From 78294662b4b7ef37b67568a0c3e8e51424f1efe1 Mon Sep 17 00:00:00 2001
From: Jeff Moe <moe@spacecruft.org>
Date: Mon, 30 May 2022 17:59:58 -0600
Subject: [PATCH] Use tensorflow keras

---
 notebooks/witzit-train.ipynb | 82 +++++++++++++++++++++++++++---------
 1 file changed, 61 insertions(+), 21 deletions(-)

diff --git a/notebooks/witzit-train.ipynb b/notebooks/witzit-train.ipynb
index 53d2211..8bbed94 100644
--- a/notebooks/witzit-train.ipynb
+++ b/notebooks/witzit-train.ipynb
@@ -39,23 +39,63 @@
    "outputs": [],
    "source": [
     "from __future__ import print_function\n",
-    "import os\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "import datetime\n",
-    "import numpy as np\n",
-    "import tensorflow.python.keras\n",
-    "from tensorflow.python.keras import Sequential\n",
-    "from tensorflow.python.keras.layers import Activation, Dropout, Flatten, Dense\n",
-    "from tensorflow.python.keras.preprocessing.image import ImageDataGenerator\n",
-    "from tensorflow.python.keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D\n",
-    "from tensorflow.python.keras import optimizers\n",
-    "from tensorflow.python.keras.preprocessing import image\n",
-    "from tensorflow.python.keras.models import load_model\n",
-    "from tensorflow.python.keras.preprocessing.image import load_img\n",
-    "from tensorflow.python.keras.preprocessing.image import img_to_array\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import tensorflow as tf\n",
+    "from tensorflow import keras\n",
+    "from tensorflow.keras import Sequential\n",
+    "from tensorflow.keras.layers import Activation, Dropout, Flatten, Dense\n",
+    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
+    "from tensorflow.keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D\n",
+    "from tensorflow.keras import optimizers\n",
+    "from tensorflow.keras.preprocessing import image\n",
+    "from tensorflow.keras.models import load_model\n",
     "from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout, MaxPooling2D\n",
-    "from tensorflow.python.keras.models import Model\n",
-    "from tensorflow.python.keras.layers import Input, concatenate\n",
-    "\n",
+    "from tensorflow.keras.models import Model\n",
+    "from tensorflow.keras.layers import Input, concatenate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tf.get_logger().setLevel('ERROR')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# Visualization\n",
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
@@ -242,9 +282,9 @@
     "os.mkdir(\"logs\")\n",
     "log_dir = \"logs\"\n",
     "# log_dir=\"logs/fit/\" + datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n",
-    "# tensorboard_callback = tensorflow.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)\n",
-    "# tensorboard_callback = tensorflow.keras.callbacks.TensorBoard(log_dir=log_dir)\n",
-    "tensorboard_callback = tensorflow.keras.callbacks.TensorBoard(\n",
+    "# tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)\n",
+    "# tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir)\n",
+    "tensorboard_callback = tf.keras.callbacks.TensorBoard(\n",
     "    log_dir=log_dir,\n",
     "    histogram_freq=1,\n",
     "    write_graph=True,\n",
@@ -288,7 +328,7 @@
    "outputs": [],
    "source": [
     "# witzitoptimizer = 'adam'\n",
-    "witzitoptimizer = tensorflow.keras.optimizers.Adam(\n",
+    "witzitoptimizer = tf.keras.optimizers.Adam(\n",
     "    learning_rate=0.001, beta_1=0.9, beta_2=0.999, amsgrad=True\n",
     ")\n",
     "witzitloss = \"binary_crossentropy\"\n",
@@ -412,7 +452,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from tensorflow.keras.utils import plot_model"
+    "from tf.keras.utils import plot_model"
    ]
   },
   {
@@ -438,7 +478,7 @@
    "outputs": [],
    "source": [
     "# from IPython.display import SVG\n",
-    "# from tensorflow.keras.utils import model_to_dot\n",
+    "# from tf.keras.utils import model_to_dot\n",
     "# SVG(model_to_dot(model).create(prog='dot', format='svg'))"
    ]
   }