# Copyright 2022 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_tokenizers_available,
    is_torch_available,
)


_import_structure = {
    "configuration_bloom": ["BloomConfig", "BloomOnnxConfig"],
}
try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["tokenization_bloom_fast"] = ["BloomTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_bloom"] = [
        "BloomForCausalLM",
        "BloomModel",
        "BloomPreTrainedModel",
        "BloomForSequenceClassification",
        "BloomForTokenClassification",
        "BloomForQuestionAnswering",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_flax_bloom"] = [
        "FlaxBloomForCausalLM",
        "FlaxBloomModel",
        "FlaxBloomPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_bloom import BloomConfig, BloomOnnxConfig

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_bloom_fast import BloomTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bloom import (
            BloomForCausalLM,
            BloomForQuestionAnswering,
            BloomForSequenceClassification,
            BloomForTokenClassification,
            BloomModel,
            BloomPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_bloom import FlaxBloomForCausalLM, FlaxBloomModel, FlaxBloomPreTrainedModel
else:
    import sys

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