Enable encoder adapters for Canary and MultiTaskAED models
# What does this PR do ?

Enable multi task AED models to add adapter support to its encoders (speech encoder and transformer encoder) and decoder (transformer decoder). Also add new API to automatically swap out original modules with adapter compatible modules.

**Collection**: [ASR]

# Changelog 
- Add support for adapter module mixin to AED multitask model
- [CORE] Add support for `replace_adapter_compatible_modules()` which automatically swaps out registered original module class with the adapter class. It also updates config so save_to() and restore_from() will automatically pick current class.
- Support mha adapter and linear adapter for both speech encoder and transformer encoder + decoder modules
- Refactor AdapterModuleMixin to separate adapter type assertion from `add_adapter`
- Refactor ASRAdapterModelMixin to separate the logic of what model is parsed  - now its determined by a simple string list of module names
- Add tests for aed multi task model with adapter support


# Usage

```python
from nemo.collections.asr.models import ASRModel
from nemo.collections.asr.parts.submodules.adapters import TransformerEncoderMultiHeadAttentionAdapterConfig
from nemo.collections.common.parts.adapter_modules import LinearAdapterConfig
 
model = ASRModel.from_pretrained("nvidia/canary-1b")

# New API to automatically swap out all original modules in model with adapter compatible modules via registry
model.replace_adapter_compatible_modules()

# Tiny Attention Adapters
adapter_cfg = TransformerEncoderMultiHeadAttentionAdapterConfig(
  hidden_size=1024,
  num_attention_heads=1,
  proj_dim=8,
)

# OR

# Linear Adapters
adapter_cfg = LinearAdapterConfig(
  in_features=1024,
  dim=8,
)

# Load adapter weights and freeze all other weights
# Adapter targets can be "", "encoder", "transf_encoder" and "transf_decoder". "" refers to encoder by default.
# Verify supported adapter target modules using `model.adapter_module_names`.
model.add_adapter("encoder:my_adapter", adapter_cfg)
model.freeze()
model.unfreeze_enabled_adapters()

# Train model ...
```


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- [ ] Bugfix
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