# Copyright 2021 The HuggingFace 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 ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_import_structure = {
    "configuration_gpt_neo": ["GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_gpt_neo"] = [
        "GPTNeoForCausalLM",
        "GPTNeoForQuestionAnswering",
        "GPTNeoForSequenceClassification",
        "GPTNeoForTokenClassification",
        "GPTNeoModel",
        "GPTNeoPreTrainedModel",
        "load_tf_weights_in_gpt_neo",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_flax_gpt_neo"] = [
        "FlaxGPTNeoForCausalLM",
        "FlaxGPTNeoModel",
        "FlaxGPTNeoPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_gpt_neo import GPTNeoConfig, GPTNeoOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt_neo import (
            GPTNeoForCausalLM,
            GPTNeoForQuestionAnswering,
            GPTNeoForSequenceClassification,
            GPTNeoForTokenClassification,
            GPTNeoModel,
            GPTNeoPreTrainedModel,
            load_tf_weights_in_gpt_neo,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
