The following changes have been made:

・Text revisions
・File name corrections
・Parameter setting modifications

Author: Toshiki-Kato

…pytorch_post_training_quantization.ipynb …osenet_pytorch_mixed_precision_ptq.ipynbtutorials/notebooks/task_notebooks/pytorch/example_posenet_pytorch_post_training_quantization.ipynb renamed to tutorials/notebooks/task_notebooks/pytorch/example_posenet_pytorch_mixed_precision_ptq.ipynb tutorials/notebooks/task_notebooks/pytorch/example_posenet_pytorch_post_training_quantization.ipynb renamed to tutorials/notebooks/task_notebooks/pytorch/example_posenet_pytorch_mixed_precision_ptq.ipynb

@@ -9,10 +9,10 @@
     }
    },
    "source": [
-    "# PoseNet Post-Training Quantization in PyTorch using the Model Compression Toolkit(MCT)\n",
+    "# PoseNet and Mixed-Precision Post-Training Post-Training Quantization in PyTorch using the Model Compression Toolkit(MCT)\n",
     "\n",
     "## Overview\n",
-    "This quick-start guide explains how to use the **Model Compression Toolkit (MCT)** to quantize a PoseNet model. We will load a pre-trained model and quantize it using the MCT with **Post-Training Quantization (PTQ)**. \n",
+    "This quick-start guide explains how to use the **Model Compression Toolkit (MCT)** to quantize a PoseNet model. We will load a pre-trained model and quantize it using the MCT with **Mixed-Precision Post-Training Quantization (PTQ)** .\n",
     "\n",
     "## Summary\n",
     "In this tutorial, we will cover:\n",
@@ -181,7 +181,7 @@
     "- CALIB_ITER  \n",
     "  This parameter allows you to set how many samples to use when generating representative data for quantization.\n",
     "- WEIGHTS_COMPRESSION_RATIO  \n",
-    "  This parameter allows you to set the quantized ratio from the size of the 8-bit model's weights."
+    "  This parameter allows you to set the quantization ratio based on the weight size of the 8-bit model when using mixed-precision quantization."
    ]
   },
   {
@@ -296,7 +296,7 @@
    "id": "b64c60b0",
    "metadata": {},
    "source": [
-    "In this class, we process the downloaded COCO's dataset for evaluation during quantization and for use in calibration."
+    "In this class, we process the downloaded COCO's dataset for calibration during quantization and for use in evaluation."
    ]
   },
   {
@@ -485,13 +485,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": null,
    "id": "f25783c9",
    "metadata": {},
    "outputs": [],
    "source": [
     "configuration = mct.core.CoreConfig(\n",
-    "    mixed_precision_config=mct.core.MixedPrecisionQuantizationConfig(num_of_images=32))"
+    "    mixed_precision_config=mct.core.MixedPrecisionQuantizationConfig(num_of_images=CALIB_ITER))"
    ]
   },
   {