TypeError: Exception encountered when calling layer 'embeddings' (type TFBertEmbeddings)

Question

My model was wholly workable two weeks back, but now it's showing the following error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-23-a3e5a45f06c9> in <cell line: 14>()
     12 
     13 # Encode input using BERT model
---> 14 bert_output = bert_model(input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids)
     15 
     16 # Get pooled output and pass through dropout layer

8 frames
/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py in error_handler(*args, **kwargs)
     68             # To get the full stack trace, call:
     69             # `tf.debugging.disable_traceback_filtering()`
---> 70             raise e.with_traceback(filtered_tb) from None
     71         finally:
     72             del filtered_tb

TypeError: Exception encountered when calling layer 'embeddings' (type TFBertEmbeddings).

Could not build a TypeSpec for name: "tf.debugging.assert_less/assert_less/Assert/Assert"
op: "Assert"
input: "tf.debugging.assert_less/assert_less/All"
input: "tf.debugging.assert_less/assert_less/Assert/Assert/data_0"
input: "tf.debugging.assert_less/assert_less/Assert/Assert/data_1"
input: "tf.debugging.assert_less/assert_less/Assert/Assert/data_2"
input: "Placeholder"
input: "tf.debugging.assert_less/assert_less/Assert/Assert/data_4"
input: "tf.debugging.assert_less/assert_less/y"
attr {
  key: "T"
  value {
    list {
      type: DT_STRING
      type: DT_STRING
      type: DT_STRING
      type: DT_INT32
      type: DT_STRING
      type: DT_INT32
    }
  }
}
attr {
  key: "summarize"
  value {
    i: 3
  }
}
 of unsupported type <class 'tensorflow.python.framework.ops.Operation'>.

Call arguments received by layer 'embeddings' (type TFBertEmbeddings):
  • input_ids=<KerasTensor: shape=(None, 50) dtype=int32 (created by layer 'input_ids')>
  • position_ids=None
  • token_type_ids=<KerasTensor: shape=(None, 50) dtype=int32 (created by layer 'token_type_ids')>
  • inputs_embeds=None
  • past_key_values_length=0
  • training=False

I think this error occurs when the input layers are sent to the corresponding BERT layer. If I use old versions of TensorFlow instead of 2.15.0, the error is resolved. However, with those old versions, I did not get GPU and faced a Graph Execution Error.

Can anyone help me with this

Answer 1

it's a problem with the transformers library, I had the same problem and solved it using version 4.31.0