Update the relevant notebook with a stand alone dataset download

sony · Dec 28, 2023 · 545422c · 545422c
1 parent a135bed
commit 545422c
Showing 1 changed file with 13 additions and 12 deletions.
diff --git a/tutorials/notebooks/example_keras_imagenet.ipynb b/tutorials/notebooks/example_keras_imagenet.ipynb
@@ -217,17 +217,18 @@
    },
    "outputs": [],
    "source": [
-    "from typing import Iterator, Tuple\n",
+    "from typing import Generator\n",
     "\n",
     "REPRESENTATIVE_DATASET_FOLDER = '/content/imagenet/val'\n",
     "BATCH_SIZE = 50\n",
     "n_iter=10\n",
     "\n",
-    "def get_representative_dataset() -> Iterator:\n",
-    "    \"\"\"Load the dataset and create a representative dataset for quantization.\n",
+    "# Create representative dataset generator\n",
+    "def get_representative_dataset() -> Generator:\n",
+    "    \"\"\"A function that loads the dataset and returns a representative dataset generator.\n",
     "\n",
     "    Returns:\n",
-    "        Iterator: An iterator yielding batches of preprocessed images.\n",
+    "        Generator: A generator yielding batches of preprocessed images.\n",
     "    \"\"\"\n",
     "\n",
     "    # Load the dataset from folder\n",
@@ -238,11 +239,12 @@
     "        image_size=[224, 224],\n",
     "        shuffle=True,\n",
     "        crop_to_aspect_ratio=True,\n",
-    "        interpolation='bilinear')\n",
+    "        interpolation='bilinear')  \n",
+    "    # Preprocess the data\n",
     "    dataset = dataset.map(lambda x, y: (imagenet_preprocess_input(x, y)))\n",
     "\n",
-    "    def representative_dataset() -> Iterator[Tuple]:\n",
-    "        \"\"\"Generate representative dataset for quantization.\n",
+    "    def representative_dataset() -> Generator:\n",
+    "        \"\"\"A generator function that yields batch of preprocessed images.\n",
     "\n",
     "        Yields:\n",
     "            A batch of preprocessed images.\n",
@@ -372,7 +374,7 @@
     "id": "0ce4fc61-e13c-48be-9f7c-d441ad76a386"
    },
    "source": [
-    "In order to evaluate our models, we first need to load the validation dataset."
+    "In order to evaluate our models, we first need to load the validation dataset. As before, please ensure that the dataset path has been set correctly."
    ]
   },
   {
@@ -466,7 +468,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "Now, we can export the model to Keras and TFLite:"
+    "Now, we can export the model to Keras and TFLite. Please ensure that the file path has been set correctly."
    ],
    "metadata": {
     "id": "6YjIdiRRjgkL"
@@ -476,12 +478,11 @@
   {
    "cell_type": "code",
    "source": [
-    "import tempfile\n",
-    "_, tflite_file_path = tempfile.mkstemp('.tflite') # Path of exported model\n",
+    "tflite_file_path = '/content/model.tflite'\n",
     "mct.exporter.keras_export_model(model=quantized_model, save_model_path=tflite_file_path,\n",
     "                                serialization_format=mct.exporter.KerasExportSerializationFormat.TFLITE, quantization_format=mct.exporter.QuantizationFormat.FAKELY_QUANT)\n",
     "\n",
-    "_, keras_file_path = tempfile.mkstemp('.keras') # Path of exported model\n",
+    "keras_file_path = '/content/model.keras'\n",
     "mct.exporter.keras_export_model(model=quantized_model, save_model_path=keras_file_path)\n"
    ],
    "metadata": {