# Migration Guide

This page contains information about changes between major versions and how you can migrate from one version to another.

## Rasa 1.7 to Rasa 1.8

### General  
- The [TED Policy](https://legacy-docs-v1.rasa.com/1.10.23/core/policies/#ted-policy) replaced the [Keras Policy](https://legacy-docs-v1.rasa.com/1.10.23/core/policies/#keras-policy) as recommended machine learning policy. New projects generated with `rasa init` will automatically use this policy. In case you want to change your existing model configuration to use the [TED Policy](https://legacy-docs-v1.rasa.com/1.10.23/core/policies/#ted-policy) add this to the `policies` section in your `config.yml` and remove potentially existing `KerasPolicy` entries:

policies:
    # - ... other policies
    - name: TEDPolicy
      max_history: 5
      epochs: 100

- All pre-defined pipeline templates are deprecated. **Any templates you use will be** **mapped to the new configuration, but the underlying architecture is the same**. Take a look at [Choosing a Pipeline](https://legacy-docs-v1.rasa.com/1.10.23/nlu/choosing-a-pipeline/#choosing-a-pipeline) to decide on what components you should use in your configuration file.
- The [Embedding Policy](https://legacy-docs-v1.rasa.com/1.10.23/core/policies/#embedding-policy) was renamed to [TED Policy](https://legacy-docs-v1.rasa.com/1.10.23/core/policies/#ted-policy). The functionality of the policy stayed the same. Please update your configuration files to use `TEDPolicy` instead of `EmbeddingPolicy`.
- Most of the model options for `EmbeddingPolicy`, `EmbeddingIntentClassifier`, and `ResponseSelector` got renamed. Please update your configuration files using the following mapping:

| Old model option                      | New model option                                                     |
|---------------------------------------|--------------------------------------------------------------------|
| hidden_layers_sizes_a                 | dictionary “hidden_layers_sizes” with key “text”                 |
| hidden_layers_sizes_b                 | dictionary “hidden_layers_sizes” with key “label”                |
| hidden_layers_sizes_pre_dial         | dictionary “hidden_layers_sizes” with key “dialogue”             |
| hidden_layers_sizes_bot               | dictionary “hidden_layers_sizes” with key “label”                |
| num_transformer_layers                | number_of_transformer_layers                                       |
| num_heads                             | number_of_attention_heads                                          |
| max_seq_length                        | maximum_sequence_length                                            |
| dense_dim                             | dense_dimension                                                   |
| embed_dim                             | embedding_dimension                                               |
| num_neg                               | number_of_negative_examples                                        |
| mu_pos                                | maximum_positive_similarity                                        |
| mu_neg                                | maximum_negative_similarity                                        |
| use_max_sim_neg                       | use_maximum_negative_similarity                                    |
| C2                                    | regularization_constant                                            |
| C_emb                                 | negative_margin_scale                                             |
| droprate_a                            | droprate_dialogue                                                |
| droprate_b                            | droprate_label                                                   |
| evaluate_every_num_epochs             | evaluate_every_number_of_epochs                                   |
| evaluate_on_num_examples              | evaluate_on_number_of_examples                                    |

Old configuration options will be mapped to the new names, and a warning will be thrown. However, these will be deprecated in a future release.

- [EmbeddingIntentClassifier](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#embedding-intent-classifier) is now deprecated and will be replaced by [DIETClassifier](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#diet-classifier) in the future. `DIETClassfier` performs intent classification as well as entity recognition. If you want to get the same model behavior as the current `EmbeddingIntentClassifier`, you can use the following configuration of `DIETClassifier`:

pipeline:
    # - ... other components
    - name: DIETClassifier
      hidden_layers_sizes:
          text: [256, 128]
      number_of_transformer_layers: 0
      weight_sparsity: 0
      intent_classification: True
      entity_recognition: False
      use_masked_language_model: False
      BILOU_flag: False
      # ... any other parameters
    
    See [DIETClassifier](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#diet-classifier) for more information about the new component. Specifying `EmbeddingIntentClassifier` in the configuration maps to the above component definition, the behavior is unchanged from previous versions.
- `CRFEntityExtractor` is now deprecated and will be replaced by `DIETClassifier` in the future. If you want to get the same model behavior as the current `CRFEntityExtractor`, you can use the following configuration:

pipeline:
    # - ... other components
    - name: LexicalSyntacticFeaturizer
      features: [
          ["low", "title", "upper"],
          [
            "BOS",
            "EOS",
            "low",
            "prefix5",
            "prefix2",
            "suffix5",
            "suffix3",
            "suffix2",
            "upper",
            "title",
            "digit",
          ],
          ["low", "title", "upper"],
      ]
    - name: DIETClassifier
      intent_classification: False
      entity_recognition: True
      use_masked_language_model: False
      number_of_transformer_layers: 0
      # ... any other parameters
    
    `CRFEntityExtractor` featurizes user messages on its own, it does not depend on any featurizer. We extracted the featurization from the component into the new featurizer [LexicalSyntacticFeaturizer](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#lexicalsyntacticfeaturizer). Thus, in order to obtain the same results as before, you need to add this featurizer to your pipeline before the [DIETClassifier](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#diet-classifier). Specifying `CRFEntityExtractor` in the configuration maps to the above component definition, the behavior is unchanged from previous versions.
- If your pipeline contains `CRFEntityExtractor` and `EmbeddingIntentClassifier` you can substitute both components with [DIETClassifier](https://legacy-docs-v1.rasa.com/1.10.23/nlu/components/#diet-classifier). You can use the following pipeline for that:

pipeline:
    # - ... other components
    - name: LexicalSyntacticFeaturizer
      features: [
          ["low", "title", "upper"],
          [
            "BOS",
            "EOS",
            "low",
            "prefix5",
            "prefix2",
            "suffix5",
            "suffix3",
            "suffix2",
            "upper",
            "title",
            "digit",
          ],
          ["low", "title", "upper"],
      ]
    - name: DIETClassifier
      number_of_transformer_layers: 0
      # ... any other parameters

## Rasa 1.6 to Rasa 1.7

### General  
- By default, the `EmbeddingIntentClassifier`, `EmbeddingPolicy`, and `ResponseSelector` will now normalize the top 10 confidence results if the `loss_type` is `