Fix Keras Deserialization Issue of Lambda Layers (#1541)

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

Author: zehao-intel

.azure-pipelines/scripts/codeScan/pylint/pylint.sh

@@ -54,7 +54,7 @@ elif [ "${scan_module}" = "neural_insights" ]; then
 fi
 
 python -m pylint -f json --disable=R,C,W,E1129 --enable=line-too-long --max-line-length=120 --extension-pkg-whitelist=numpy --ignored-classes=TensorProto,NodeProto \
---ignored-modules=tensorflow,torch,torch.quantization,torch.tensor,torchvision,fairseq,mxnet,onnx,onnxruntime,intel_extension_for_pytorch,intel_extension_for_tensorflow,torchinfo,horovod,transformers \
+--ignored-modules=tensorflow,keras,torch,torch.quantization,torch.tensor,torchvision,fairseq,mxnet,onnx,onnxruntime,intel_extension_for_pytorch,intel_extension_for_tensorflow,torchinfo,horovod,transformers \
 /neural-compressor/${scan_module} > $log_dir/pylint.json
 
 exit_code=$?

docs/source/releases_info.md

@@ -19,8 +19,6 @@ The MSE tuning strategy does not work with the PyTorch adaptor layer. This strat
 
 The diagnosis function does not work with ONNX Runtime 1.13.1 for QDQ format quantization of ONNX models. It can not dump the output value of QDQ pairs since framework limitation.
 
-Keras version 2.13.0 is experiencing an open issue [18284](https://github.com/keras-team/keras/issues/18284) related to the absence of a `safe_mode` parameter in `tf.keras.models.model_from_json()`. This deficiency could potentially hinder the successful quantization of certain Keras models.
-
 ## Incompatible Changes
 
 [Neural Compressor v1.2](https://github.com/intel/neural-compressor/tree/v1.2) introduces incompatible changes in user facing APIs. Please refer to [incompatible changes](incompatible_changes.md) to know which incompatible changes are made in v1.2.

neural_compressor/adaptor/keras.py

@@ -42,6 +42,7 @@
 from .query import QueryBackendCapability
 
 tf = LazyImport("tensorflow")
+keras = LazyImport("keras")
 
 
 def _add_supported_quantized_objects(custom_objects):
@@ -519,6 +520,13 @@ def _check_quantize_mode(self, json_model):
     def _restore_model_from_json(self, json_model):
         from tensorflow.keras.models import model_from_json
 
+        from neural_compressor.utils.utility import version1_gte_version2
+
+        if version1_gte_version2(keras.__version__, "2.13.1"):
+            from keras.src.saving import serialization_lib
+
+            serialization_lib.enable_unsafe_deserialization()
+
         custom_objects = {}
         # We need to keep a dictionary of custom objects as our quantized library
         # is not recognized by keras.

neural_compressor/tensorflow/algorithms/static_quantize/keras.py

@@ -21,6 +21,7 @@
 import os
 from collections import OrderedDict, UserDict
 
+import keras
 import numpy as np
 import tensorflow as tf
 import yaml
@@ -486,6 +487,13 @@ def _restore_model_from_json(self, json_model):
         """Generate a keras model from json files."""
         from tensorflow.keras.models import model_from_json
 
+        from neural_compressor.tensorflow.utils import version1_gte_version2
+
+        if version1_gte_version2(keras.__version__, "2.13.1"):
+            from keras.src.saving import serialization_lib
+
+            serialization_lib.enable_unsafe_deserialization()
+
         custom_objects = {}
         # We need to keep a dictionary of custom objects as our quantized library
         # is not recognized by keras.