diff --git a/docs/examples/notebooks/decoder_examples.ipynb b/docs/examples/notebooks/decoder_examples.ipynb
index 30be5a7c8..b452528a2 100644
--- a/docs/examples/notebooks/decoder_examples.ipynb
+++ b/docs/examples/notebooks/decoder_examples.ipynb
@@ -28,6 +28,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import os\n",
     "from amd.rocal.pipeline import pipeline_def\n",
     "from amd.rocal.plugin.generic import ROCALClassificationIterator\n",
     "import amd.rocal.fn as fn\n",
@@ -37,11 +38,11 @@
     "%matplotlib inline\n",
     "\n",
     "seed = 1549361629\n",
-    "image_dir = \"../../../data/images/AMD-tinyDataSet/\"\n",
+    "image_dir = f\"{os.environ.get('ROCM_PATH', '/opt/rocm')}/share/rocal/test/data/images/AMD-tinyDataSet/\"\n",
     "batch_size = 4\n",
     "gpu_id = 0\n",
     "\n",
-    "def show_images(image_batch, device):\n",
+    "def show_images(image_batch):\n",
     "    columns = 4\n",
     "    rows = (batch_size + 1) // (columns)\n",
     "    fig = plt.figure(figsize = (32,(32 // columns) * rows))\n",
@@ -50,17 +51,14 @@
     "        plt.subplot(gs[j])\n",
     "        img = image_batch[j]\n",
     "        plt.axis(\"off\")\n",
-    "        if device == \"cpu\":\n",
-    "            plt.imshow(img)\n",
-    "        else:\n",
-    "            plt.imshow(cp.asnumpy(img))\n",
+    "        plt.imshow(img)\n",
     "\n",
     "\n",
     "def show_pipeline_output(pipe, device, device_id=0):\n",
     "    pipe.build()\n",
     "    data_loader = ROCALClassificationIterator(pipe, device, device_id)\n",
     "    images = next(iter(data_loader))\n",
-    "    show_images(images[0][0], device)\n"
+    "    show_images(images[0][0])\n"
    ]
   },
   {
@@ -70,7 +68,7 @@
    "source": [
     "## Image Decoder (CPU)\n",
     "\n",
-    "`decoders.image` decodes images stored in common formats (including JPEG, JPEG2000, TIFF, PNG)"
+    "`decoders.image` decodes images stored in JPEG format"
    ]
   },
   {
@@ -130,7 +128,7 @@
     "\n",
     "`decoders.image` with GPU backend uses rocJpeg to offload the JPEG decoding process to the GPU’s built-in hardware decoder, if supported\n",
     "\n",
-    "Note, that we repeat the examples shown above, changing only the device parameter. Both the operator and its other parameters stay the same and offer the same functionality - but now we use GPU acceleration.\n"
+    "Note, that we repeat the examples shown above, changing only the device and rocal_cpu parameters. Both the operator and its other parameters stay the same and offer the same functionality - but now we use GPU acceleration.\n"
    ]
   },
   {
@@ -139,7 +137,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pipe = image_decoder_pipeline(batch_size=batch_size, num_threads=1, device_id=gpu_id, rocal_cpu=True, tensor_layout=types.NHWC, \n",
+    "pipe = image_decoder_pipeline(batch_size=batch_size, num_threads=1, device_id=gpu_id, rocal_cpu=False, tensor_layout=types.NHWC, \n",
     "        reverse_channels=True, mean=[0,0,0], std = [255,255,255], device=\"gpu\")\n",
     "show_pipeline_output(pipe, device=\"gpu\")"
    ]
@@ -162,7 +160,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pipe = image_decoder_random_crop_pipeline(batch_size=batch_size, num_threads=1, device_id=gpu_id, rocal_cpu=True, tensor_layout=types.NHWC, reverse_channels=True, \n",
+    "pipe = image_decoder_random_crop_pipeline(batch_size=batch_size, num_threads=1, device_id=gpu_id, rocal_cpu=False, tensor_layout=types.NHWC, reverse_channels=True, \n",
     "                                          mean=[0,0,0], std = [255,255,255], device=\"gpu\")\n",
     "show_pipeline_output(pipe, device=\"gpu\")"
    ]