Update model list for onnx

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

auto_transformers.py

@@ -107,20 +107,21 @@ class AutoTransformers(NNOperator):
                                   path,
                                   input_names=["input_ids", "token_type_ids", "attention_mask"],  # list(inputs.keys())
                                   output_names=["last_hidden_state"],
-                                  opset_version=12,
+                                  opset_version=13,
                                   dynamic_axes={
                                       "input_ids": {0: "batch_size", 1: "input_length"},
                                       "token_type_ids": {0: "batch_size", 1: "input_length"},
                                       "attention_mask": {0: "batch_size", 1: "input_length"},
                                       "last_hidden_state": {0: "batch_size"},
                                   })
-            except Exception:
+            except Exception as e:
+                print(e, '\nTrying with 2 outputs...')
                 torch.onnx.export(self.model,
                                   tuple(inputs.values()),
                                   path,
                                   input_names=["input_ids", "token_type_ids", "attention_mask"],  # list(inputs.keys())
                                   output_names=["last_hidden_state", "pooler_output"],
-                                  opset_version=12,
+                                  opset_version=13,
                                   dynamic_axes={
                                       "input_ids": {0: "batch_size", 1: "input_length"},
                                       "token_type_ids": {0: "batch_size", 1: "input_length"},
@@ -321,16 +322,11 @@ class AutoTransformers(NNOperator):
             model_list = list(set(full_list) - set(to_remove))
         elif format == 'onnx':
             to_remove = [
-                'albert-xlarge-v1',
-                'albert-xlarge-v2',
-                'albert-xxlarge-v1',
-                'albert-xxlarge-v2',
                 'allenai/led-base-16384',
                 'ctrl',
                 'distilgpt2',
                 'EleutherAI/gpt-j-6B',
                 'EleutherAI/gpt-neo-1.3B',
-                'funnel-transformer/intermediate',
                 'funnel-transformer/large',
                 'funnel-transformer/medium',
                 'funnel-transformer/small',
@@ -338,8 +334,6 @@ class AutoTransformers(NNOperator):
                 'google/bigbird-pegasus-large-arxiv',
                 'google/bigbird-pegasus-large-bigpatent',
                 'google/bigbird-pegasus-large-pubmed',
-                'google/canine-c',
-                'google/canine-s',
                 'google/fnet-base',
                 'google/fnet-large',
                 'google/reformer-crime-and-punishment',

test_onnx.py

@@ -1,11 +1,16 @@
 from auto_transformers import AutoTransformers
 import onnx
+import warnings
+
+warnings.filterwarnings('ignore')
 
 f = open('onnx.csv', 'a+')
 f.write('model_name, run_op, save_onnx, check_onnx\n')
 
-# models = AutoTransformers.supported_model_names()[:1]
-models = ['bert-base-cased', 'distilbert-base-cased']
+# full_models = AutoTransformers.supported_model_names()
+# checked_models = AutoTransformers.supported_model_names(format='onnx')
+# models = [x for x in full_models if x not in checked_models]
+models = ['funnel-transformer/large', 'funnel-transformer/medium', 'funnel-transformer/small', 'funnel-transformer/xlarge']
 
 for name in models:
     f.write(f'{name},')
@@ -16,22 +21,23 @@ for name in models:
     except Exception as e:
         f.write('fail')
         print(f'Fail to load op for {name}: {e}')
-        continue
+        pass
     try:
         op.save_model(format='onnx')
         f.write('success,')
     except Exception as e:
         f.write('fail')
         print(f'Fail to save onnx for {name}: {e}')
-        continue
+        pass
     try:
         saved_name = name.replace('/', '-')
-        onnx_model = onnx.load(f'saved/onnx/{saved_name}.onnx')
+        onnx_model = onnx.load(f'saved/onnx/{saved_name}.onnx', load_external_data=False)
         onnx.checker.check_model(onnx_model)
         f.write('success')
     except Exception as e:
         f.write('fail')
         print(f'Fail to check onnx for {name}: {e}')
-        continue
+        pass
+    
     f.write('\n')
 print('Finished.')