Automatic convert from py to ipynb

guoxiongfei · Jul 25, 2021 · d05e31e · d05e31e
1 parent 93dde25
commit d05e31e
Showing 1 changed file with 16 additions and 4 deletions.
diff --git a/4-1.Seq2Seq/Seq2Seq.ipynb b/4-1.Seq2Seq/Seq2Seq.ipynb
@@ -5,7 +5,6 @@
       "metadata": {},
       "source": [
         "# code by Tae Hwan Jung @graykode\n",
-        "import argparse\n",
         "import numpy as np\n",
         "import torch\n",
         "import torch.nn as nn\n",
@@ -32,6 +31,19 @@
         "    # make tensor\n",
         "    return torch.FloatTensor(input_batch), torch.FloatTensor(output_batch), torch.LongTensor(target_batch)\n",
         "\n",
+        "# make test batch\n",
+        "def make_testbatch(input_word):\n",
+        "    input_batch, output_batch = [], []\n",
+        "\n",
+        "    input_w = input_word + 'P' * (n_step - len(input_word))\n",
+        "    input = [num_dic[n] for n in input_w]\n",
+        "    output = [num_dic[n] for n in 'S' + 'P' * n_step]\n",
+        "\n",
+        "    input_batch = np.eye(n_class)[input]\n",
+        "    output_batch = np.eye(n_class)[output]\n",
+        "\n",
+        "    return torch.FloatTensor(input_batch).unsqueeze(0), torch.FloatTensor(output_batch).unsqueeze(0)\n",
+        "\n",
         "# Model\n",
         "class Seq2Seq(nn.Module):\n",
         "    def __init__(self):\n",
@@ -92,11 +104,11 @@
         "        optimizer.step()\n",
         "\n",
         "    # Test\n",
-        "    def translate(word, args):\n",
-        "        input_batch, output_batch, _ = make_batch([[word, 'P' * len(word)]], args)\n",
+        "    def translate(word):\n",
+        "        input_batch, output_batch = make_testbatch(word)\n",
         "\n",
         "        # make hidden shape [num_layers * num_directions, batch_size, n_hidden]\n",
-        "        hidden = torch.zeros(1, 1, args.n_hidden)\n",
+        "        hidden = torch.zeros(1, 1, n_hidden)\n",
         "        output = model(input_batch, hidden, output_batch)\n",
         "        # output : [max_len+1(=6), batch_size(=1), n_class]\n",
         "\n",