DistilBert for Tensorflow doesn't work
Model:  TFDistilBertForSequenceClassification
Language: English 
Task: multi-label classification
Environment: google colab

When trying to use TF Distil Bert I get the below error after I have loaded the model and try to run model.fit() : 

> TypeError: in converted code:
>     relative to /usr/local/lib/python3.6/dist-packages:
> 
>     transformers/modeling_tf_distilbert.py:680 call  *
>         distilbert_output = self.distilbert(inputs, **kwargs)
>     tensorflow_core/python/keras/engine/base_layer.py:842 __call__
>         outputs = call_fn(cast_inputs, *args, **kwargs)
>     transformers/modeling_tf_distilbert.py:447 call  *
>         tfmr_output = self.transformer([embedding_output, attention_mask, head_mask], training=training)
>     tensorflow_core/python/keras/engine/base_layer.py:891 __call__
>         outputs = self.call(cast_inputs, *args, **kwargs)
>     transformers/modeling_tf_distilbert.py:382 call
>         layer_outputs = layer_module([hidden_state, attn_mask, head_mask[i]], training=training)
>     tensorflow_core/python/keras/engine/base_layer.py:891 __call__
>         outputs = self.call(cast_inputs, *args, **kwargs)
>     transformers/modeling_tf_distilbert.py:324 call
>         sa_output = self.attention([x, x, x, attn_mask, head_mask], training=training)
>     tensorflow_core/python/keras/engine/base_layer.py:891 __call__
>         outputs = self.call(cast_inputs, *args, **kwargs)
>     transformers/modeling_tf_distilbert.py:229 call
>         assert 2 <= len(tf.shape(mask)) <= 3
>     tensorflow_core/python/framework/ops.py:741 __len__
>         "shape information.".format(self.name))
> 
>     TypeError: len is not well defined for symbolic Tensors. (tf_distil_bert_for_sequence_classification_1/distilbert/transformer/layer_._0/attention/Shape_2:0) Please call `x.shape` rather than `len(x)` for shape information.


The exact same procedure works if I use TF Bert but not Distil Bert.  Does anyone know how to get around this problem?
I have been experiencing the same issue #1378.<|||||>Fixed on master with 23b7138, thanks.
Will be in this week's new release 2.1<|||||>thanks a lot