<commit_before>import tensorflow as tf
import numpy as np


# Load in mnist dataset using one_hot
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets("data/MNIST/", one_hot=True)

# Get basic information about dataset
print("Training Size:\t\t{}".format(len(data.train.labels)))
print("Test Size:\t\t{}".format(len(data.test.labels)))


# Each image size is 28px by 28px
img_size = 28
img_size_flat = img_size * img_size
img_shape = (img_size, img_size)
num_classes = 10

data.test.classes = np.array([label.argmax() for label in data.test.labels])<commit_msg>added placeholders for X and y<commit_after>import tensorflow as tf
import numpy as np


# Load in mnist dataset using one_hot
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets("data/MNIST/", one_hot=True)

# Get basic information about dataset
print("Training Size:\t\t{}".format(len(data.train.labels)))
print("Test Size:\t\t{}".format(len(data.test.labels)))


# Each image size is 28px by 28px
img_size = 28
img_size_flat = img_size * img_size
img_shape = (img_size, img_size)
num_classes = 10

data.test.cls = np.array([label.argmax() for label in data.test.labels])

X = tf.placeholder(tf.float32, [None, img_size_flat])
y_one_hot = tf.placeholder(tf.float32, [None, num_classes])
y_true = tf.placeholder(tf.int64, [None])
{'fraction_non_alphanumeric': 0.12408759124087591, 'fraction_numerical': 0.016058394160583942, 'mean_word_length': 5.6231884057971016, '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': '3342646', 'n_tokens_mistral': 502, 'n_tokens_neox': 470, 'n_words': 121}