Merge pull request #586 from autonomio/callbacks_submodule

Make callbacks to a submodule

docs/Energy_Draw.md

@@ -9,7 +9,7 @@ A callback for recording GPU power draw (watts) on epoch begin and end. The call
 
 Before `model.fit()` in the input model:
 
-`power_draw = PowerDrawCallback()`
+`power_draw = PowerDraw()`
 
 Then use `power_draw` as you would callbacks in general:
 

docs/Monitoring.md

@@ -7,29 +7,30 @@ There are several options for monitoring the experiment.
 Scan(disable_progress_bar=True)
 
 # enable live training plot
-from talos import live
+from talos.callbacks import TrainingPlot
+
 out = model.fit(X,
                 Y,
                 epochs=20,
-                callbacks=[live()])
+                callbacks=[TrainingPlot()])
 
 # turn on parameter printing
 Scan(print_params=True)
 ```
 
 **Progress Bar :** A round-by-round updating progress bar that shows the remaining rounds, together with a time estimate to completion. Progress bar is on by default.
 
-**Live Monitoring :** Live monitoring provides an epoch-by-epoch updating line graph that is enabled through the `live()` custom callback.
+**Live Monitoring :** Live monitoring provides an epoch-by-epoch updating line graph that is enabled through the `TrainingPlot()` custom callback.
 
 **Round Hyperparameters :** Displays the hyperparameters for each permutation. Does not work together with live monitoring.
 
 ### Local Monitoring
 
-Epoch-by-epoch training data is available during the experiment using the `ExperimentLogCallback`:
+Epoch-by-epoch training data is available during the experiment using the `ExperimentLog`:
 
 ```python
 model.fit(...
-          callbacks=[talos.utils.ExperimentLogCallback('experiment_name', params)])
+          callbacks=[talos.callbacks.ExperimentLog('experiment_name', params)])
 ```
 Here `params` is the params dictionary in the `Scan()` input model. Both
 `experiment_name` and `experiment_id` should match with the current experiment,

docs/_coverpage.md

@@ -1,6 +1,6 @@
 ![logo](_media/talos_logo_bg.png)
 
-## v1.2.4
+## v1.2.5
 
 > Hyperparameter Experiments with Tensorflow, PyTorch and Keras
 

docs/index.html

@@ -16,7 +16,7 @@
   <div id="app"></div>
   <script>
     window.$docsify = {
-      name: 'Talos 1.2.4',
+      name: 'Talos 1.2.5',
       repo: 'https://github.com/autonomio/talos',
       coverpage: true,
       loadSidebar: true,

examples/Hyperparameter Optimization on Keras with Breast Cancer Data.ipynb

@@ -2,21 +2,20 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "<img src='https://raw.githubusercontent.com/autonomio/hyperio/master/logo.png' width=250px>"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "This notebook is a compliment to the *Hyperparameter Optimization on Keras* article. "
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## Overview\n",
     "\n",
@@ -29,20 +28,19 @@
     "3) Defining the Parameter Space Boundaries \n",
     "\n",
     "4) Running the Experiment"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## 1. The Required Inputs and Data"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "from tensorflow.keras.models import Sequential\n",
     "from tensorflow.keras.layers import Dropout, Dense\n",
@@ -52,33 +50,33 @@
     "import sys\n",
     "sys.path.insert(0, '/Users/mikko/Documents/GitHub/talos')\n",
     "import talos"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "# then we load the dataset\n",
     "x, y = talos.templates.datasets.breast_cancer()\n",
     "\n",
     "# and normalize every feature to mean 0, std 1\n",
     "x = talos.utils.rescale_meanzero(x)"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## 2. Creating the Keras Model"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "# first we have to make sure to input data and params into the function\n",
     "def breast_cancer_model(x_train, y_train, x_val, y_val, params):\n",
@@ -100,25 +98,25 @@
     "    history = model.fit(x_train, y_train, \n",
     "                        validation_data=[x_val, y_val],\n",
     "                        batch_size=params['batch_size'],\n",
-    "                        callbacks=[talos.utils.live()],\n",
+    "                        callbacks=[talos.callbacks.TrainingPlot()],\n",
     "                        epochs=params['epochs'],\n",
     "                        verbose=0)\n",
     "\n",
     "    return history, model"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## 3. Defining the Parameter Space Boundary"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "# then we can go ahead and set the parameter space\n",
     "p = {'first_neuron':[9,10,11],\n",
@@ -131,22 +129,20 @@
     "     'losses': ['binary_crossentropy'],\n",
     "     'activation':['relu', 'elu'],\n",
     "     'last_activation': ['sigmoid']}"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {}
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## 4. Starting the Experiment"
-   ]
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
    "source": [
     "# and run the experiment\n",
     "t = talos.Scan(x=x,\n",
@@ -155,7 +151,11 @@
     "               params=p,\n",
     "               experiment_name='breast_cancer',\n",
     "               round_limit=10)"
-   ]
+   ],
+   "outputs": [],
+   "metadata": {
+    "collapsed": true
+   }
   }
  ],
  "metadata": {
@@ -179,4 +179,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}