seq2seq has funcs with same name and it's not clear. renamed for clar…

…ity.
fastai · Aug 16, 2017 · 60754a3 · 60754a3
1 parent 20e8524
commit 60754a3
Showing 1 changed file with 22 additions and 24 deletions.
diff --git a/deeplearning2/seq2seq-translation.ipynb b/deeplearning2/seq2seq-translation.ipynb
@@ -61,7 +61,7 @@
     "\n",
     "[This question on Open Data Stack Exchange](http://opendata.stackexchange.com/questions/3888/dataset-of-sentences-translated-into-many-languages) pointed me to the open translation site http://tatoeba.org/ which has downloads available at http://tatoeba.org/eng/downloads - and better yet, someone did the extra work of splitting language pairs into individual text files here: http://www.manythings.org/anki/\n",
     "\n",
-    "The English to French pairs are too big to include in the repo, so download to `data/eng-fra.txt` before continuing. The file is a tab separated list of translation pairs:\n",
+    "The English to French pairs are too big to include in the repo, so download to `data/fra.txt` before continuing. The file is a tab separated list of translation pairs:\n",
     "\n",
     "```\n",
     "I am cold.    Je suis froid.\n",
@@ -168,11 +168,11 @@
    },
    "outputs": [],
    "source": [
-    "def readLangs(lang1, lang2, reverse=False):\n",
+    "def readLangs(lang1, lang2, pairs_file, reverse=False):\n",
     "    print(\"Reading lines...\")\n",
     "\n",
     "    # Read the file and split into lines\n",
-    "    lines = open('data/%s-%s.txt' % (lang1, lang2)).read().strip().split('\\n')\n",
+    "    lines = open('data/%s' % (pairs_file)).read().strip().split('\\n')\n",
     "    \n",
     "    # Split every line into pairs and normalize\n",
     "    pairs = [[normalizeString(s) for s in l.split('\\t')] for l in lines]\n",
@@ -268,8 +268,8 @@
     }
    ],
    "source": [
-    "def prepareData(lang1, lang2, reverse=False):\n",
-    "    input_lang, output_lang, pairs = readLangs(lang1, lang2, reverse)\n",
+    "def prepareData(lang1, lang2, pairs_file, reverse=False):\n",
+    "    input_lang, output_lang, pairs = readLangs(lang1, lang2, pairs_file, reverse)\n",
     "    print(\"Read %s sentence pairs\" % len(pairs))\n",
     "    pairs = filterPairs(pairs)\n",
     "    print(\"Trimmed to %s sentence pairs\" % len(pairs))\n",
@@ -282,7 +282,7 @@
     "    print(output_lang.name, output_lang.n_words)\n",
     "    return input_lang, output_lang, pairs\n",
     "\n",
-    "input_lang, output_lang, pairs = prepareData('eng', 'fra', True)\n",
+    "input_lang, output_lang, pairs = prepareData('eng', 'fra', 'fra.txt', True)\n",
     "print(random.choice(pairs))"
    ]
   },
@@ -542,8 +542,7 @@
    "cell_type": "markdown",
    "metadata": {
     "deletable": true,
-    "editable": true,
-    "heading_collapsed": true
+    "editable": true
    },
    "source": [
     "## Training\n",
@@ -559,8 +558,7 @@
    "metadata": {
     "collapsed": false,
     "deletable": true,
-    "editable": true,
-    "hidden": true
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -597,8 +595,7 @@
    "metadata": {
     "collapsed": false,
     "deletable": true,
-    "editable": true,
-    "hidden": true
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -621,8 +618,7 @@
    "metadata": {
     "collapsed": false,
     "deletable": true,
-    "editable": true,
-    "hidden": true
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -664,9 +660,7 @@
    "cell_type": "markdown",
    "metadata": {
     "deletable": true,
-    "editable": true,
-    "heading_collapsed": true,
-    "hidden": true
+    "editable": true
    },
    "source": [
     "### Attention"
@@ -678,15 +672,14 @@
    "metadata": {
     "collapsed": false,
     "deletable": true,
-    "editable": true,
-    "hidden": true
+    "editable": true
    },
    "outputs": [],
    "source": [
     "# TODO: Make this change during training\n",
     "teacher_forcing_ratio = 0.5\n",
     "\n",
-    "def train(input_variable, target_variable, encoder, decoder, encoder_optimizer, \n",
+    "def attn_train(input_variable, target_variable, encoder, decoder, encoder_optimizer, \n",
     "          decoder_optimizer, criterion, max_length=MAX_LENGTH):\n",
     "    encoder_hidden = encoder.initHidden()\n",
     "\n",
@@ -739,8 +732,7 @@
    "cell_type": "markdown",
    "metadata": {
     "deletable": true,
-    "editable": true,
-    "heading_collapsed": true
+    "editable": true
    },
    "source": [
     "# Plotting results\n",
@@ -754,8 +746,7 @@
    "metadata": {
     "collapsed": false,
     "deletable": true,
-    "editable": true,
-    "hidden": true
+    "editable": true
    },
    "outputs": [],
    "source": [
@@ -1002,6 +993,13 @@
     "You could simply run `plt.matshow(attentions)` to see attention output displayed as a matrix, with the columns being input steps and rows being output steps:"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "NOTE: This only works when using the attentional decoder, if you've been following the notebook to this point you are using the standard decoder."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 20,