Rearrange attention output to have batch dimension on the 0th axis

[dakshvar22]

Proposed changes:

• ...

Status (please check what you already did):

• added some tests for the functionality
• updated the documentation
• updated the changelog (please check changelog for instructions)
• reformat files using black (please check Readme for instructions)

[JEM-Mosig]

Looks good! Just one small thing in the changelog. ... And you'll have to fix that test for output shapes.

[JEM-Mosig]

The key would be attention_weights, not attention_output.

[github-actions]

Hey @dakshvar22! 👋 To run model regression tests, comment with the /modeltest command and a configuration.

Tips 💡: The model regression test will be run on push events. You can re-run the tests by re-add status:model-regression-tests label or use a Re-run jobs button in Github Actions workflow.

Tips 💡: Every time when you want to change a configuration you should edit the comment with the previous configuration.

You can copy this in your comment and customize:

/modeltest

```yml
##########
## Available datasets
##########
# - "Carbon Bot"
# - "Hermit"
# - "Private 1"
# - "Private 2"
# - "Private 3"
# - "Sara"

##########
## Available configurations
##########
# - "BERT + DIET(bow) + ResponseSelector(bow)"
# - "BERT + DIET(seq) + ResponseSelector(t2t)"
# - "Spacy + DIET(bow) + ResponseSelector(bow)"
# - "Spacy + DIET(seq) + ResponseSelector(t2t)"
# - "Sparse + BERT + DIET(bow) + ResponseSelector(bow)"
# - "Sparse + BERT + DIET(seq) + ResponseSelector(t2t)"
# - "Sparse + DIET(bow) + ResponseSelector(bow)"
# - "Sparse + DIET(seq) + ResponseSelector(t2t)"
# - "Sparse + Spacy + DIET(bow) + ResponseSelector(bow)"
# - "Sparse + Spacy + DIET(seq) + ResponseSelector(t2t)"

## Example configuration
#################### syntax #################
## include:
##   - dataset: ["<dataset_name>"]
##     config: ["<configuration_name>"]
#
## Example:
## include:
##  - dataset: ["Carbon Bot"]
##    config: ["Sparse + DIET(bow) + ResponseSelector(bow)"]
#
## Shortcut:
## You can use the "all" shortcut to include all available configurations or datasets
#
## Example: Use the "Sparse + EmbeddingIntent + ResponseSelector(bow)" configuration
## for all available datasets
## include:
##  - dataset: ["all"]
##    config: ["Sparse + DIET(bow) + ResponseSelector(bow)"]
#
## Example: Use all available configurations for the "Carbon Bot" and "Sara" datasets
## and for the "Hermit" dataset use the "Sparse + DIET + ResponseSelector(T2T)" and
## "BERT + DIET + ResponseSelector(T2T)" configurations:
## include:
##  - dataset: ["Carbon Bot", "Sara"]
##    config: ["all"]
##  - dataset: ["Hermit"]
##    config: ["Sparse + DIET(seq) + ResponseSelector(t2t)", "BERT + DIET(seq) + ResponseSelector(t2t)"]
#
## Example: Define a branch name to check-out for a dataset repository. Default branch is 'main'
## dataset_branch: "test-branch"
## include:
##  - dataset: ["Carbon Bot", "Sara"]
##    config: ["all"]


include:
 - dataset: ["Carbon Bot"]
   config: ["Sparse + DIET(bow) + ResponseSelector(bow)"]

```

[github-actions]

/modeltest

include:
 - dataset: ["Carbon Bot"]
   config: ["Sparse + DIET(bow) + ResponseSelector(bow)", "Sparse + DIET(seq) + ResponseSelector(t2t)"]

[github-actions]

The model regression tests have started. It might take a while, please be patient.
As soon as results are ready you'll see a new comment with the results.

Used configuration can be found in the comment.

[github-actions]

Commit: 3c1c5d6, The full report is available as an artifact.

Dataset: Carbon Bot, Dataset repository branch: main, commit: c3e1ed09c204a1be311c61320c8defcf0ee1a7dd

Configuration	Intent Classification Micro F1	Entity Recognition Micro F1	Response Selection Micro F1
Sparse + DIET(bow) + ResponseSelector(bow) test: 36s, train: 2m33s, total: 3m9s	0.7748 (0.04)	0.7529 (0.00)	0.4702 (-0.01)
Sparse + DIET(seq) + ResponseSelector(t2t) test: 55s, train: 3m46s, total: 4m41s	0.7359 (-0.01)	0.6724 (-0.01)	0.5033 (-0.04)