Deberta_v2 tf (#13120)

* Deberta_v2 tf * added new line at the end of file, make style * +V2, typo * remove never executed branch of code * rm cmnt and fixed typo in url filter * cleanup according to review comments * added #Copied from
huggingface · Aug 31, 2021 · 3efcfea · 3efcfea
1 parent 286ccef
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diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -351,7 +351,7 @@ Flax), PyTorch, and/or TensorFlow.
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
 |           DeBERTa           |       ✅       |       ✅       |       ✅        |         ✅         |      ❌      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
-|         DeBERTa-v2          |       ✅       |       ❌       |       ✅        |         ❌         |      ❌      |
+|         DeBERTa-v2          |       ✅       |       ❌       |       ✅        |         ✅         |      ❌      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
 |            DeiT             |       ❌       |       ❌       |       ✅        |         ❌         |      ❌      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+

diff --git a/docs/source/model_doc/deberta_v2.rst b/docs/source/model_doc/deberta_v2.rst
@@ -58,7 +58,8 @@ New in v2:
 - **900M model & 1.5B model** Two additional model sizes are available: 900M and 1.5B, which significantly improves the
   performance of downstream tasks.
 
-This model was contributed by `DeBERTa <https://huggingface.co/DeBERTa>`__. The original code can be found `here
+This model was contributed by `DeBERTa <https://huggingface.co/DeBERTa>`__. This model TF 2.0 implementation was
+contributed by `kamalkraj <https://huggingface.co/kamalkraj>`__. The original code can be found `here
 <https://github.com/microsoft/DeBERTa>`__.
 
 
@@ -117,3 +118,45 @@ DebertaV2ForQuestionAnswering
 
 .. autoclass:: transformers.DebertaV2ForQuestionAnswering
     :members: forward
+
+
+TFDebertaV2Model
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2Model
+    :members: call
+
+
+TFDebertaV2PreTrainedModel
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2PreTrainedModel
+    :members: call
+
+
+TFDebertaV2ForMaskedLM
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2ForMaskedLM
+    :members: call
+
+
+TFDebertaV2ForSequenceClassification
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2ForSequenceClassification
+    :members: call
+
+
+TFDebertaV2ForTokenClassification
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2ForTokenClassification
+    :members: call
+
+
+TFDebertaV2ForQuestionAnswering
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFDebertaV2ForQuestionAnswering
+    :members: call
diff --git a/src/transformers/__init__.py b/src/transformers/__init__.py
@@ -1341,6 +1341,17 @@
             "TFDebertaPreTrainedModel",
         ]
     )
+    _import_structure["models.deberta_v2"].extend(
+        [
+            "TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
+            "TFDebertaV2ForMaskedLM",
+            "TFDebertaV2ForQuestionAnswering",
+            "TFDebertaV2ForSequenceClassification",
+            "TFDebertaV2ForTokenClassification",
+            "TFDebertaV2Model",
+            "TFDebertaV2PreTrainedModel",
+        ]
+    )
     _import_structure["models.distilbert"].extend(
         [
             "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
@@ -2925,6 +2936,15 @@
             TFDebertaModel,
             TFDebertaPreTrainedModel,
         )
+        from .models.deberta_v2 import (
+            TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
+            TFDebertaV2ForMaskedLM,
+            TFDebertaV2ForQuestionAnswering,
+            TFDebertaV2ForSequenceClassification,
+            TFDebertaV2ForTokenClassification,
+            TFDebertaV2Model,
+            TFDebertaV2PreTrainedModel,
+        )
         from .models.distilbert import (
             TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFDistilBertForMaskedLM,

diff --git a/src/transformers/models/auto/modeling_tf_auto.py b/src/transformers/models/auto/modeling_tf_auto.py
@@ -29,6 +29,7 @@
 TF_MODEL_MAPPING_NAMES = OrderedDict(
     [
         # Base model mapping
+        ("deberta-v2", "TFDebertaV2Model"),
         ("deberta", "TFDebertaModel"),
         ("rembert", "TFRemBertModel"),
         ("roformer", "TFRoFormerModel"),
@@ -145,6 +146,7 @@
 TF_MODEL_FOR_MASKED_LM_MAPPING_NAMES = OrderedDict(
     [
         # Model for Masked LM mapping
+        ("deberta-v2", "TFDebertaV2ForMaskedLM"),
         ("deberta", "TFDebertaForMaskedLM"),
         ("rembert", "TFRemBertForMaskedLM"),
         ("roformer", "TFRoFormerForMaskedLM"),
@@ -185,6 +187,7 @@
 TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES = OrderedDict(
     [
         # Model for Sequence Classification mapping
+        ("deberta-v2", "TFDebertaV2ForSequenceClassification"),
         ("deberta", "TFDebertaForSequenceClassification"),
         ("rembert", "TFRemBertForSequenceClassification"),
         ("roformer", "TFRoFormerForSequenceClassification"),
@@ -214,6 +217,7 @@
 TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict(
     [
         # Model for Question Answering mapping
+        ("deberta-v2", "TFDebertaV2ForQuestionAnswering"),
         ("deberta", "TFDebertaForQuestionAnswering"),
         ("rembert", "TFRemBertForQuestionAnswering"),
         ("roformer", "TFRoFormerForQuestionAnswering"),
@@ -238,6 +242,7 @@
 TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES = OrderedDict(
     [
         # Model for Token Classification mapping
+        ("deberta-v2", "TFDebertaV2ForTokenClassification"),
         ("deberta", "TFDebertaForTokenClassification"),
         ("rembert", "TFRemBertForTokenClassification"),
         ("roformer", "TFRoFormerForTokenClassification"),

diff --git a/src/transformers/models/deberta_v2/__init__.py b/src/transformers/models/deberta_v2/__init__.py
@@ -18,14 +18,25 @@
 
 from typing import TYPE_CHECKING
 
-from ...file_utils import _LazyModule, is_torch_available
+from ...file_utils import _LazyModule, is_tf_available, is_torch_available
 
 
 _import_structure = {
     "configuration_deberta_v2": ["DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaV2Config"],
     "tokenization_deberta_v2": ["DebertaV2Tokenizer"],
 }
 
+if is_tf_available():
+    _import_structure["modeling_tf_deberta_v2"] = [
+        "TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
+        "TFDebertaV2ForMaskedLM",
+        "TFDebertaV2ForQuestionAnswering",
+        "TFDebertaV2ForSequenceClassification",
+        "TFDebertaV2ForTokenClassification",
+        "TFDebertaV2Model",
+        "TFDebertaV2PreTrainedModel",
+    ]
+
 if is_torch_available():
     _import_structure["modeling_deberta_v2"] = [
         "DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
@@ -42,6 +53,17 @@
     from .configuration_deberta_v2 import DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaV2Config
     from .tokenization_deberta_v2 import DebertaV2Tokenizer
 
+    if is_tf_available():
+        from .modeling_tf_deberta_v2 import (
+            TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
+            TFDebertaV2ForMaskedLM,
+            TFDebertaV2ForQuestionAnswering,
+            TFDebertaV2ForSequenceClassification,
+            TFDebertaV2ForTokenClassification,
+            TFDebertaV2Model,
+            TFDebertaV2PreTrainedModel,
+        )
+
     if is_torch_available():
         from .modeling_deberta_v2 import (
             DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,