Refine Keras Examples for INC New API

.azure-pipelines/scripts/codeScan/pyspelling/inc_dict.txt

@@ -2387,6 +2387,8 @@ amsgrad
 qoperator
 apis
 CPz
+PostTrainingQuantConfig
+dgpu
 Nsh
 UmK
 fe

examples/.config/model_params_tensorflow.json

@@ -40,10 +40,8 @@
       "model_src_dir": "image_recognition/keras_models/resnet101/quantization/ptq",
       "dataset_location": "/tf_dataset/dataset/imagenet",
       "input_model": "/tf_dataset2/models/tensorflow/resnet101_keras/saved_model/",
-      "yaml": "resnet101.yaml",
-      "strategy": "basic",
-      "batch_size": 1,
-      "new_benchmark": true
+      "main_script": "main.py",
+      "batch_size": 32
     },
     "resnet_v1_50_slim": {
       "model_src_dir": "image_recognition/tensorflow_models/quantization/ptq/slim",
@@ -121,10 +119,8 @@
       "model_src_dir": "image_recognition/keras_models/inception_v3/quantization/ptq",
       "dataset_location": "/tf_dataset/dataset/imagenet",
       "input_model": "/tf_dataset2/models/tensorflow/inception_v3_keras/saved_model/",
-      "yaml": "inception_v3.yaml",
-      "strategy": "basic",
-      "batch_size": 1,
-      "new_benchmark": true
+      "main_script": "main.py",
+      "batch_size": 32
     },
     "inception_v3_slim": {
       "model_src_dir": "image_recognition/tensorflow_models/quantization/ptq/slim",
@@ -319,10 +315,8 @@
       "model_src_dir": "image_recognition/keras_models/resnetv2_101/quantization/ptq",
       "dataset_location": "/tf_dataset/dataset/imagenet",
       "input_model": "/tf_dataset2/models/tensorflow/resnetv2_101_keras/saved_model",
-      "yaml": "resnetv2_101.yaml",
-      "strategy": "basic",
-      "batch_size": 1,
-      "new_benchmark": true
+      "main_script": "main.py",
+      "batch_size": 32
     },
     "resnetv2_152": {
       "model_src_dir": "image_recognition/tensorflow_models/quantization/ptq",
@@ -364,10 +358,8 @@
       "model_src_dir": "image_recognition/keras_models/mobilenet_v2/quantization/ptq",
       "dataset_location": "/tf_dataset/dataset/imagenet",
       "input_model": "/tf_dataset2/models/tensorflow/mobilenet_v2_keras/saved_model/",
-      "yaml": "mobilenet_v2.yaml",
-      "strategy": "basic",
-      "batch_size": 1,
-      "new_benchmark": true
+      "main_script": "main.py",
+      "batch_size": 32
     },
     "mobilenetv3": {
       "model_src_dir": "image_recognition/tensorflow_models/quantization/ptq",

examples/tensorflow/image_recognition/keras_models/inception_v3/quantization/ptq/README.md

@@ -12,9 +12,9 @@ This example can run on Intel CPUs and GPUs.
 # Install Intel® Neural Compressor
 pip install neural-compressor
 ```
-### 2. Install Intel Tensorflow
+### 2. Install Tensorflow
 ```shell
-pip install intel-tensorflow
+pip install tensorflow
 ```
 > Note: Supported Tensorflow [Version](../../../../../../../README.md).
 
@@ -26,7 +26,8 @@ Intel Extension for Tensorflow is mandatory to be installed for quantizing the m
 ```shell
 pip install --upgrade intel-extension-for-tensorflow[gpu]
 ```
-For any more details, please follow the procedure in [install-gpu-drivers](https://github.com/intel-innersource/frameworks.ai.infrastructure.intel-extension-for-tensorflow.intel-extension-for-tensorflow/blob/master/docs/install/install_for_gpu.md#install-gpu-drivers)
+Please refer to the [Installation Guides](https://dgpu-docs.intel.com/installation-guides/ubuntu/ubuntu-focal-dc.html) for latest Intel GPU driver installation.
+For any more details, please follow the procedure in [install-gpu-drivers](https://github.com/intel-innersource/frameworks.ai.infrastructure.intel-extension-for-tensorflow.intel-extension-for-tensorflow/blob/master/docs/install/install_for_gpu.md#install-gpu-drivers).
 
 #### Quantizing the model on Intel CPU(Experimental)
 Intel Extension for Tensorflow for Intel CPUs is experimental currently. It's not mandatory for quantizing the model on Intel CPUs.
@@ -43,12 +44,25 @@ python prepare_model.py   --output_model=/path/to/model
  ```
 `--output_model ` the model should be saved as SavedModel format or H5 format.
 
-## Write Yaml config file
-In examples directory, there is a inception_v3.yaml for tuning the model on Intel CPUs. The 'framework' in the yaml is set to 'tensorflow'. If running this example on Intel GPUs, the 'framework' should be set to 'tensorflow_itex' and the device in yaml file should be set to 'gpu'. The inception_v3_itex.yaml is prepared for the GPU case. We could remove most of items and only keep mandatory item for tuning. We also implement a calibration dataloader and have evaluation field for creation of evaluation function at internal neural_compressor.
+## Quantization Config
+The Quantization Config class has default parameters setting for running on Intel CPUs. If running this example on Intel GPUs, the 'backend' parameter should be set to 'itex' and the 'device' parameter should be set to 'gpu'.
+
+```
+config = PostTrainingQuantConfig(
+    device="gpu",
+    backend="itex",
+    ...
+    )
+```
 
 ## Run Command
+#### Tune
   ```shell
-  bash run_tuning.sh --config=inception_v3.yaml --input_model=./path/to/model --output_model=./result --eval_data=/path/to/evaluation/dataset --calib_data=/path/to/calibration/dataset
-  bash run_benchmark.sh --config=inception_v3.yaml --input_model=./path/to/model --mode=performance --eval_data=/path/to/evaluation/dataset
+  bash run_tuning.sh --input_model=./path/to/model --output_model=./result --dataset_location=/path/to/evaluation/dataset
   ```
 
+#### Benchmark
+  ```shell
+  bash run_benchmark.sh --input_model=./path/to/model --dataset_location=/path/to/evaluation/dataset --mode=performance
+  bash run_benchmark.sh --input_model=./path/to/model --dataset_location=/path/to/evaluation/dataset --mode=accuracy
+  ```