fix bug in ipex fallback (#918)

Signed-off-by: Xin He <[email protected]>
intel · May 30, 2023 · b4f9c72 · b4f9c72
1 parent 1e1d706
commit b4f9c72
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Showing 4 changed files with 74 additions and 15 deletions.
diff --git a/neural_compressor/adaptor/pytorch_ipex.yaml b/neural_compressor/adaptor/pytorch_ipex.yaml
@@ -22,7 +22,7 @@
   fp32: ['*'] # '*' means all op types
   int8: &1_12_capabilities {
     'static': &cap_1_12_s8 {
-            'conv2d': &cap_s8_1_12_Conv2d {
+            'Conv2d': &cap_s8_1_12_Conv2d {
             'weight': {
                         'dtype': ['int8'],
                         'scheme': ['sym'],
@@ -36,9 +36,9 @@
                         'algorithm': ['minmax', 'kl']
                         },
                     },
-          'conv1d': *cap_s8_1_12_Conv2d,
-          'conv3d': *cap_s8_1_12_Conv2d,
-          'linear': *cap_s8_1_12_Conv2d,
+          'Conv1d': *cap_s8_1_12_Conv2d,
+          'Conv3d': *cap_s8_1_12_Conv2d,
+          'Linear': *cap_s8_1_12_Conv2d,
           'default': {
             'weight': {
                         'dtype': ['int8'],
@@ -67,7 +67,7 @@
   fp32: ['*'] # '*' means all op types
   int8: &1_10_capabilities {
     'static': &cap_1_10_s8 {
-          'conv2d': &cap_s8_1_10_Conv2d {
+          'Conv2d': &cap_s8_1_10_Conv2d {
             'weight': {
                         'dtype': ['int8'],
                         'scheme': ['sym'],
@@ -81,9 +81,9 @@
                         'algorithm': ['minmax']
                         },
                     },
-          'conv1d': *cap_s8_1_10_Conv2d,
-          'conv3d': *cap_s8_1_10_Conv2d,
-          'linear': *cap_s8_1_10_Conv2d,
+          'Conv1d': *cap_s8_1_10_Conv2d,
+          'Conv3d': *cap_s8_1_10_Conv2d,
+          'Linear': *cap_s8_1_10_Conv2d,
           'default': &cap_s8_1_10_default {
             'weight': {
                         'dtype': ['int8'],
@@ -98,8 +98,6 @@
                         'algorithm': ['minmax']
                         }
                     },
-          'add': *cap_s8_1_10_default,
-          'matmul': *cap_s8_1_10_default,
           },
     'dynamic': {},
     'quant_aware': {}

diff --git a/neural_compressor/strategy/utils/tuning_sampler.py b/neural_compressor/strategy/utils/tuning_sampler.py
@@ -428,7 +428,7 @@ def __iter__(self):
             if self.accumulate and skip_first:  # skip the first one
                 skip_first = False
                 continue
-            logger.debug(f"fallback {op_name_type} to {target_dtype}")
+            logger.info(f"fallback {op_name_type} to {target_dtype}")
             yield new_tune_cfg  # need to skip the first one
 
 class LowerBitsSampler(TuningSampler):

diff --git a/neural_compressor/strategy/utils/tuning_space.py b/neural_compressor/strategy/utils/tuning_space.py
@@ -268,9 +268,14 @@ def _merge_model_wise_cfg(self, cap: Dict, model_wise_usr_cfg: Dict, fw_cap: Dic
     def _merge_op_wise_cfg(self, cap: Dict, op_wise_usr_cfg: Dict, fw_cap: Dict):
         op_name_types = {key[0]: key for key in cap['op'].keys()}
         for op_name_pattern, op_user_cfg in op_wise_usr_cfg.items():
-            op_name_pattern = re.compile(op_name_pattern)
+            if isinstance(op_name_pattern, str):
+                op_name_pattern = re.compile(op_name_pattern)
+                str_flag=True
+            else:
+                str_flag=False
             for op_name in op_name_types:
-                if op_name_pattern.fullmatch(op_name):
+                if str_flag and op_name_pattern.fullmatch(str(op_name)) \
+                  or op_name_pattern == op_name:
                     op_name_type = op_name_types[op_name]
                     cap['op'][op_name_type] = self._merge_op_cfg(cap['op'][op_name_type],
                                                                  op_user_cfg,

diff --git a/test/strategy/test_tuning_space_v2.py b/test/strategy/test_tuning_space_v2.py
@@ -166,6 +166,51 @@
                 }
         },
     ],
+    # op4 have tuple name as IPEX
+    (('op_name4', 0), 'op_type4'): [
+        {
+            'activation':
+                {
+                    'dtype': ['int8'],
+                    'quant_mode': 'static',
+                    'scheme': ['sym'],
+                    'granularity': ['per_channel', 'per_tensor'],
+                    'algorithm': ['minmax', 'kl']
+                },
+            'weight':
+                {
+                    'dtype': ['int8'],
+                    'scheme': ['sym'],
+                    'granularity': ['per_channel', 'per_tensor']
+                }
+        },
+        {
+            'activation':
+                {
+                    'dtype': ['int8'],
+                    'quant_mode': 'dynamic',
+                    'scheme': ['sym'],
+                    'granularity': ['per_channel', 'per_tensor'],
+                    'algorithm': ['minmax', 'kl']
+                },
+            'weight':
+                {
+                    'dtype': ['int8'],
+                    'scheme': ['sym'],
+                    'granularity': ['per_channel', 'per_tensor']
+                }
+        },
+        {
+            'activation':
+                {
+                    'dtype': 'fp32'
+                },
+            'weight':
+                {
+                    'dtype': 'fp32'
+                }
+        },
+    ],
 
     # op5, weight only
     ('op_name5', 'op_type5'): [
@@ -227,6 +272,14 @@ def setUp(self) -> None:
                     'dtype': ['fp32']
                 }
             },
+            ('op_name4', 0): {
+                'activation': {
+                    'dtype': ['fp32']
+                },
+                'weight': {
+                    'dtype': ['fp32']
+                }
+            },
         }
 
 
@@ -311,19 +364,22 @@ def initial_op_quant_mode(items_lst, target_quant_mode, op_item_dtype_dict):
     def test_tuning_space_merge_op_wise(self):
         # op-wise
         conf = {
-                    'op_name_dict': self.op_wise_user_cfg_for_fallback,
-
+            'op_name_dict': self.op_wise_user_cfg_for_fallback,
         }
         conf = DotDict(conf)
         # test fallback
         tuning_space2 = TuningSpace(deepcopy(self.capability), deepcopy(conf))
         logger.debug(tuning_space2.root_item.get_details())
         op_name1_only_fp32 = True
+        op_name4_only_fp32 = True
         for quant_mode in ['static', 'dynamic']:
             for item in tuning_space2.query_items_by_quant_mode(quant_mode):
                 if item.name[0] == 'op_name1':
                     op_name1_only_fp32 = False
+                if item.name[0] == ('op_name4', 0):
+                    op_name4_only_fp32 = False
         self.assertTrue(op_name1_only_fp32)
+        self.assertTrue(op_name4_only_fp32)