

TITLE
Cannot import transformers with TF version 2.1.0

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The installation README says that transformers library requires Tensorflow version >2.0, but I can't seem to import the latest transformers 3.2 release even with Tensorflow v2.1. 

```
>>> import transformers
wandb: WARNING W&B installed but not logged in.  Run `wandb login` or set the WANDB_API_KEY env variable.
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/amog/dev/ray/lib/python3.7/site-packages/transformers/__init__.py", line 121, in <module>
    from .pipelines import (
  File "/Users/amog/dev/ray/lib/python3.7/site-packages/transformers/pipelines.py", line 47, in <module>
    from .modeling_tf_auto import (
  File "/Users/amog/dev/ray/lib/python3.7/site-packages/transformers/modeling_tf_auto.py", line 45, in <module>
    from .modeling_tf_albert import (
  File "/Users/amog/dev/ray/lib/python3.7/site-packages/transformers/modeling_tf_albert.py", line 24, in <module>
    from .activations_tf import get_tf_activation
  File "/Users/amog/dev/ray/lib/python3.7/site-packages/transformers/activations_tf.py", line 53, in <module>
    "swish": tf.keras.activations.swish,
AttributeError: module 'tensorflow_core.python.keras.api._v2.keras.activations' has no attribute 'swish'
```

Upgrading to TF 2.2 works fine, but I think this should be made more clear in the docs.

cc @jplu @sgugger 
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.2.0
- Platform: Mac OS
- Python version: 3.7.7
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 2.1.0. On CPU only.
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

### Who can help
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 albert, bert, GPT2, XLM: @LysandreJik 
 tokenizers: @mfuntowicz
 Trainer: @sgugger
 Speed and Memory Benchmarks: @patrickvonplaten
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 Translation: @sshleifer
 Summarization: @sshleifer
 TextGeneration: @TevenLeScao 
 examples/distillation: @VictorSanh
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
 Text Generation: @TevenLeScao
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 Bart: @sshleifer
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 T5: @patrickvonplaten
 Longformer/Reformer: @patrickvonplaten
 TransfoXL/XLNet: @TevenLeScao 
 examples/seq2seq: @sshleifer
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 tensorflow: @jplu
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## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1.
2.
3.

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## Expected behavior

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