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# coding=utf-8
# Copyright 2024 weblab. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING
from transformers.utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_import_structure = {
"configuration_kinoe": ["KinoeConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["modeling_kinoe"] = [
"KinoeForCausalLM",
"KinoeModel",
"KinoePreTrainedModel",
"KinoeForSequenceClassification",
"KinoeForTokenClassification",
]
if TYPE_CHECKING:
from .configuration_kinoe import KinoeConfig
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .modeling_kinoe import (
KinoeForCausalLM,
KinoeForSequenceClassification,
KinoeForTokenClassification,
KinoeModel,
KinoePreTrainedModel,
)
else:
import sys
sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__) |