edited tutorial

Author: Karadarya

examples/tutorial_emnist_tflm/conversion_tutorial/model_conversion.ipynb

@@ -300,6 +300,22 @@
     "interpreter.allocate_tensors()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Full test set contains 20800 samples. Evaluating int8 model on it might take more than 10 minutes. If you want to get estimation faster, please, limit number of samples to be evaluated by reducing **max_samples** value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "max_samples = 20800"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -314,7 +330,7 @@
     "\n",
     "    prediction_values = []\n",
     "    \n",
-    "    for test_image in preprocessed_test_images:\n",
+    "    for test_image in preprocessed_test_images[:max_samples]:\n",
     "        # Pre-processing: add batch dimension, quantize and convert inputs to int8 to match with\n",
     "        # the model's input data format.\n",
     "        test_image = np.expand_dims(test_image, axis=0) #.astype(np.float32)\n",
@@ -451,7 +467,7 @@
     "* copy *generated/model.h* and *generated/test_samples.cc* to *../src*\n",
     "* open top folder of this tutorial (*tutorial_emnist_tflm*) in terminal and build and run application:\n",
     "```\n",
-    "make app run\n",
+    "gmake app run\n",
     "```"
    ]
   }

examples/tutorial_emnist_tflm/src/test_samples.cc

@@ -1163,4 +1163,4 @@ TestSample sample25 = {
 const TestSample test_samples[kNumSamples] = {sample1, sample2, sample3, sample4, 
     sample5, sample6, sample7, sample8, sample9, sample10, sample11, sample12, 
     sample13, sample14, sample15, sample16, sample17, sample18, sample19, sample20, 
-    sample21, sample22, sample23, sample24, sample25, };
+    sample21, sample22, sample23, sample24, sample25 };