---------------------------------------------------------------------------OSError                                   Traceback (most recent call last) in 
----> 1 preds = predict(model, test_loader, test_ds, label_vocab)
      2 file_path = "ernie_results.txt"
      3 with open(file_path, "w", encoding="utf8") as fout:
      4     fout.write("\n".join(preds))
      5 # Print some examples
 in predict(model, data_loader, ds, label_vocab)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/base.py in _decorate_function(func, *args, **kwargs)
    329         def _decorate_function(func, *args, **kwargs):
    330             with self:
--> 331                 return func(*args, **kwargs)
    332 
    333         @decorator.decorator
~/utils.py in predict(model, data_loader, ds, label_vocab)
     29     all_lens = []
     30     for input_ids, seg_ids, lens, labels in data_loader:
---> 31         logits = model(input_ids, seg_ids)
     32         preds = paddle.argmax(logits, axis=-1)
     33         # Drop CLS prediction
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
    900                 self._built = True
    901 
--> 902             outputs = self.forward(*inputs, **kwargs)
    903 
    904             for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddlenlp/transformers/ernie/modeling.py in forward(self, input_ids, token_type_ids, position_ids, attention_mask)
    624             token_type_ids=token_type_ids,
    625             position_ids=position_ids,
--> 626             attention_mask=attention_mask)
    627 
    628         sequence_output = self.dropout(sequence_output)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
    900                 self._built = True
    901 
--> 902             outputs = self.forward(*inputs, **kwargs)
    903 
    904             for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddlenlp/transformers/ernie/modeling.py in forward(self, input_ids, token_type_ids, position_ids, attention_mask)
    353             position_ids=position_ids,
    354             token_type_ids=token_type_ids)
--> 355         encoder_outputs = self.encoder(embedding_output, attention_mask)
    356         sequence_output = encoder_outputs
    357         pooled_output = self.pooler(sequence_output)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
    900                 self._built = True
    901 
--> 902             outputs = self.forward(*inputs, **kwargs)
    903 
    904             for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/transformer.py in forward(self, src, src_mask, cache)
    681         for i, mod in enumerate(self.layers):
    682             if cache is None:
--> 683                 output = mod(output, src_mask=src_mask)
    684             else:
    685                 output, new_cache = mod(output,
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
    900                 self._built = True
    901 
--> 902             outputs = self.forward(*inputs, **kwargs)
    903 
    904             for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/transformer.py in forward(self, src, src_mask, cache)
    565         # Add cache for encoder for the usage like UniLM
    566         if cache is None:
--> 567             src = self.self_attn(src, src, src, src_mask)
    568         else:
    569             src, incremental_cache = self.self_attn(src, src, src, src_mask,
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
    900                 self._built = True
    901 
--> 902             outputs = self.forward(*inputs, **kwargs)
    903 
    904             for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/transformer.py in forward(self, query, key, value, attn_mask, cache)
    404             attn_mask = _convert_attention_mask(attn_mask, product.dtype)
    405             product = product + attn_mask
--> 406         weights = F.softmax(product)
    407         if self.dropout:
    408             weights = F.dropout(
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/functional/activation.py in softmax(x, axis, dtype, name)
    874         outs_cast = x if dtype is None \
    875             else core.ops.cast(x, 'in_dtype', x.dtype, 'out_dtype', dtype)
--> 876         return core.ops.softmax(outs_cast, 'axis', axis, 'use_cudnn', use_cudnn)
    877 
    878     if dtype is None:
OSError: (External)  Cudnn error, CUDNN_STATUS_NOT_SUPPORTED  (at /paddle/paddle/fluid/platform/cudnn_helper.h:231)
  [operator < softmax > error]