Added adapters to whisper

adapter_docs/classes/models/whisper.rst

@@ -0,0 +1,17 @@
+Whisper
+-----------------------------------------------------------------------------------------------------------------------
+
+The Whisper model was presented in `Robust Speech Recognition via Large-Scale Weak Supervision
+<https://arxiv.org/abs/2212.04356>`_ by Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine
+McLeavey, Ilya Sutskever.
+
+According to the abstract, Whisper is trained on 680,000 hours of multilingual and multitask data. This
+scale was previously unseen. Whisper is able to approach the accuracy and robustness of humans.
+
+
+WhisperAdapterModel
+~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.adapters.WhisperAdapterModel
+    :members:
+    :inherited-members: WhisperPreTrainedModel

adapter_docs/index.rst

@@ -70,6 +70,7 @@ Currently, we support the PyTorch versions of all models as listed on the `Model
    classes/models/gpt2
    classes/models/gptj
    classes/models/mbart
+   classes/models/whisper
    classes/models/roberta
    classes/models/t5
    classes/models/vit

adapter_docs/model_overview.md

@@ -25,6 +25,7 @@ The table below further shows which model architectures support which adaptation
 | [GPT-2](classes/models/gpt2.html)       | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
 | [GPT-J](classes/models/gptj.html)       | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
 | [MBart](classes/models/mbart.html)      | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Whisper](classes/models/whisper.html)  | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
 | [RoBERTa](classes/models/roberta.html)  | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
 | [T5](classes/models/t5.html)            | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
 | [ViT](classes/models/vit.html)            | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |

src/transformers/__init__.py

@@ -2604,6 +2604,8 @@
         "MAMConfig",
         "MBartAdapterModel",
         "MBartModelWithHeads",
+        "WhisperAdapterModel",
+        "WhisperModelWithHeads",
         "ModelAdaptersConfig",
         "ModelAdaptersMixin",
         "ModelWithFlexibleHeadsAdaptersMixin",
@@ -5708,6 +5710,8 @@
             MAMConfig,
             MBartAdapterModel,
             MBartModelWithHeads,
+            WhisperAdapterModel,
+            WhisperModelWithHeads,
             ModelAdaptersConfig,
             ModelAdaptersMixin,
             ModelWithFlexibleHeadsAdaptersMixin,

src/transformers/adapters/__init__.py

@@ -118,6 +118,10 @@
         "MBartAdapterModel",
         "MBartModelWithHeads",
     ],
+    "models.whisper": [
+        "WhisperAdapterModel",
+        "WhisperModelWithHeads",
+    ],    
     "models.roberta": [
         "RobertaAdapterModel",
         "RobertaModelWithHeads",
@@ -219,6 +223,7 @@
     from .models.gpt2 import GPT2AdapterModel, GPT2ModelWithHeads
     from .models.gptj import GPTJAdapterModel
     from .models.mbart import MBartAdapterModel, MBartModelWithHeads
+    from .models.whisper import WhisperAdapterModel, WhisperModelWithHeads
     from .models.roberta import RobertaAdapterModel, RobertaModelWithHeads
     from .models.t5 import T5AdapterModel, T5ModelWithHeads
     from .models.vit import ViTAdapterModel

src/transformers/adapters/composition.py

@@ -108,6 +108,7 @@ def __init__(self, *split_adapters: List[Union[AdapterCompositionBlock, str]], b
         "deberta",
         "bart",
         "mbart",
+        "whisper",
         "gpt2",
         "gptj",
         "t5",

src/transformers/adapters/head_utils.py

@@ -314,6 +314,13 @@
         },
         "layers": ["lm_head"],
     },
+    # Whisper
+    "WhisperForConditionalGeneration": {
+        "config": {
+            "head_type": "seq2seq_lm",
+        },
+        "layers": ["proj_out"],
+    },
     # DistilBERT
     "DistilBertForSequenceClassification": {
         "config": {

src/transformers/adapters/mixins/whisper.py

@@ -0,0 +1,51 @@
+from typing import Iterable, Tuple
+
+import torch.nn as nn
+
+from ..layer import AdapterLayer
+from ..model_mixin import (
+    EmbeddingAdaptersMixin,
+    EmbeddingAdaptersWrapperMixin,
+    InvertibleAdaptersWrapperMixin,
+    ModelAdaptersMixin,
+    ModelWithHeadsAdaptersMixin,
+)
+
+
+class WhisperEncoderLayerAdaptersMixin:
+    """Adds adapters to the WhisperEncoderLayer module of WHISPER."""
+
+    def _init_adapter_modules(self):
+        self.attention_adapters = AdapterLayer("mh_adapter", self.config)
+        self.output_adapters = AdapterLayer("output_adapter", self.config)
+        self.attention_adapters._init_adapter_modules()
+        self.output_adapters._init_adapter_modules()
+
+
+class WhisperDecoderLayerAdaptersMixin(WhisperEncoderLayerAdaptersMixin):
+    """Adds adapters to the WhisperDecoderLayer module of WHISPER."""
+
+    def _init_adapter_modules(self):
+        super()._init_adapter_modules()
+        self.cross_attention_adapters = AdapterLayer("cross_adapter", self.config)
+        self.cross_attention_adapters._init_adapter_modules()
+
+
+class WhisperModelAdaptersMixin(EmbeddingAdaptersMixin, InvertibleAdaptersWrapperMixin, ModelAdaptersMixin):
+    """Adds adapters to the WhisperModel class."""
+
+    invertible_adapters_base_name = "encoder"
+
+    def iter_layers(self) -> Iterable[Tuple[int, nn.Module]]:
+        if hasattr(self, "encoder"):
+            for i, layer in enumerate(self.encoder.layers):
+                yield i, layer
+            for i, layer in enumerate(self.decoder.layers, start=len(self.encoder.layers)):
+                yield i, layer
+        else:
+            for i, layer in enumerate(self.decoder.layers):
+                yield i, layer
+
+
+class WhisperModelWithHeadsAdaptersMixin(EmbeddingAdaptersWrapperMixin, ModelWithHeadsAdaptersMixin):
+    pass

src/transformers/adapters/models/auto/adapter_model.py

@@ -19,6 +19,7 @@
         ("deberta", "DebertaAdapterModel"),
         ("bart", "BartAdapterModel"),
         ("mbart", "MBartAdapterModel"),
+        ("whisper", "WhisperAdapterModel"),
         ("gpt2", "GPT2AdapterModel"),
         ("gptj", "GPTJAdapterModel"),
         ("t5", "T5AdapterModel"),
@@ -33,6 +34,7 @@
         ("distilbert", "DistilBertModelWithHeads"),
         ("bart", "BartModelWithHeads"),
         ("mbart", "MBartModelWithHeads"),
+        ("whisper", "WhisperModelWithHeads"),
         ("gpt2", "GPT2ModelWithHeads"),
         ("t5", "T5ModelWithHeads"),
     ]

src/transformers/adapters/models/whisper/__init__.py

@@ -0,0 +1,24 @@
+from typing import TYPE_CHECKING
+
+from ....utils import _LazyModule
+
+
+_import_structure = {
+    "adapter_model": [
+        "WhisperAdapterModel",
+        "WhisperModelWithHeads",
+    ],
+}
+
+
+if TYPE_CHECKING:
+    from .adapter_model import WhisperAdapterModel, WhisperModelWithHeads
+
+else:
+    import sys
+
+    sys.modules[__name__] = _LazyModule(
+        __name__,
+        globals()["__file__"],
+        _import_structure,
+    )