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Remove Roberta Dependencies from XLM Roberta Flax and Tensorflow models (#21047)

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* Added flax model code

* Added tf changes

* missed some

* Added copy comments

* Added style hints

* Fixed copy statements

* Added suggested fixes

* Made some fixes

* Style fixup

* Added necessary copy statements

* Fixing copy statements

* Added more copies

* Final copy fix

* Some bugfixes

* Adding imports to init

* Fixed up all make fixup errors

* Fixed doc errors

* Auto model changes
This commit is contained in:
Samuel Xu
2023-01-18 07:49:39 -05:00
committed by GitHub
parent 023f51fe16
commit defdcd2862
10 changed files with 3097 additions and 131 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
docs/source/en/model_doc/xlm-roberta.mdx
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@@ -146,6 +146,11 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
[[autodoc]] TFXLMRobertaModel
- call
## TFXLMRobertaForCausalLM
[[autodoc]] TFXLMRobertaForCausalLM
- call
## TFXLMRobertaForMaskedLM
[[autodoc]] TFXLMRobertaForMaskedLM
@@ -176,6 +181,11 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
[[autodoc]] FlaxXLMRobertaModel
- __call__
## FlaxXLMRobertaForCausalLM
[[autodoc]] FlaxXLMRobertaForCausalLM
- __call__
## FlaxXLMRobertaForMaskedLM
[[autodoc]] FlaxXLMRobertaForMaskedLM

10
src/transformers/__init__.py
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@@ -3153,12 +3153,14 @@ else:
_import_structure["models.xlm_roberta"].extend(
[
"TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
"TFXLMRobertaForCausalLM",
"TFXLMRobertaForMaskedLM",
"TFXLMRobertaForMultipleChoice",
"TFXLMRobertaForQuestionAnswering",
"TFXLMRobertaForSequenceClassification",
"TFXLMRobertaForTokenClassification",
"TFXLMRobertaModel",
"TFXLMRobertaPreTrainedModel",
]
)
_import_structure["models.xlnet"].extend(
@@ -3435,12 +3437,15 @@ else:
)
_import_structure["models.xlm_roberta"].extend(
[
"FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
"FlaxXLMRobertaForMaskedLM",
"FlaxXLMRobertaForMultipleChoice",
"FlaxXLMRobertaForQuestionAnswering",
"FlaxXLMRobertaForSequenceClassification",
"FlaxXLMRobertaForTokenClassification",
"FlaxXLMRobertaModel",
"FlaxXLMRobertaForCausalLM",
"FlaxXLMRobertaPreTrainedModel",
]
)
@@ -6022,12 +6027,14 @@ if TYPE_CHECKING:
)
from .models.xlm_roberta import (
TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
TFXLMRobertaForCausalLM,
TFXLMRobertaForMaskedLM,
TFXLMRobertaForMultipleChoice,
TFXLMRobertaForQuestionAnswering,
TFXLMRobertaForSequenceClassification,
TFXLMRobertaForTokenClassification,
TFXLMRobertaModel,
TFXLMRobertaPreTrainedModel,
)
from .models.xlnet import (
TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
@@ -6240,12 +6247,15 @@ if TYPE_CHECKING:
)
from .models.xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel
from .models.xlm_roberta import (
FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
FlaxXLMRobertaForCausalLM,
FlaxXLMRobertaForMaskedLM,
FlaxXLMRobertaForMultipleChoice,
FlaxXLMRobertaForQuestionAnswering,
FlaxXLMRobertaForSequenceClassification,
FlaxXLMRobertaForTokenClassification,
FlaxXLMRobertaModel,
FlaxXLMRobertaPreTrainedModel,
)
else:

1
src/transformers/models/auto/modeling_flax_auto.py
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@@ -142,6 +142,7 @@ FLAX_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES = OrderedDict(
("roberta", "FlaxRobertaForCausalLM"),
("roberta-prelayernorm", "FlaxRobertaPreLayerNormForCausalLM"),
("xglm", "FlaxXGLMForCausalLM"),
("xlm-roberta", "FlaxXLMRobertaForCausalLM"),
]
)

1
src/transformers/models/auto/modeling_tf_auto.py
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@@ -180,6 +180,7 @@ TF_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES = OrderedDict(
("transfo-xl", "TFTransfoXLLMHeadModel"),
("xglm", "TFXGLMForCausalLM"),
("xlm", "TFXLMWithLMHeadModel"),
("xlm-roberta", "TFXLMRobertaForCausalLM"),
("xlnet", "TFXLNetLMHeadModel"),
]
)

10
src/transformers/models/xlm_roberta/__init__.py
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@@ -79,12 +79,14 @@ except OptionalDependencyNotAvailable:
else:
_import_structure["modeling_tf_xlm_roberta"] = [
"TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
"TFXLMRobertaForCausalLM",
"TFXLMRobertaForMaskedLM",
"TFXLMRobertaForMultipleChoice",
"TFXLMRobertaForQuestionAnswering",
"TFXLMRobertaForSequenceClassification",
"TFXLMRobertaForTokenClassification",
"TFXLMRobertaModel",
"TFXLMRobertaPreTrainedModel",
]
try:
@@ -94,12 +96,15 @@ except OptionalDependencyNotAvailable:
pass
else:
_import_structure["modeling_flax_xlm_roberta"] = [
"FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
"FlaxXLMRobertaForMaskedLM",
"FlaxXLMRobertaForCausalLM",
"FlaxXLMRobertaForMultipleChoice",
"FlaxXLMRobertaForQuestionAnswering",
"FlaxXLMRobertaForSequenceClassification",
"FlaxXLMRobertaForTokenClassification",
"FlaxXLMRobertaModel",
"FlaxXLMRobertaPreTrainedModel",
]
if TYPE_CHECKING:
@@ -151,12 +156,14 @@ if TYPE_CHECKING:
else:
from .modeling_tf_xlm_roberta import (
TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
TFXLMRobertaForCausalLM,
TFXLMRobertaForMaskedLM,
TFXLMRobertaForMultipleChoice,
TFXLMRobertaForQuestionAnswering,
TFXLMRobertaForSequenceClassification,
TFXLMRobertaForTokenClassification,
TFXLMRobertaModel,
TFXLMRobertaPreTrainedModel,
)
try:
@@ -166,12 +173,15 @@ if TYPE_CHECKING:
pass
else:
from .modeling_flax_xlm_roberta import (
FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
FlaxXLMRobertaForCausalLM,
FlaxXLMRobertaForMaskedLM,
FlaxXLMRobertaForMultipleChoice,
FlaxXLMRobertaForQuestionAnswering,
FlaxXLMRobertaForSequenceClassification,
FlaxXLMRobertaForTokenClassification,
FlaxXLMRobertaModel,
FlaxXLMRobertaPreTrainedModel,
)
else:

1473
src/transformers/models/xlm_roberta/modeling_flax_xlm_roberta.py
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1682
src/transformers/models/xlm_roberta/modeling_tf_xlm_roberta.py
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File diff suppressed because it is too large Load Diff

10
src/transformers/models/xlm_roberta/modeling_xlm_roberta.py
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@@ -286,7 +286,7 @@ class XLMRobertaSelfAttention(nn.Module):
return outputs
# Copied from transformers.models.roberta.modeling_roberta.RobertaSelfOutput
# Copied from transformers.models.roberta.modeling_roberta.RobertaSelfOutput with Roberta->XLMRoberta
class XLMRobertaSelfOutput(nn.Module):
def __init__(self, config):
super().__init__()
@@ -351,7 +351,7 @@ class XLMRobertaAttention(nn.Module):
return outputs
# Copied from transformers.models.roberta.modeling_roberta.RobertaIntermediate
# Copied from transformers.models.roberta.modeling_roberta.RobertaIntermediate with Roberta->XLMRoberta
class XLMRobertaIntermediate(nn.Module):
def __init__(self, config):
super().__init__()
@@ -367,7 +367,7 @@ class XLMRobertaIntermediate(nn.Module):
return hidden_states
# Copied from transformers.models.roberta.modeling_roberta.RobertaOutput
# Copied from transformers.models.roberta.modeling_roberta.RobertaOutput with Roberta->XLMRoberta
class XLMRobertaOutput(nn.Module):
def __init__(self, config):
super().__init__()
@@ -567,7 +567,7 @@ class XLMRobertaEncoder(nn.Module):
)
# Copied from transformers.models.roberta.modeling_roberta.RobertaPooler
# Copied from transformers.models.roberta.modeling_roberta.RobertaPooler with Roberta->XLMRoberta
class XLMRobertaPooler(nn.Module):
def __init__(self, config):
super().__init__()
@@ -1455,7 +1455,7 @@ class XLMRobertaForTokenClassification(XLMRobertaPreTrainedModel):
)
# Copied from transformers.models.roberta.modeling_roberta.RobertaClassificationHead
# Copied from transformers.models.roberta.modeling_roberta.RobertaClassificationHead with Roberta->XLMRoberta
class XLMRobertaClassificationHead(nn.Module):
"""Head for sentence-level classification tasks."""

17
src/transformers/utils/dummy_flax_objects.py
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@@ -1152,6 +1152,16 @@ class FlaxXGLMPreTrainedModel(metaclass=DummyObject):
requires_backends(self, ["flax"])
FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = None
class FlaxXLMRobertaForCausalLM(metaclass=DummyObject):
_backends = ["flax"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])
class FlaxXLMRobertaForMaskedLM(metaclass=DummyObject):
_backends = ["flax"]
@@ -1192,3 +1202,10 @@ class FlaxXLMRobertaModel(metaclass=DummyObject):
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])
class FlaxXLMRobertaPreTrainedModel(metaclass=DummyObject):
_backends = ["flax"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])

14
src/transformers/utils/dummy_tf_objects.py
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@@ -2646,6 +2646,13 @@ class TFXLMWithLMHeadModel(metaclass=DummyObject):
TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = None
class TFXLMRobertaForCausalLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"])
class TFXLMRobertaForMaskedLM(metaclass=DummyObject):
_backends = ["tf"]
@@ -2688,6 +2695,13 @@ class TFXLMRobertaModel(metaclass=DummyObject):
requires_backends(self, ["tf"])
class TFXLMRobertaPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"])
TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST = None