Fix TF2.10.0 UT fail (#1188)

neural_compressor/adaptor/tf_utils/graph_converter.py

@@ -68,7 +68,7 @@
 from .graph_util import GraphRewriterHelper as Helper
 
 
-TF_SUPPORTED_MAX_VERSION = '2.9.1'
+TF_SUPPORTED_MAX_VERSION = '2.10.0'
 TF_SUPPORTED_MIN_VERSION = '1.14.0'
 
 logger = logging.getLogger()
@@ -247,7 +247,7 @@ def _check_tf_version(self):
             if version1_gte_version2(tf.version.VERSION, '2.9.0'):
                 is_supported_version = True
 
-            if tf.version.VERSION == '1.15.0-up3':
+            if version1_eq_version2(tf.version.VERSION, '1.15.0-up3'):
                 is_supported_version = True
 
         except Exception as e:

neural_compressor/adaptor/tf_utils/graph_converter_without_calib.py

@@ -44,9 +44,9 @@
 from .graph_rewriter.int8.post_quantized_op_cse import PostCseOptimizer
 from .graph_rewriter.int8.meta_op_optimizer import MetaInfoChangingMemOpOptimizer
 from .graph_rewriter.int8.rnn_convert import QuantizedRNNConverter
+from .util import version1_gte_version2,version1_gt_version2,version1_eq_version2
 
-
-TF_SUPPORTED_MAX_VERSION = '2.9.1'
+TF_SUPPORTED_MAX_VERSION = '2.10.0'
 TF_SUPPORTED_MIN_VERSION = '1.14.0'
 
 logger = logging.getLogger()
@@ -107,29 +107,31 @@ def _check_tf_version(self):
             if IsMklEnabled() and (TF_SUPPORTED_MIN_VERSION <= tf.version.VERSION):
                 is_supported_version = True
 
-            if tf.version.VERSION >= '2.6.0' and os.getenv('TF_ENABLE_ONEDNN_OPTS') == '1':
+            if version1_gte_version2(tf.version.VERSION, '2.6.0') and os.getenv('TF_ENABLE_ONEDNN_OPTS') == '1':
+                is_supported_version = True
+
+            if version1_gte_version2(tf.version.VERSION, '2.9.0'):
                 is_supported_version = True
 
-            if tf.version.VERSION >= '2.9.0':
+            if version1_eq_version2(tf.version.VERSION, '1.15.0-up3'):
                 is_supported_version = True
 
         except Exception as e:
             raise ValueError(e)
         finally:# pragma: no cover
-            if tf.version.VERSION > TF_SUPPORTED_MAX_VERSION:
+            if version1_gt_version2(tf.version.VERSION, TF_SUPPORTED_MAX_VERSION):
                 logger.warning(
                     str('Please note the {} version of Intel® Optimizations for '
                         'TensorFlow is not fully verified! '
                         'Suggest to use the versions '
                         'between {} and {} if meet problem.').format(tf.version.VERSION,
                                                                      TF_SUPPORTED_MIN_VERSION,
                                                                      TF_SUPPORTED_MAX_VERSION))
-            if tf.version.VERSION == '2.5.0' and os.getenv('TF_ENABLE_MKL_NATIVE_FORMAT') != '0':
+            if version1_eq_version2(tf.version.VERSION, '2.5.0') and os.getenv('TF_ENABLE_MKL_NATIVE_FORMAT') != '0':
                 logger.fatal("Please set environment variable TF_ENABLE_MKL_NATIVE_FORMAT=0 "
                              "when TensorFlow 2.5.0 installed.")
 
-            if tf.version.VERSION >= '2.6.0' and tf.version.VERSION < '2.9.0' \
-                    and os.getenv('TF_ENABLE_ONEDNN_OPTS') != '1':
+            if version1_gte_version2(tf.version.VERSION, '2.6.0') and os.getenv('TF_ENABLE_ONEDNN_OPTS') != '1':
                 logger.fatal("Please set environment variable TF_ENABLE_ONEDNN_OPTS=1 "
                              "when TensorFlow >= 2.6.0 and < 2.9.0 installed.")
 

neural_compressor/adaptor/tf_utils/graph_rewriter/generic/dummy_biasadd.py

@@ -39,11 +39,8 @@ def do_transformation(self):
         valid_ops = ('BiasAdd', 'Add', 'AddV2', 'AddN')
         target_nodes = g.query_fusion_pattern_nodes([['MatMul', 'Conv2D'],])
         for i in target_nodes:
-            # only apply this pass for tensorflow release 2.9.1 and lower version for
-            # old quantization API.
+            # only apply this pass for tensorflow old quantization API, pre_optimize does this check
             # use conv+dummy_biasadd+relu because TF do not support conv+relu now. 
-            if version1_gt_version2(tf.version.VERSION, '2.9.1'):
-                continue
             if i[0] in self.outputs:
                 continue
             next_node_names = graph_info[i[0]].outputs

neural_compressor/adaptor/tf_utils/quantize_graph/quantize_graph_base.py

@@ -627,7 +627,7 @@ def _add_quantize_down_nodes(self,
             # Add a RequantizationRange node for finding the min and max values.
             requant_range_node = helper.create_node(
                 "RequantizationRangePerChannel"
-                if self.per_channel else "RequantizationRange",
+                if self.per_channel or original_node.op == 'DepthwiseConv2dNative' else "RequantizationRange",
                 original_node.name + "_eightbit_requant_range", quantized_outputs)
 
             if self.per_channel:
@@ -661,7 +661,8 @@ def _add_quantize_down_nodes(self,
             ]
 
         requantize_node = helper.create_node(
-            "RequantizePerChannel" if self.per_channel else "Requantize",
+            "RequantizePerChannel" if self.per_channel or original_node.op == 'DepthwiseConv2dNative' \
+            else "Requantize",
             original_node.name + "_eightbit_requantize",
             quantized_outputs + min_max_inputs)
         if self.per_channel:

test/adaptor/tensorflow_adaptor/test_tensorboard.py

@@ -10,6 +10,7 @@
 from tensorflow.core.framework import node_def_pb2
 from tensorflow.python.framework import tensor_util
 from tensorflow.python.framework import dtypes
+from neural_compressor.adaptor.tf_utils.util import version1_gt_version2
 tf.compat.v1.disable_eager_execution()
 
 def build_fake_yaml():
@@ -195,7 +196,8 @@ def tearDownClass(self):
         shutil.rmtree("saved", ignore_errors=True)
         shutil.rmtree("runs/", ignore_errors=True)
 
-    @unittest.skipIf(tf.version.VERSION > '2.5.0', " Skip test_bf16_fallback case for tf 2.6.0 and above.")
+    @unittest.skipIf(version1_gt_version2(tf.version.VERSION, '2.5.0'), \
+                     "Skip test_bf16_fallback case for tf 2.6.0 and above.")
     def test_run_basic_one_trial(self):
         from neural_compressor.experimental import Quantization, common