joeyism

import tensorflow as tf

image_size = 32
input_images = tf.placeholder(tf.float32,
                              shape=[None, image_size, image_size, 3], 
                              name="input_images")

# First CONV layer
kernel = tf.Variable(tf.truncated_normal([11, 11, 3, 96],
                                         dtype=tf.float32,

joeyism

import tensorflow as tf

image_size = 32
input_images = tf.placeholder(tf.float32,
                              shape=[None, image_size, image_size, 3], 
                              name="input_images")

# First CONV layer
kernel = tf.Variable(tf.truncated_normal([11, 11, 3, 96],
                                         dtype=tf.float32,

joeyism

import tensorflow as tf

image_size = 32
input_images = tf.placeholder(tf.float32,
                              shape=[None, image_size, image_size, 3], 
                              name="input_images")

# First CONV layer
kernel = tf.Variable(tf.truncated_normal([11, 11, 3, 96],
                                         dtype=tf.float32,

joeyism

import tensorflow as tf

n_classes = 10 # <-- newly added constant 

image_size = 32
input_images = tf.placeholder(tf.float32,
                              shape=[None, image_size, image_size, 3], 
                              name="input_images")

# First CONV layer

joeyism

from cifar import Cifar
import tensorflow as tf
import model

learning_rate = 0.001

y = tf.placeholder(tf.float32, [None, model.n_classes])
cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
    logits=model.out,
    labels=y))

joeyism

from cifar import Cifar
from tqdm import tqdm
import tensorflow as tf
import model
import helper

learning_rate = 0.001
batch_size = 16
no_of_epochs = 10

joeyism

import numpy as np


def __one_hot__(num, dim=1000):
    vec = np.zeros(dim)
    vec[num] = 1
    return vec


def transform_to_input_output(input_output, dim=1000):

joeyism

from cifar import Cifar
from tqdm import tqdm
import tensorflow as tf
import model
import helper

learning_rate = 0.001
batch_size = 16
no_of_epochs = 10

joeyism

from cifar import Cifar
from tqdm import tqdm
import tensorflow as tf
import model
import helper

learning_rate = 0.001
batch_size = 16
no_of_epochs = 10

joeyism

from cifar import Cifar
from tqdm import tqdm
import tensorflow as tf
import model
import helper

learning_rate = 0.001
batch_size = 16
no_of_epochs = 10