# \[On model.fit()\]: TypeError: Exception encountered when calling layer

**URL:** <https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653>\
**Category:** 🤗Transformers\
**Created:** [January 2, 2024, 3:03am UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653 "2024-01-02T03:03:51Z")\
**Posts on this page:** 6\
**Page:** 1

<div class="post-metadata">

**Author:** ![raygx](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/raygx/32/17328_2.png) [@raygx](https://discuss.huggingface.co/u/raygx)\
**Post date:** [January 2, 2024, 3:03am UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/1 "2024-01-02T03:03:51Z")

</div>

I am not quite sure why I can’t run GPT2 for sequence classification.  
The same code works perfectly when I use GPT2 that I have pretrained myself.  
The code is running perfectly for BERT (bert-base-uncased).  
But somehow it doesn’t run when i used ‘gpt2’ base model.

[Kaggle Notebook](https://www.kaggle.com/code/reganmaharjan/imdb-classification-using-transformers). In this notebook I have done both BERT and GPT2. but GPT2 is not working.

Error:

> "---------------------------------------------------------------------------  
> TypeError Traceback (most recent call last)  
> File :4  
> File /opt/conda/lib/python3.10/site-packages/keras/utils/traceback\_utils.py:70, in filter\_traceback..error\_handler(\*args, \*\*kwargs)  
> 67 filtered\_tb = _process\_traceback\_frames(e. **traceback** )  
> 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  
> File /tmp/autograph\_generated\_fileaokm8mv0.py:15, in outer\_factory..inner\_factory..tf\_\_train\_function(iterator)  
> 13 try:  
> 14 do\_return = True  
> —\> 15 retval = ag_.converted\_call(ag\_\_.ld(step\_function), (ag\_\_.ld(self), ag\_\_.ld(iterator)), None, fscope)  
> 16 except:  
> 17 do\_return = False  
> File /opt/conda/lib/python3.10/site-packages/transformers/modeling\_tf\_utils.py:1638, in TFPreTrainedModel.train\_step(self, data)  
> 1636 y\_pred = self(x, training=True, return\_loss=True)  
> 1637 else:  
> → 1638 y\_pred = self(x, training=True)  
> 1639 if self._using\_dummy\_loss:  
> 1640 loss = self.compiled\_loss(y\_pred.loss, y\_pred.loss, sample\_weight, regularization\_losses=self.losses)  
> File /tmp/autograph\_generated\_fileapf58knl.py:37, in outer\_factory..inner\_factory..tf\_\_run\_call\_with\_unpacked\_inputs(self, \*args, \*\*kwargs)  
> 35 try:  
> 36 do\_return = True  
> —\> 37 retval = ag_.converted\_call(ag\_\_.ld(func), (ag\_\_.ld(self),), dict(\*\*ag\_\_.ld(unpacked\_inputs)), fscope)  
> 38 except:  
> 39 do\_return = False  
> File /tmp/**autograph\_generated\_file889imx4d.py:56, in outer\_factory..inner\_factory..tf\_\_call(self, input\_ids, past\_key\_values, attention\_mask, token\_type\_ids, position\_ids, head\_mask, inputs\_embeds, use\_cache, output\_attentions, output\_hidden\_states, return\_dict, labels, training)  
> 54 ag**.if\_stmt(ag\_\_.ld(input\_ids) is not None, if\_body, else\_body, get\_state, set\_state, (‘in\_logits’, ‘sequence\_lengths’), 2)  
> 55 sequence\_lengths = ag\_\_.Undefined(‘sequence\_lengths’)  
> —\> 56 ag\_\_.if\_stmt(ag\_\_.ld(self).config.pad\_token\_id is None, if\_body\_1, else\_body\_1, get\_state\_1, set\_state\_1, (‘in\_logits’, ‘sequence\_lengths’), 2)  
> 57 loss = None  
> 59 def get\_state\_3():  
> File /tmp/**autograph\_generated\_file889imx4d.py:54, in outer\_factory..inner\_factory..tf\_\_call..else\_body\_1()  
> 52 ag**.converted\_call(ag\_\_.ld(logger).warning, (f’{ag\_\_.ld(self).**class **.** name**} will not detect padding tokens in `inputs_embeds`. Results may be unexpected if using padding tokens in conjunction with `inputs_embeds.`',), None, fscope)  
> 53 sequence\_lengths = ag\_\_.Undefined(‘sequence\_lengths’)  
> —\> 54 ag\_\_.if\_stmt(ag\_\_.ld(input\_ids) is not None, if\_body, else\_body, get\_state, set\_state, (‘in\_logits’, ‘sequence\_lengths’), 2)  
> File /tmp/**autograph\_generated\_file889imx4d.py:46, in outer\_factory..inner\_factory..tf\_\_call..else\_body\_1..if\_body()  
> 44 nonlocal in\_logits, sequence\_lengths  
> 45 sequence\_lengths = ag**.converted\_call(ag\_\_.ld(tf).argmax, (ag\_\_.converted\_call(ag\_\_.ld(tf).cast, (ag\_\_.converted\_call(ag\_\_.ld(tf).math.equal, (ag\_\_.ld(input\_ids), ag\_\_.ld(self).config.pad\_token\_id), None, fscope), ag\_\_.ld(input\_ids).dtype), None, fscope),), dict(axis=-1), fscope) - 1  
> —\> 46 sequence\_lengths = ag\_\_.converted\_call(ag\_\_.ld(tf).where, (ag\_\_.ld(sequence\_lengths) \>= 0, ag\_\_.ld(sequence\_lengths), ag\_\_.ld(input\_ids).shape[-1] - 1), None, fscope)  
> 47 in\_logits = ag\_\_.converted\_call(ag\_\_.ld(tf).gather, (ag\_\_.ld(logits), ag\_\_.ld(sequence\_lengths)), dict(batch\_dims=1, axis=1), fscope)

```
TypeError: in user code:
File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1284, in train_function *
    return step_function(self, iterator)
File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1268, in step_function **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in run_step **
    outputs = model.train_step(data)
File "/opt/conda/lib/python3.10/site-packages/transformers/modeling_tf_utils.py", line 1638, in train_step
    y_pred = self(x, training=True)
File "/opt/conda/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
File "/tmp/ __autograph_generated_fileapf58knl.py", line 37, in tf__ run_call_with_unpacked_inputs
    retval_ = ag__.converted_call(ag__.ld(func), (ag__.ld(self),), dict(**ag__.ld(unpacked_inputs)), fscope)
File "/tmp/ __autograph_generated_file889imx4d.py", line 56, in tf__ call
    ag__.if_stmt(ag__.ld(self).config.pad_token_id is None, if_body_1, else_body_1, get_state_1, set_state_1, ('in_logits', 'sequence_lengths'), 2)
File "/tmp/__autograph_generated_file889imx4d.py", line 54, in else_body_1
    ag__.if_stmt(ag__.ld(input_ids) is not None, if_body, else_body, get_state, set_state, ('in_logits', 'sequence_lengths'), 2)
File "/tmp/__autograph_generated_file889imx4d.py", line 46, in if_body
    sequence_lengths = ag__.converted_call(ag__.ld(tf).where, (ag__.ld(sequence_lengths) >= 0, ag__.ld(sequence_lengths), ag__.ld(input_ids).shape[-1] - 1), None, fscope)

TypeError: Exception encountered when calling layer 'tfgpt2_for_sequence_classification_2' (type TFGPT2ForSequenceClassification).    
in user code:

    File "/opt/conda/lib/python3.10/site-packages/transformers/modeling_tf_utils.py", line 1050, in run_call_with_unpacked_inputs *
        return func(self, **unpacked_inputs)
    File "/opt/conda/lib/python3.10/site-packages/transformers/models/gpt2/modeling_tf_gpt2.py", line 1088, in call *
        sequence_lengths = tf.where(sequence_lengths >= 0, sequence_lengths, input_ids.shape[-1] - 1)

    TypeError: unsupported operand type(s) for -: 'NoneType' and 'int'

Call arguments received by layer 'tfgpt2_for_sequence_classification_2' (type TFGPT2ForSequenceClassification):
  • input_ids={'input_ids': 'tf.Tensor(shape=(16, None), dtype=int64)', 'attention_mask': 'tf.Tensor(shape=(16, None), dtype=int64)', 'labels': 'tf.Tensor(shape=(16,), dtype=int64)'}
  • past_key_values=None
  • attention_mask=None
  • token_type_ids=None
  • position_ids=None
  • head_mask=None
  • inputs_embeds=None
  • use_cache=None
  • output_attentions=None
  • output_hidden_states=None
  • return_dict=None
  • labels=None
  • training=True

```

I believe this to be a simple fix. Sorry for the trouble. But help please.

@sgugger  
@amyeroberts

---

<div class="post-metadata">

**Author:** ![nidiabucarelli01](https://avatars.discourse-cdn.com/v4/letter/n/50afbb/32.png) [@nidiabucarelli01](https://discuss.huggingface.co/u/nidiabucarelli01)\
**Post date:** [February 26, 2024, 11:25pm UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/2 "2024-02-26T23:25:10Z")

</div>

Hi @raygx,  
were you able to fix the problem? I have the same issue.

TypeError: in user code:

```
File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1160, in train_function *
    return step_function(self, iterator)
File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1146, in step_function **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1135, in run_step **
    outputs = model.train_step(data)
File "/home/nbucar1/.local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 1637, in train_step
    y_pred = self(x, training=True)
File "/usr/local/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
File "/tmp/ __autograph_generated_filemwik0t34.py", line 37, in tf__ run_call_with_unpacked_inputs
    retval_ = ag__.converted_call(ag__.ld(func), (ag__.ld(self),), dict(**ag__.ld(unpacked_inputs)), fscope)
File "/tmp/ __autograph_generated_filebbszqrkw.py", line 56, in tf__ call
    ag__.if_stmt(ag__.ld(self).config.pad_token_id is None, if_body_1, else_body_1, get_state_1, set_state_1, ('in_logits', 'sequence_lengths'), 2)
File "/tmp/__autograph_generated_filebbszqrkw.py", line 54, in else_body_1
    ag__.if_stmt(ag__.ld(input_ids) is not None, if_body, else_body, get_state, set_state, ('in_logits', 'sequence_lengths'), 2)
File "/tmp/__autograph_generated_filebbszqrkw.py", line 46, in if_body
    sequence_lengths = ag__.converted_call(ag__.ld(tf).where, (ag__.ld(sequence_lengths) >= 0, ag__.ld(sequence_lengths), ag__.ld(input_ids).shape[-1] - 1), None, fscope)

TypeError: Exception encountered when calling layer "tfgpt2_for_sequence_classification" " f"(type TFGPT2ForSequenceClassification).

in user code:

    File "/home/nbucar1/.local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 1163, in run_call_with_unpacked_inputs *
        return func(self, **unpacked_inputs)
    File "/home/nbucar1/.local/lib/python3.9/site-packages/transformers/models/gpt2/modeling_tf_gpt2.py", line 1201, in call *
        sequence_lengths = tf.where(sequence_lengths >= 0, sequence_lengths, input_ids.shape[-1] - 1)

    TypeError: unsupported operand type(s) for -: 'NoneType' and 'int'

Call arguments received by layer "tfgpt2_for_sequence_classification" " f"(type TFGPT2ForSequenceClassification):
  • self={'input_ids': 'tf.Tensor(shape=(None, None), dtype=int64)', 'attention_mask': 'tf.Tensor(shape=(None, None), dtype=int64)', 'labels': 'tf.Tensor(shape=(None,), dtype=int64)'}
  • input_ids=None
  • past_key_values=None
  • attention_mask=None
  • token_type_ids=None
  • position_ids=None
  • head_mask=None
  • inputs_embeds=None
  • use_cache=None
  • output_attentions=None
  • output_hidden_states=None
  • return_dict=None
  • labels=None
  • training=True

```

---

<div class="post-metadata">

**Author:** ![raygx](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/raygx/32/17328_2.png) [@raygx](https://discuss.huggingface.co/u/raygx)\
**Post date:** [February 27, 2024, 12:49am UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/3 "2024-02-27T00:49:59Z")

</div>

@nidiabucarelli01  
Not really. I think this is due to some version mismatch on some of the dependencies of transformers library on the kaggle environment. Use Google Colab. There is no issue on Colab.

---

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**Author:** ![nidiabucarelli01](https://avatars.discourse-cdn.com/v4/letter/n/50afbb/32.png) [@nidiabucarelli01](https://discuss.huggingface.co/u/nidiabucarelli01)\
**Post date:** [February 27, 2024, 3:27pm UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/4 "2024-02-27T15:27:18Z")

</div>

Thanks. I changed transformer version and now I am getting the error:

```auto
    File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1160, in train_function *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1146, in step_function **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.9/site-packages/keras/engine/training.py", line 1135, in run_step **
        outputs = model.train_step(data)
    File "/home/nbucar1/.local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 1562, in train_step
        x, y, sample_weight = keras.utils.unpack_x_y_sample_weight(data)

    AttributeError: module 'keras.utils' has no attribute 'unpack_x_y_sample_weight'  

```

My system has:

- Keras ‘2.10.0’
- tensorflow ‘2.10.1’
- transformers ‘4.39.dev0’

It seems Keras version does not have ‘‘unpack\_x\_y\_sample\_weight’’. What package versions do show up in Colab? Thanks!

---

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**Author:** ![raygx](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/raygx/32/17328_2.png) [@raygx](https://discuss.huggingface.co/u/raygx)\
**Post date:** [February 27, 2024, 8:35pm UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/5 "2024-02-27T20:35:20Z")

</div>

@nidiabucarelli01 I am not working on GPT2 now so I haven’t actually researched much. But what I suggest is, first check the doc of GPT2 and make sure you pass all the required fields (i.e. in **tokenizer create all the necessary parameters special\_token\_mask** and other values). This is because when the required fields are not there the input dictionary doesn’t get spread out to the respective parameters (I am not actually sure, but I think I had came across this scenario once before).

Secondly, if you are working locally, I suggest you create a **virtual environment** with python version less than 3.9 (3.6 probably, can’t say specifically) then install transformers library. It should install tensorflow that it works with.

> There is also another solution where you have to upgrade einops, accelerate  
> pip install -q --upgrade accelerate einops xformers  
> This solution used to work before on Kaggle.

These are the two things I can think of. Other than that I mostly work on Kaggle and Colab, most of the time code works on Colab, but T4 GPU is slow and P100 on Kaggle is faster.

---

<div class="post-metadata">

**Author:** ![raygx](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/raygx/32/17328_2.png) [@raygx](https://discuss.huggingface.co/u/raygx)\
**Post date:** [March 1, 2024, 1:08am UTC](https://discuss.huggingface.co/t/on-model-fit-typeerror-exception-encountered-when-calling-layer/67653/6 "2024-03-01T01:08:06Z")

</div>

@nidiabucarelli01 I found the solution, I am not sure where the actual issue lies. But if you install transformer version 4.31.0, it should run. It worked for me.