use_internal_tpc = True # Use MCT's built-in Target Platform Capabilities

Author: KazunoriSumiya

tutorials/notebooks/mct_features_notebooks/keras/example_keras_mct_wrapper.ipynb

@@ -442,7 +442,7 @@
     "    # Configuration for GPTQ quantization\n",
     "    method = 'GPTQ'                   # Gradient-based Post-Training Quantization\n",
     "    framework = 'tensorflow'          # Target framework (Keras/TensorFlow)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = False                  # Disable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for GPTQ\n",
@@ -509,7 +509,7 @@
     "    # Configuration for GPTQ with mixed precision\n",
     "    method = 'GPTQ'                   # Gradient-based Post-Training Quantization\n",
     "    framework = 'tensorflow'          # Target framework (Keras/TensorFlow)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = True                   # Enable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for GPTQ with Mixed Precision\n",

tutorials/notebooks/mct_features_notebooks/pytorch/example_pytorch_mct_wrapper.ipynb

@@ -301,7 +301,7 @@
     "    # Configuration for PyTorch PTQ quantization\n",
     "    method = 'PTQ'                    # Post-Training Quantization method\n",
     "    framework = 'pytorch'             # Target framework (PyTorch)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = False                  # Disable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for PyTorch PTQ\n",
@@ -368,7 +368,7 @@
     "    # Configuration for PyTorch PTQ with mixed precision\n",
     "    method = 'PTQ'                    # Post-Training Quantization method\n",
     "    framework = 'pytorch'             # Target framework (PyTorch)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = True                   # Enable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for PyTorch PTQ with Mixed Precision\n",
@@ -435,7 +435,7 @@
     "    # Configuration for PyTorch GPTQ quantization\n",
     "    method = 'GPTQ'                   # Gradient-based Post-Training Quantization\n",
     "    framework = 'pytorch'             # Target framework (PyTorch)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = False                  # Disable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for PyTorch GPTQ\n",
@@ -501,7 +501,7 @@
     "    # Configuration for PyTorch GPTQ with mixed precision\n",
     "    method = 'GPTQ'                   # Gradient-based Post-Training Quantization\n",
     "    framework = 'pytorch'             # Target framework (PyTorch)\n",
-    "    use_internal_tpc = True                # Use external EdgeMDT Target Platform Capabilities\n",
+    "    use_internal_tpc = True                # Use MCT's built-in Target Platform Capabilities\n",
     "    use_mixed_precision = True                   # Enable mixed-precision quantization\n",
     "\n",
     "    # Parameter configuration for PyTorch GPTQ with Mixed Precision\n",