0].reshape(N,1)})
x
# Number of Gibbs sampling iterations
num_iter = 5000

with tf.Session() as sess:

    # Initialize variable
    sess.run(tf.global_variables_initializer())

    # Gibbs sampler iterations
    for i in range(num_iter):
        print("Gibbs sampling iteration: ", i)
        sess.run(emu_up)
        #sess.run(ny_reset)
        index = np.random.permutation(M)

        for marker in index:
            current_col = x[:,[marker]]
            feed = {ind: marker, Xj: current_col}
            sess.run(up_grp, feed_dict=feed)
        sess.run(nz_up)
        sess.run(emu_up)
        sess.run(eps_up)
        sess.run(s2b_up)
        sess.run(s2e_up)

        # Print operations 
        print(sess.run(print_dict))
    
    # End of Gibbs sampling
    print(sess.run(Ebeta), beta_true)


total_time =   time.clock()-start_time
print("Total time: " + str(total_time) + "s")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12756849315068494, 'fraction_numerical': 0.014554794520547944, 'mean_word_length': 2.820261437908497, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '173622', 'license': 'MIT', 'n_tokens_mistral': 448, 'n_tokens_neox': 422, 'n_words': 75, 'path': 'notebooks/TensorBayes_v3.2.ipynb', 'repo_name': 'jklopf/tensorbayes', 'size': '1168'}