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add e2e docs (#7512)
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* change TED default params

* Update docs/docs/training-data-format.mdx

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36 changes: 36 additions & 0 deletions changelog/7496.feature.md
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Make [TED Policy](./policies.mdx#ted-policy) an end-to-end policy. Namely, make it possible to train TED on stories that contain
intent and entities or user text and bot actions or bot text.
If you don't have text in your stories, TED will behave the same way as before.
Add possibility to predict entities using TED.

Here's an example of a dialogue in the Rasa story format:

```rasa-yaml
stories:
- story: collect restaurant booking info # name of the story - just for debugging
steps:
- intent: greet # user message with no entities
- action: utter_ask_howcanhelp # action that the bot should execute
- intent: inform # user message with entities
entities:
- location: "rome"
- price: "cheap"
- bot: On it # actual text that bot can output
- action: utter_ask_cuisine
- user: I would like [spanish](cuisine). # actual text that user input
- action: utter_ask_num_people
```

Some model options for `TEDPolicy` got renamed.
Please update your configuration files using the following mapping:

| Old model option | New model option |
|-----------------------------|--------------------------------------------------------|
|transformer_size |dictionary “transformer_size” with keys |
| |“text”, “action_text”, “label_action_text”, “dialogue” |
|number_of_transformer_layers |dictionary “number_of_transformer_layers” with keys |
| |“text”, “action_text”, “label_action_text”, “dialogue” |
|dense_dimension |dictionary “dense_dimension” with keys |
| |“text”, “action_text”, “label_action_text”, “intent”, |
| |“action_name”, “label_action_name”, “entities”, “slots”,|
| |“active_loop” |
6 changes: 3 additions & 3 deletions docs/docs/components.mdx
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Expand Up @@ -1485,7 +1485,7 @@ However, additional parameters exist that can be adapted.
+=================================+==================+==============================================================+
| hidden_layers_sizes | text: [] | Hidden layer sizes for layers before the embedding layers |
| | label: [] | for user messages and labels. The number of hidden layers is |
| | | equal to the length of the corresponding. |
| | | equal to the length of the corresponding list. |
+---------------------------------+------------------+--------------------------------------------------------------+
| share_hidden_layers | False | Whether to share the hidden layer weights between user |
| | | messages and labels. |
Expand Down Expand Up @@ -1519,8 +1519,8 @@ However, additional parameters exist that can be adapted.
+---------------------------------+------------------+--------------------------------------------------------------+
| embedding_dimension | 20 | Dimension size of embedding vectors. |
+---------------------------------+------------------+--------------------------------------------------------------+
| dense_dimension | text: 128 | Dense dimension for sparse features to use if no dense |
| | label: 20 | features are present. |
| dense_dimension | text: 128 | Dense dimension for sparse features to use. |
| | label: 20 | |
+---------------------------------+------------------+--------------------------------------------------------------+
| concat_dimension | text: 128 | Concat dimension for sequence and sentence features. |
| | label: 20 | |
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56 changes: 56 additions & 0 deletions docs/docs/migration-guide.mdx
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Expand Up @@ -12,8 +12,54 @@ how you can migrate from one version to another.

## Rasa 2.1 to Rasa 2.2

### General

`TEDPolicy`'s `transformer_size`, `number_of_transformer_layers`,
and `dense_dimensions` parameters have been renamed.
Please update your configuration files using the following mapping:

| Old Model Parameter | New Model Parameter |
|-----------------------------|--------------------------------------------------------|
|`transformer_size` |dictionary `transformer_size` with keys |
| |`text`, `action_text`, `label_action_text`, `dialogue` |
|`number_of_transformer_layers`|dictionary `number_of_transformer_layers` with keys |
| |`text`, `action_text`, `label_action_text`, `dialogue` |
|`dense_dimension` |dictionary `dense_dimension` with keys |
| |`text`, `action_text`, `label_action_text`, `intent`, |
| |`action_name`, `label_action_name`, `entities`, `slots`,|
| |`active_loop` |

For example:

```yaml-rasa title="config.yml"
policies:
- name: TEDPolicy
transformer_size:
text: 128
action_text: 128
label_action_text: 128
dialogue: 128
number_of_transformer_layers:
text: 1
action_text: 1
label_action_text: 1
dialogue: 1
dense_dimension:
text: 128
action_text: 128
label_action_text: 128
intent: 20
action_name: 20
label_action_name: 20
entities: 20
slots: 20
active_loop: 20
```


### Deprecations

#### Markdown Data
Training and test data in Markdown format is now deprecated. This includes:
- reading and writing of story files in Markdown format
- reading and writing of NLU data in Markdown format
Expand All @@ -24,13 +70,23 @@ Support for Markdown data will be removed entirely in Rasa Open Source 3.0.0.
Please convert your existing Markdown data by using the commands
described [here](./migration-guide.mdx#training-data-files).


### Policies

[Policies](./policies.mdx) now require a `**kwargs` argument in their constructor and `load` method.
Policies without `**kwargs` will be supported until Rasa version `3.0.0`.
However when using [incremental training](./command-line-interface.mdx#incremental-training)
`**kwargs` **must** be included.


#### Other

* `Domain.random_template_for` is deprecated and will be removed in Rasa Open Source
3.0.0. You can alternatively use the `TemplatedNaturalLanguageGenerator`.
* `Domain.action_names` is deprecated and will be removed in Rasa Open Source
3.0.0. Please use `Domain.action_names_or_texts` instead.


## Rasa 2.0 to Rasa 2.1

### Deprecations
Expand Down
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