diff --git a/mnist/mnist_slim.ipynb b/mnist/mnist_slim.ipynb index dc7ae89..20a16de 100644 --- a/mnist/mnist_slim.ipynb +++ b/mnist/mnist_slim.ipynb @@ -49,9 +49,9 @@ }, "outputs": [], "source": [ - "def CNN(inputs, is_training=True):\n", + "def CNN(inputs, _is_training=True):\n", " x = tf.reshape(inputs, [-1, 28, 28, 1])\n", - " batch_norm_params = {'is_training': is_training, 'decay': 0.9, 'updates_collections': None}\n", + " batch_norm_params = {'is_training': _is_training, 'decay': 0.9, 'updates_collections': None}\n", " net = slim.conv2d(x, 32, [5, 5], padding='SAME'\n", " , activation_fn = tf.nn.relu\n", " , weights_initializer = tf.truncated_normal_initializer(stddev=0.01)\n", @@ -68,7 +68,7 @@ " , normalizer_fn = slim.batch_norm\n", " , normalizer_params = batch_norm_params\n", " , scope='fc4')\n", - " net = slim.dropout(net, keep_prob=0.7, is_training=is_training, scope='dropout4') \n", + " net = slim.dropout(net, keep_prob=0.7, is_training=_is_training, scope='dropout4') \n", " out = slim.fully_connected(net, 10, activation_fn=None, normalizer_fn=None, scope='fco')\n", " return out" ] @@ -272,6 +272,15 @@ "name": "stdout", "output_type": "stream", "text": [ + "WARNING:tensorflow:From :9: softmax_cross_entropy (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n", + "Instructions for updating:\n", + "Use tf.losses.softmax_cross_entropy instead.\n", + "WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:394: compute_weighted_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n", + "Instructions for updating:\n", + "Use tf.losses.compute_weighted_loss instead.\n", + "WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/losses/python/losses/loss_ops.py:151: add_loss (from tensorflow.contrib.losses.python.losses.loss_ops) is deprecated and will be removed after 2016-12-30.\n", + "Instructions for updating:\n", + "Use tf.losses.add_loss instead.\n", "MODEL DEFINED.\n" ] } @@ -282,7 +291,7 @@ "y_ = tf.placeholder(tf.float32, [None, 10]) #answer\n", "is_training = tf.placeholder(tf.bool, name='MODE')\n", "# CONVOLUTIONAL NEURAL NETWORK MODEL \n", - "y = CNN(x)\n", + "y = CNN(x, is_training)\n", "# DEFINE LOSS\n", "with tf.name_scope(\"LOSS\"):\n", " loss = slim.losses.softmax_cross_entropy(y, y_)\n", @@ -341,11 +350,257 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { - "collapsed": false + "collapsed": false, + "scrolled": true }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: [ 1/ 10] Batch: [0000/5500] Training Acc: 0.12000\n", + "Epoch: [ 1/ 10] Batch: [0000/5500] Validation Acc: 0.16060\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.16060\n", + "Epoch: [ 1/ 10] Batch: [0500/5500] Training Acc: 0.94000\n", + "Epoch: [ 1/ 10] Batch: [0500/5500] Validation Acc: 0.98500\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.98500\n", + "Epoch: [ 1/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [1000/5500] Validation Acc: 0.98640\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.98640\n", + "Epoch: [ 1/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [1500/5500] Validation Acc: 0.98840\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.98840\n", + "Epoch: [ 1/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [2000/5500] Validation Acc: 0.99080\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99080\n", + "Epoch: [ 1/ 10] Batch: [2500/5500] Training Acc: 0.98000\n", + "Epoch: [ 1/ 10] Batch: [2500/5500] Validation Acc: 0.99240\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99240\n", + "Epoch: [ 1/ 10] Batch: [3000/5500] Training Acc: 0.96000\n", + "Epoch: [ 1/ 10] Batch: [3000/5500] Validation Acc: 0.99160\n", + "Epoch: [ 1/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [3500/5500] Validation Acc: 0.99200\n", + "Epoch: [ 1/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [4000/5500] Validation Acc: 0.99360\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99360\n", + "Epoch: [ 1/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [4500/5500] Validation Acc: 0.99180\n", + "Epoch: [ 1/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 1/ 10] Batch: [5000/5500] Validation Acc: 0.99240\n", + "Epoch: [ 2/ 10] Batch: [0000/5500] Training Acc: 0.98000\n", + "Epoch: [ 2/ 10] Batch: [0000/5500] Validation Acc: 0.99300\n", + "Epoch: [ 2/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [0500/5500] Validation Acc: 0.99240\n", + "Epoch: [ 2/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [1000/5500] Validation Acc: 0.99400\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99400\n", + "Epoch: [ 2/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [1500/5500] Validation Acc: 0.99380\n", + "Epoch: [ 2/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [2000/5500] Validation Acc: 0.99400\n", + "Epoch: [ 2/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [2500/5500] Validation Acc: 0.99460\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99460\n", + "Epoch: [ 2/ 10] Batch: [3000/5500] Training Acc: 0.98000\n", + "Epoch: [ 2/ 10] Batch: [3000/5500] Validation Acc: 0.99360\n", + "Epoch: [ 2/ 10] Batch: [3500/5500] Training Acc: 0.98000\n", + "Epoch: [ 2/ 10] Batch: [3500/5500] Validation Acc: 0.99460\n", + "Epoch: [ 2/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [4000/5500] Validation Acc: 0.99380\n", + "Epoch: [ 2/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 2/ 10] Batch: [4500/5500] Validation Acc: 0.99380\n", + "Epoch: [ 2/ 10] Batch: [5000/5500] Training Acc: 0.98000\n", + "Epoch: [ 2/ 10] Batch: [5000/5500] Validation Acc: 0.99320\n", + "Epoch: [ 3/ 10] Batch: [0000/5500] Training Acc: 0.98000\n", + "Epoch: [ 3/ 10] Batch: [0000/5500] Validation Acc: 0.99420\n", + "Epoch: [ 3/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [0500/5500] Validation Acc: 0.99280\n", + "Epoch: [ 3/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [1000/5500] Validation Acc: 0.99440\n", + "Epoch: [ 3/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [1500/5500] Validation Acc: 0.99520\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99520\n", + "Epoch: [ 3/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [2000/5500] Validation Acc: 0.99400\n", + "Epoch: [ 3/ 10] Batch: [2500/5500] Training Acc: 0.98000\n", + "Epoch: [ 3/ 10] Batch: [2500/5500] Validation Acc: 0.99560\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99560\n", + "Epoch: [ 3/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [3000/5500] Validation Acc: 0.99520\n", + "Epoch: [ 3/ 10] Batch: [3500/5500] Training Acc: 0.98000\n", + "Epoch: [ 3/ 10] Batch: [3500/5500] Validation Acc: 0.99380\n", + "Epoch: [ 3/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [4000/5500] Validation Acc: 0.99540\n", + "Epoch: [ 3/ 10] Batch: [4500/5500] Training Acc: 0.96000\n", + "Epoch: [ 3/ 10] Batch: [4500/5500] Validation Acc: 0.99480\n", + "Epoch: [ 3/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 3/ 10] Batch: [5000/5500] Validation Acc: 0.99460\n", + "Epoch: [ 4/ 10] Batch: [0000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [0000/5500] Validation Acc: 0.99540\n", + "Epoch: [ 4/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [0500/5500] Validation Acc: 0.99520\n", + "Epoch: [ 4/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [1000/5500] Validation Acc: 0.99560\n", + "Epoch: [ 4/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [1500/5500] Validation Acc: 0.99580\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99580\n", + "Epoch: [ 4/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [2000/5500] Validation Acc: 0.99520\n", + "Epoch: [ 4/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [2500/5500] Validation Acc: 0.99440\n", + "Epoch: [ 4/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [3000/5500] Validation Acc: 0.99620\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99620\n", + "Epoch: [ 4/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [3500/5500] Validation Acc: 0.99500\n", + "Epoch: [ 4/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [4000/5500] Validation Acc: 0.99360\n", + "Epoch: [ 4/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [4500/5500] Validation Acc: 0.99400\n", + "Epoch: [ 4/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 4/ 10] Batch: [5000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 5/ 10] Batch: [0000/5500] Training Acc: 0.98000\n", + "Epoch: [ 5/ 10] Batch: [0000/5500] Validation Acc: 0.99500\n", + "Epoch: [ 5/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [0500/5500] Validation Acc: 0.99640\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99640\n", + "Epoch: [ 5/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [1000/5500] Validation Acc: 0.99640\n", + "Epoch: [ 5/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [1500/5500] Validation Acc: 0.99480\n", + "Epoch: [ 5/ 10] Batch: [2000/5500] Training Acc: 0.98000\n", + "Epoch: [ 5/ 10] Batch: [2000/5500] Validation Acc: 0.99580\n", + "Epoch: [ 5/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [2500/5500] Validation Acc: 0.99580\n", + "Epoch: [ 5/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [3000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 5/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [3500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 5/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [4000/5500] Validation Acc: 0.99520\n", + "Epoch: [ 5/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [4500/5500] Validation Acc: 0.99460\n", + "Epoch: [ 5/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 5/ 10] Batch: [5000/5500] Validation Acc: 0.99640\n", + "Epoch: [ 6/ 10] Batch: [0000/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [0000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 6/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [0500/5500] Validation Acc: 0.99580\n", + "Epoch: [ 6/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [1000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 6/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [1500/5500] Validation Acc: 0.99640\n", + "Epoch: [ 6/ 10] Batch: [2000/5500] Training Acc: 0.98000\n", + "Epoch: [ 6/ 10] Batch: [2000/5500] Validation Acc: 0.99520\n", + "Epoch: [ 6/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [2500/5500] Validation Acc: 0.99560\n", + "Epoch: [ 6/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [3000/5500] Validation Acc: 0.99660\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99660\n", + "Epoch: [ 6/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [3500/5500] Validation Acc: 0.99460\n", + "Epoch: [ 6/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [4000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 6/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [4500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 6/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 6/ 10] Batch: [5000/5500] Validation Acc: 0.99540\n", + "Epoch: [ 7/ 10] Batch: [0000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [0000/5500] Validation Acc: 0.99420\n", + "Epoch: [ 7/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [0500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 7/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [1000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 7/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [1500/5500] Validation Acc: 0.99580\n", + "Epoch: [ 7/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [2000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 7/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [2500/5500] Validation Acc: 0.99560\n", + "Epoch: [ 7/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [3000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 7/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [3500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 7/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [4000/5500] Validation Acc: 0.99500\n", + "Epoch: [ 7/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [4500/5500] Validation Acc: 0.99660\n", + "Epoch: [ 7/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 7/ 10] Batch: [5000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 8/ 10] Batch: [0000/5500] Training Acc: 0.98000\n", + "Epoch: [ 8/ 10] Batch: [0000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 8/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [0500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 8/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [1000/5500] Validation Acc: 0.99640\n", + "Epoch: [ 8/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [1500/5500] Validation Acc: 0.99520\n", + "Epoch: [ 8/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [2000/5500] Validation Acc: 0.99560\n", + "Epoch: [ 8/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [2500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 8/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [3000/5500] Validation Acc: 0.99620\n", + "Epoch: [ 8/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [3500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 8/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [4000/5500] Validation Acc: 0.99680\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99680\n", + "Epoch: [ 8/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [4500/5500] Validation Acc: 0.99540\n", + "Epoch: [ 8/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 8/ 10] Batch: [5000/5500] Validation Acc: 0.99660\n", + "Epoch: [ 9/ 10] Batch: [0000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [0000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 9/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [0500/5500] Validation Acc: 0.99660\n", + "Epoch: [ 9/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [1000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 9/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [1500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 9/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [2000/5500] Validation Acc: 0.99660\n", + "Epoch: [ 9/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [2500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 9/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [3000/5500] Validation Acc: 0.99660\n", + "Epoch: [ 9/ 10] Batch: [3500/5500] Training Acc: 0.98000\n", + "Epoch: [ 9/ 10] Batch: [3500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 9/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [4000/5500] Validation Acc: 0.99680\n", + " MODEL UPDATED TO [model/model.ckpt] VALIDATION ACC IS 0.99680\n", + "Epoch: [ 9/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [4500/5500] Validation Acc: 0.99620\n", + "Epoch: [ 9/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 9/ 10] Batch: [5000/5500] Validation Acc: 0.99600\n", + "Epoch: [ 10/ 10] Batch: [0000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [0000/5500] Validation Acc: 0.99580\n", + "Epoch: [ 10/ 10] Batch: [0500/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [0500/5500] Validation Acc: 0.99580\n", + "Epoch: [ 10/ 10] Batch: [1000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [1000/5500] Validation Acc: 0.99540\n", + "Epoch: [ 10/ 10] Batch: [1500/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [1500/5500] Validation Acc: 0.99500\n", + "Epoch: [ 10/ 10] Batch: [2000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [2000/5500] Validation Acc: 0.99640\n", + "Epoch: [ 10/ 10] Batch: [2500/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [2500/5500] Validation Acc: 0.99640\n", + "Epoch: [ 10/ 10] Batch: [3000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [3000/5500] Validation Acc: 0.99680\n", + "Epoch: [ 10/ 10] Batch: [3500/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [3500/5500] Validation Acc: 0.99600\n", + "Epoch: [ 10/ 10] Batch: [4000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [4000/5500] Validation Acc: 0.99660\n", + "Epoch: [ 10/ 10] Batch: [4500/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [4500/5500] Validation Acc: 0.99580\n", + "Epoch: [ 10/ 10] Batch: [5000/5500] Training Acc: 1.00000\n", + "Epoch: [ 10/ 10] Batch: [5000/5500] Validation Acc: 0.99560\n", + "OPTIMIZATION FINISHED\n" + ] + } + ], "source": [ "# MAXIMUM ACCURACY\n", "max_acc = 0.\n", @@ -379,7 +634,6 @@ " feed_dict={x: validation_data, y_: validation_labels, is_training: False})\n", " print(\"Epoch: [%3d/%3d] Batch: [%04d/%04d] Validation Acc: %.5f\" \n", " % (epoch + 1, training_epochs, iteration, total_batch, validation_accuracy))\n", - " \n", " # SAVE THE MODEL WITH HIGEST VALIDATION ACCURACY\n", " if validation_accuracy > max_acc:\n", " max_acc = validation_accuracy\n", @@ -398,7 +652,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -407,7 +661,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "TEST ACCURACY IS: 0.9959\n" + "TEST ACCURACY IS: 0.9961\n" ] } ], @@ -417,7 +671,6 @@ "\n", "# COMPUTE ACCURACY FOR TEST DATA\n", "test_size = test_labels.shape[0]\n", - "batch_size = TEST_BATCH_SIZE\n", "total_batch = int(test_size / batch_size)\n", "acc_buffer = []\n", "for i in range(total_batch):\n",