use scale=1.0 in floats_tensor called in speech model testers
# What does this PR do?

Fix the failure of `Speech2TextModelTest.test_pt_tf_model_equivalence`. This is caused by 

https://github.com/huggingface/transformers/blob/e6f00a11d7fa34215184e3c797e19e6c7debe0fe/tests/speech_to_text/test_modeling_speech_to_text.py#L134-L136

where the `input_features` get a large magnitude of `1e2` (from `self.vocab_size=99`).

(probably this happens because we just copied the `input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)` from NLP models?)

I changed it to `scale=1.0`, but need @patrickvonplaten's expertise **to make sure there was no particular reason to use `self.vocab_size`.**

### Details
Current speech model testers have

```
def prepare_config_and_inputs(self):
    input_values = floats_tensor([self.batch_size, self.seq_length], self.vocab_size)
```

The ` self.vocab_size` argument is the `scale`, so the generated dummy `input_values` has the magnitude of  `self.vocab_size`.
For `Speech2TextModelTester`, we have `vocab_size=99`.

Furthermore, `Speech2TextEncoder` has

https://github.com/huggingface/transformers/blob/e6f00a11d7fa34215184e3c797e19e6c7debe0fe/src/transformers/models/speech_to_text/modeling_speech_to_text.py#L705

and from the tester's `hidden_size=16,` we get `embed_scale=4`.

The `input_features` goes through the conv layer(s) and being scaled:
https://github.com/huggingface/transformers/blob/e6f00a11d7fa34215184e3c797e19e6c7debe0fe/src/transformers/models/speech_to_text/modeling_speech_to_text.py#L767-L768

On `CPU` however, the conv layers of PT/TF gives diff. with a magnitude of `1e-7` for input values with 1s. So with the above 2 scalings, this error becomes `4e-5`, and the PT/TF equiv. test fails.
_The documentation is not available anymore as the PR was closed or merged._<|||||>Thanks for fixing all the tests!