Neural Coder enable support of TensorFlow/Keras models to quantize (preliminary) (#217)

* Create tf_inc_static_quant.yaml

* Create inc.py

* Delete tf_inc_static_quant.yaml

* Update interface.py

* Update inc.py

Signed-off-by: zehao-intel <[email protected]>

Author: kaikaiyao

neural_coder/coders/tensorflow/inc.py

@@ -0,0 +1,48 @@
+# Copyright (c) 2022 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from ...utils.line_operation import get_line_left_hand_side
+
+class TensorFlowKerasINC(object):
+    def __init__(self, file) -> None:
+        self.file = file
+        self.result = []
+
+    def transform(self):
+        # import pdb
+        # pdb.set_trace()
+        lines = self.file.split('\n')
+        for line in lines:
+            if self.is_modify(line):
+                self.result.append(line)
+                self.result.append("from neural_compressor.conf.config import QuantConf")
+                self.result.append("from neural_compressor.experimental import Quantization")
+                self.result.append("from neural_compressor.experimental import common")
+                self.result.append("quant_config = QuantConf()")
+                self.result.append("quant_config.usr_cfg.model.framework = 'tensorflow'")
+                self.result.append("quantizer = Quantization(quant_config)")
+                self.result.append("quantizer.model = common.Model(" + model_name + ")")
+                self.result.append(model_name + " = quantizer.fit()")
+            else:
+                self.result.append(line)
+        for index, line in enumerate(self.result):
+            if index != len(self.result)-1:
+                self.result[index] += '\n'
+        return ''.join(self.result)
+
+    def is_modify(self, s):
+        if 'model = tf.' in s:
+            return True
+        else:
+            return False

neural_coder/interface.py

@@ -139,7 +139,10 @@ def enable(
         "pytorch_aliblade",
         "tensorflow_amp",
         "keras_amp",
-        "onnx_inc_static_quant_qlinear"
+        "tensorflow_inc",
+        "onnx_inc_static_quant_qlinear",
+        "onnx_inc_static_quant_qdq",
+        "onnx_inc_dynamic_quant",
     ]
     '''
 
@@ -350,6 +353,9 @@ def enable(
                 if "tensorflow_mixed_precision" in features:
                     from .coders.tensorflow.amp import TensorFlowKerasAMP
                     list_transformed_code[i] = TensorFlowKerasAMP(list_transformed_code[i]).transform()
+                if "tensorflow_inc" in features:
+                    from .coders.tensorflow.inc import TensorFlowKerasINC
+                    list_transformed_code[i] = TensorFlowKerasINC(list_transformed_code[i]).transform()
                 # Change Trainer to NLPTrainer (only for intel_extension_for_pytorch)
                 if "change_trainer_to_nlptrainer" in features:
                     from .coders.pytorch.change_trainer_to_nlptrainer import TrainerToNLPTrainer