<commit_before>""" Restores a trained model and predicts handwritings. """
from __future__ import absolute_import, division, print_function

import sys
import argparse

import numpy as np
import tensorflow as tf

import utils.ui

FLAGS = None


def main(_):
    with tf.Session() as sess:
        new_saver = tf.train.import_meta_graph('checkpoint/model.ckpt.meta')
        new_saver.restore(sess, 'checkpoint/model.ckpt')
        x_ph = tf.get_collection('x_ph')[0]
        dropout_ph = tf.get_collection('dropout_ph')[0]

        model_y = tf.get_collection('model_y')[0]

        data_shape = x_ph.get_shape().as_list()[1:]

        while True:
            dialog = utils.ui.CanvasDialog("Read Handwriting...", data_shape[0], data_shape[1],
                                           scale=5, num_letters=FLAGS.num_letters)
            data = dialog.show()
            writing = np.asarray(data)
            writing = writing.reshape([-1] + data_shape)

            if writing.shape[0] == 0:
                break

            prediction = sess.run(model_y, feed_dict={x_ph: writing, dropout_ph: 1.0})
            for i in range(prediction.shape[0]):
                alpha_pos = np.argmax(prediction[i])
                print(chr(ord('A') + alpha_pos), end='')
            print()


if __name__ == "__main__":
    PARSER = argparse.ArgumentParser()
    PARSER.add_argument('--num_letters', type=int, default=6,<commit_msg>Predict chars for Handwritings, numbers for MNIST<commit_after>""" Restores a trained model and predicts handwritings. """
from __future__ import absolute_import, division, print_function

import sys
import argparse

import numpy as np
import tensorflow as tf

import utils.ui

FLAGS = None


def main(_):
    with tf.Session() as sess:
        new_saver = tf.train.import_meta_graph('checkpoint/model.ckpt.meta')
        new_saver.restore(sess, 'checkpoint/model.ckpt')
        x_ph = tf.get_collection('x_ph')[0]
        dropout_ph = tf.get_collection('dropout_ph')[0]

        model_y = tf.get_collection('model_y')[0]

        data_shape = x_ph.get_shape().as_list()[1:]

        while True:
            dialog = utils.ui.CanvasDialog("Read Handwriting...", data_shape[0], data_shape[1],
                                           scale=5, num_letters=FLAGS.num_letters)
            data = dialog.show()
            writing = np.asarray(data)
            writing = writing.reshape([-1] + data_shape)

            if writing.shape[0] == 0:
                break

            prediction = sess.run(model_y, feed_dict={x_ph: writing, dropout_ph: 1.0})
            for i in range(prediction.shape[0]):
                index_pos = np.argmax(prediction[i])
                if data_shape[0] == 28:  # MNIST
                    print(index_pos, end='')
                else:  # Handwriting
                    print(chr(ord('A') + index_pos), end='')
            print()


if __name__ == "__main__":
    PARSER = argparse.ArgumentParser()
    PARSER.add_argument('--num_letters', type=int, default=6,
{'fraction_non_alphanumeric': 0.12148295266468057, 'fraction_numerical': 0.010261502813637868, 'mean_word_length': 2.3577777777777778, 'pattern_counts': {'":': 2, '<': 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': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '7555606', 'n_tokens_mistral': 967, 'n_tokens_neox': 930, 'n_words': 197}