set proper input names while converting

convert.py

@@ -1,11 +1,18 @@
 from transformers import AutoTokenizer, AutoModel
 import torch
 
+max_seq_length=128
+
 model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L12-v2")
 model.eval()
 
-sample = torch.randint(low=0, high=1, size=(1,128))
-input = (sample, sample, sample)
+inputs = {"input_ids": torch.ones(1, max_seq_length, dtype=torch.int64),
+        "attention_mask": torch.ones(1, max_seq_length, dtype=torch.int64),
+        "token_type_ids": torch.ones(1, max_seq_length, dtype=torch.int64)}
+
+symbolic_names = {0: 'batch_size', 1: 'max_seq_len'}
 
-torch.onnx.export(model, input, 'pytorch_model.onnx', export_params=True)
+torch.onnx.export(model, args=tuple(inputs.values()), f='pytorch_model.onnx', export_params=True, 
+    input_names=['input_ids', 'attention_mask', 'token_type_ids'], output_names=['output'],
+    dynamic_axes={'input_ids': symbolic_names, 'attention_mask': symbolic_names, 'token_type_ids': symbolic_names})
 

pytorch_model.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a504d31e57702a74fecf5c2d7df67fa9fcb5635baa2cd335ac74bc2cbdefcbdd
-size 133597269
+oid sha256:6bdde0dabded044bf81d8945dc92bd4c15328a056c893cb57ef7bbc5cae80dac
+size 133694646