# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team and Alibaba PAI team
#
# 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 ...file_utils import (
    _BaseLazyModule,
    is_tokenizers_available,
    is_torch_available
)

_import_structure = {
    # "configuration_bert": ["BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BertConfig"],
    "configuration_bert": ["BertConfig"],
    "tokenization_bert": ["BasicTokenizer", "BertTokenizer", "WordpieceTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_bert_fast"] = ["BertTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_megatron_bert"] = [
        "MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "MegatronBertForCausalLM",
        "MegatronBertForMaskedLM",
        "MegatronBertForMultipleChoice",
        "MegatronBertForNextSentencePrediction",
        "MegatronBertForPreTraining",
        "MegatronBertForQuestionAnswering",
        "MegatronBertForSequenceClassification",
        "MegatronBertForTokenClassification",
        "MegatronBertModel",
        "MegatronBertPreTrainedModel",
    ]

# if is_tf_available():
#     _import_structure["modeling_tf_bert"] = [
#         "TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
#         "TFBertEmbeddings",
#         "TFBertForMaskedLM",
#         "TFBertForMultipleChoice",
#         "TFBertForNextSentencePrediction",
#         "TFBertForPreTraining",
#         "TFBertForQuestionAnswering",
#         "TFBertForSequenceClassification",
#         "TFBertForTokenClassification",
#         "TFBertLMHeadModel",
#         "TFBertMainLayer",
#         "TFBertModel",
#         "TFBertPreTrainedModel",
#     ]

# if is_flax_available():
#     _import_structure["modeling_flax_bert"] = [
#         "FlaxBertForMaskedLM",
#         "FlaxBertForMultipleChoice",
#         "FlaxBertForNextSentencePrediction",
#         "FlaxBertForPreTraining",
#         "FlaxBertForQuestionAnswering",
#         "FlaxBertForSequenceClassification",
#         "FlaxBertForTokenClassification",
#         "FlaxBertModel",
#         "FlaxBertPreTrainedModel",
#     ]

if TYPE_CHECKING:
    # from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig
    # from .configuration_megatron_bert import BertConfig
    # from .tokenization_megatron_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer

    # if is_tokenizers_available():
    #     from .tokenization_modeling_bert_fast import BertTokenizerFast
    from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig
    
    if is_torch_available():
        from .modeling_megatron_bert import (
            MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            MegatronBertForCausalLM,
            MegatronBertForMaskedLM,
            MegatronBertForMultipleChoice,
            MegatronBertForNextSentencePrediction,
            MegatronBertForPreTraining,
            MegatronBertForQuestionAnswering,
            MegatronBertForSequenceClassification,
            MegatronBertForTokenClassification,
            MegatronBertModel,
            MegatronBertPreTrainedModel,
        )

else:
    import importlib
    import os
    import sys

    class _LazyModule(_BaseLazyModule):
        """
        Module class that surfaces all objects but only performs associated imports when the objects are requested.
        """

        __file__ = globals()["__file__"]
        __path__ = [os.path.dirname(__file__)]

        def _get_module(self, module_name: str):
            return importlib.import_module("." + module_name, self.__name__)

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