<commit_before># Attempting to get very high accuracy with MNIST convnet

import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data

# Get data
mnist = input_data.read_data_sets("/tmp/data")

h = 28
w = 28
channels = 1
n_inputs = h * w

# Architecture Conv 64, Max Pool, Conv 32, Average Pool, FC

conv1_filters = 64
conv1_k = 3
conv1_s = 1
conv1_pad = 'SAME'

pool1_filters = 64
pool1_k = 3
pool1_s = 1
pool1_pad = 'SAME'

conv2_filters = 32
conv2_k = 3
conv2_s = 2
conv2_pad = 'SAME'<commit_msg>Add seed for random number generation<commit_after># Attempting to get very high accuracy with MNIST convnet

import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data

# Set random seed

np.random.seed(123456)
tf.set_random_seed(123456)

# Get data
mnist = input_data.read_data_sets("/tmp/data")

h = 28
w = 28
channels = 1
n_inputs = h * w

# Architecture Conv 64, Max Pool, Conv 32, Average Pool, FC

conv1_filters = 64
conv1_k = 3
conv1_s = 1
conv1_pad = 'SAME'

pool1_filters = 64
pool1_k = 3
pool1_s = 1
pool1_pad = 'SAME'

conv2_filters = 32
conv2_k = 3
conv2_s = 2
conv2_pad = 'SAME'
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{'dir': 'git-commits-cleaned', 'id': '2980574', 'n_tokens_mistral': 513, 'n_tokens_neox': 448, 'n_words': 147}