so much betterrrrrr

Author: jshtaway

word_based.ipynb

@@ -96,18 +96,18 @@
     "#--- --- ---- --- ---- --- ---- ---- --- ----- ---- ---\n",
     "# -- Write Files ---- ---- ---- --- ---- --- --- --- -- \n",
     "#--- --- ---- --- ---- --- ---- ---- --- ----- ---- ---\n",
-    "def writeFiles(model, modelName, history_callback, modelList, seq_length, total_sequences, epochs, batch_size):\n",
+    "def writeFiles(model, modelName, history_callback, modelList, seq_length, total_sequences, epochs, batch_size, results_path):\n",
     "    loss_history = history_callback.history\n",
     "    \n",
     "    # save the model to file\n",
-    "    model.save('m_' + modelName + '.h5')\n",
+    "    model.save(results_path.rstrip('/') + '/m_' + modelName + '.h5')\n",
     "    loss_history['seq_length'] = seq_length\n",
     "    loss_history['total_sequences'] = total_sequences\n",
     "    loss_history['batch_size'] = batch_size\n",
     "    loss_history['epochs'] = epochs\n",
     "    \n",
     "    # save losses\n",
-    "    with open('info_' + modelName + '.txt', 'w+') as f:\n",
+    "    with open(results_path.rstrip('/') + '/info_' + modelName + '.txt', 'w+') as f:\n",
     "        f.write(str(modelList))\n",
     "        f.write('\\n')\n",
     "        f.write(str(loss_history))\n"
@@ -219,20 +219,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 14,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "SyntaxError",
-     "evalue": "positional argument follows keyword argument (<ipython-input-8-b8a592ace547>, line 61)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-8-b8a592ace547>\"\u001b[0;36m, line \u001b[0;32m61\u001b[0m\n\u001b[0;31m    writeFiles(model, modelName, history_callback, modelList, seq_length, total_sequences = len(sequences), epochs, batch_size)\u001b[0m\n\u001b[0m                                                                                                           ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m positional argument follows keyword argument\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "def trainModelComplete():\n",
+    "def trainModelComplete(results_path):\n",
     "    from keras.utils import to_categorical\n",
     "    \n",
     "    #--- PARAMETERS --- --- --- ---- --- --- ---- ---- --- ----- --- --- ----\n",
@@ -299,7 +290,7 @@
     "    #-- Fit model -- ---- --- --- --- ---- --- --- ---- --- --- --- --- --- --- --- --- \n",
     "    history_callback = modelFit(model, modelName, X, y, seq_length, batch_size, epochs)\n",
     "    #-- Save history and final model --- -\n",
-    "    writeFiles(model, modelName, history_callback, modelList, seq_length, len(sequences), epochs, batch_size)"
+    "    writeFiles(model, modelName, history_callback, modelList, seq_length, len(sequences), epochs, batch_size, results_path)"
    ]
   },
   {

word_based.py

@@ -82,18 +82,18 @@ def modelFit(model, modelName, X, y, seq_length, batch_size, epochs):
 #--- --- ---- --- ---- --- ---- ---- --- ----- ---- ---
 # -- Write Files ---- ---- ---- --- ---- --- --- --- -- 
 #--- --- ---- --- ---- --- ---- ---- --- ----- ---- ---
-def writeFiles(model, modelName, history_callback, modelList, seq_length, total_sequences, epochs, batch_size):
+def writeFiles(model, modelName, history_callback, modelList, seq_length, total_sequences, epochs, batch_size, results_path):
     loss_history = history_callback.history
 
     # save the model to file
-    model.save('m_' + modelName + '.h5')
+    model.save(results_path.rstrip('/') + '/m_' + modelName + '.h5')
     loss_history['seq_length'] = seq_length
     loss_history['total_sequences'] = total_sequences
     loss_history['batch_size'] = batch_size
     loss_history['epochs'] = epochs
 
     # save losses
-    with open('info_' + modelName + '.txt', 'w+') as f:
+    with open(results_path.rstrip('/') + '/info_' + modelName + '.txt', 'w+') as f:
         f.write(str(modelList))
         f.write('\n')
         f.write(str(loss_history))
@@ -182,10 +182,10 @@ def defineModel(vocab_size, seq_length, modelList, length, input_shape):
     return model, modelName
 
 
-# In[8]:
+# In[14]:
 
 
-def trainModelComplete():
+def trainModelComplete(results_path):
     from keras.utils import to_categorical
 
     #--- PARAMETERS --- --- --- ---- --- --- ---- ---- --- ----- --- --- ----
@@ -252,7 +252,7 @@ def trainModelComplete():
     #-- Fit model -- ---- --- --- --- ---- --- --- ---- --- --- --- --- --- --- --- --- 
     history_callback = modelFit(model, modelName, X, y, seq_length, batch_size, epochs)
     #-- Save history and final model --- -
-    writeFiles(model, modelName, history_callback, modelList, seq_length, len(sequences), epochs, batch_size)
+    writeFiles(model, modelName, history_callback, modelList, seq_length, len(sequences), epochs, batch_size, results_path)
 
 
 # In[9]: