Update spr-base version number (#259)

Signed-off-by: Lv, Liang1 <[email protected]>
Co-authored-by: chen, suyue <[email protected]>

Author: lvliang-intel

.azure-pipelines/scripts/ut/env_setup.sh

@@ -20,7 +20,7 @@ echo "mxnet version is $mxnet_version"
 if [[ "${tensorflow_version}" == *"-official" ]]; then
     pip install tensorflow==${tensorflow_version%-official}
 elif [[ "${tensorflow_version}" == "spr-base" ]]; then
-    pip install /tf_dataset/tf_binary/221204/tensorflow*.whl
+    pip install /tf_dataset/tf_binary/221212/tensorflow*.whl
     if [[ $? -ne 0 ]]; then
       exit 1
     fi

neural_compressor/adaptor/tensorflow.py

@@ -83,7 +83,7 @@ def __init__(self, framework_specific_info):
 
         from pkg_resources import parse_version
         import tensorflow as tf
-        self.new_api = parse_version(tf.version.VERSION) == parse_version('2.11.0202242')
+        self.new_api = tf.version.VERSION in ('2.11.0202242', '2.11.0202250')
         self.qdq_enabled = self.itex_mode or self.format == 'QDQ' or self.new_api
         self.op_wise_sequences = self.query_handler.get_eightbit_patterns(self.qdq_enabled)
         self.optimization = self.query_handler.get_grappler_optimization_cfg()

neural_compressor/adaptor/tensorflow.yaml

@@ -16,7 +16,7 @@
 ---
 -
   version:
-    name: ['2.11.0202242']
+    name: ['2.11.0202242', '2.11.0202250']
 
   precisions:
     names: int8, uint8, bf16, fp32

neural_compressor/adaptor/tf_utils/graph_converter.py

@@ -36,6 +36,7 @@
 from .transform_graph.bias_correction import BiasCorrection
 from .util import generate_feed_dict, iterator_sess_run,version1_gt_version2,version1_eq_version2
 from .util import version1_gte_version2,version1_lte_version2,version1_lt_version2
+from .util import TF_SPR_BASE_VERSIONS
 from .quantize_graph.quantize_graph_for_intel_cpu import QuantizeGraphForIntel
 from .quantize_graph_common import QuantizeGraphHelper
 from .quantize_graph.qdq.optimize_qdq import OptimizeQDQGraph
@@ -268,7 +269,7 @@ def _check_tf_version(self):
             if version1_eq_version2(tf.version.VERSION, '1.15.0-up3'):
                 is_supported_version = True
 
-            if version1_eq_version2(tf.version.VERSION, '2.11.0202242'):
+            if tf.version.VERSION in TF_SPR_BASE_VERSIONS:
                 is_supported_version = True
                 is_sprbase_version = True
 

neural_compressor/adaptor/tf_utils/graph_converter_without_calib.py

@@ -44,7 +44,8 @@
 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, version1_lt_version2
+from .util import version1_gte_version2,version1_gt_version2,version1_eq_version2,version1_lt_version2
+from .util import TF_SPR_BASE_VERSIONS
 
 TF_SUPPORTED_MAX_VERSION = '2.11.0'
 TF_SUPPORTED_MIN_VERSION = '1.14.0'
@@ -118,8 +119,8 @@ def _check_tf_version(self):
 
             if version1_eq_version2(tf.version.VERSION, '1.15.0-up3'):
                 is_supported_version = True
-            
-            if version1_eq_version2(tf.version.VERSION, '2.11.0202242'):
+
+            if tf.version.VERSION in TF_SPR_BASE_VERSIONS:
                 is_supported_version = True
                 is_sprbase_version = True
 

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

@@ -20,7 +20,7 @@
 from neural_compressor.adaptor.tf_utils.graph_util import GraphAnalyzer
 from neural_compressor.adaptor.tf_utils.graph_util import GraphRewriterHelper as Helper
 from tensorflow.python.framework import dtypes
-from neural_compressor.adaptor.tf_utils.util import version1_eq_version2
+from neural_compressor.adaptor.tf_utils.util import TF_SPR_BASE_VERSIONS
 
 
 class FuseGeluOptimizer(GraphRewriterBase): # pragma: no cover
@@ -29,7 +29,7 @@ class FuseGeluOptimizer(GraphRewriterBase): # pragma: no cover
 
     def do_transformation(self):
         if not (tf.version.VERSION in ('1.15.0-up2','1.15.0-up3') or \
-           version1_eq_version2(tf.version.VERSION, '2.11.0202242')):
+           tf.version.VERSION in TF_SPR_BASE_VERSIONS):
             return self.model
 
         cur_graph = GraphAnalyzer()

neural_compressor/adaptor/tf_utils/util.py

@@ -30,6 +30,8 @@
 from .graph_util import GraphRewriterHelper
 from pkg_resources import parse_version
 
+TF_SPR_BASE_VERSIONS = ('2.11.0202242', '2.11.0202250')
+
 def version1_lt_version2(version1, version2):
     return parse_version(version1) < parse_version(version2)
 

test/itex/test_tensorflow_itex_basic.py

@@ -6,6 +6,7 @@
 import shutil
 import yaml
 import platform
+from tensorflow.python.platform import gfile
 from neural_compressor.adaptor.tf_utils.util import disable_random
 from neural_compressor.experimental import Quantization, Benchmark, common
 from neural_compressor.adaptor.tf_utils.util import version1_lt_version2, version1_gte_version2
@@ -239,6 +240,9 @@ def test_itex_benchmark_gpu(self):
         relu = tf.nn.relu(add)
         relu6 = tf.nn.relu6(relu, name='op_to_store')
         out_name = relu6.name.split(':')[0]
+        num_of_instance = 1
+        cores_per_instance = 1
+        log_file = ''
         with tf.compat.v1.Session() as sess:
             sess.run(tf.compat.v1.global_variables_initializer())
             output_graph_def = graph_util.convert_variables_to_constants(
@@ -257,11 +261,13 @@ def test_itex_benchmark_gpu(self):
             evaluator.b_dataloader = common.DataLoader(dataset)
             num_of_instance = evaluator.conf.usr_cfg.evaluation.performance.configs.num_of_instance
             cores_per_instance = evaluator.conf.usr_cfg.evaluation.performance.configs.cores_per_instance
+            log_file = '{}_{}_{}.log'.format(num_of_instance, cores_per_instance, 0)
+            if gfile.Exists(log_file):
+                os.remove(log_file)
             evaluator.model = output_graph
             evaluator('performance')
 
         found_multi_instance_log = False
-        log_file = '{}_{}_{}.log'.format(num_of_instance, cores_per_instance, 0)
         for file_name in os.listdir(os.getcwd()):
             if file_name == log_file:
                 found_multi_instance_log = True