# coding=utf-8

# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.

# Copyright (c) 2018, NVIDIA CORPORATION.  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.

""" ALBERT model configuration """



from .configuration_utils import PretrainedConfig



ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {

    'albert-base-v1': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-base-config.json",

    'albert-large-v1': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-large-config.json",

    'albert-xlarge-v1': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xlarge-config.json",

    'albert-xxlarge-v1': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xxlarge-config.json",

    'albert-base-v2': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-base-v2-config.json",

    'albert-large-v2': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-large-v2-config.json",

    'albert-xlarge-v2': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xlarge-v2-config.json",

    'albert-xxlarge-v2': "https://s3.amazonaws.com/models.huggingface.co/bert/albert-xxlarge-v2-config.json",

}



class AlbertConfig(PretrainedConfig):

    """Configuration for `AlbertModel`.



    The default settings match the configuration of model `albert_xxlarge`.

    """



    pretrained_config_archive_map = ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP



    def __init__(self,

                 vocab_size_or_config_json_file=30000,

                 embedding_size=128,

                 hidden_size=4096,

                 num_hidden_layers=12,

                 num_hidden_groups=1,

                 num_attention_heads=64,

                 intermediate_size=16384,

                 inner_group_num=1,

                 hidden_act="gelu_new",

                 hidden_dropout_prob=0,

                 attention_probs_dropout_prob=0,

                 max_position_embeddings=512,

                 type_vocab_size=2,

                 initializer_range=0.02,

                 layer_norm_eps=1e-12, **kwargs):

        """Constructs AlbertConfig.



        Args:

            vocab_size: Vocabulary size of `inputs_ids` in `AlbertModel`.

            embedding_size: size of voc embeddings.

            hidden_size: Size of the encoder layers and the pooler layer.

            num_hidden_layers: Number of hidden layers in the Transformer encoder.

            num_hidden_groups: Number of group for the hidden layers, parameters in

                the same group are shared.

            num_attention_heads: Number of attention heads for each attention layer in

                the Transformer encoder.

            intermediate_size: The size of the "intermediate" (i.e., feed-forward)

                layer in the Transformer encoder.

            inner_group_num: int, number of inner repetition of attention and ffn.

            down_scale_factor: float, the scale to apply

            hidden_act: The non-linear activation function (function or string) in the

                encoder and pooler.

            hidden_dropout_prob: The dropout probability for all fully connected

                layers in the embeddings, encoder, and pooler.

            attention_probs_dropout_prob: The dropout ratio for the attention

                probabilities.

            max_position_embeddings: The maximum sequence length that this model might

                ever be used with. Typically set this to something large just in case

                (e.g., 512 or 1024 or 2048).

            type_vocab_size: The vocabulary size of the `token_type_ids` passed into

                `AlbertModel`.

            initializer_range: The stdev of the truncated_normal_initializer for

                initializing all weight matrices.

        """

        super(AlbertConfig, self).__init__(**kwargs)



        self.vocab_size = vocab_size_or_config_json_file

        self.embedding_size = embedding_size

        self.hidden_size = hidden_size

        self.num_hidden_layers = num_hidden_layers

        self.num_hidden_groups = num_hidden_groups

        self.num_attention_heads = num_attention_heads

        self.inner_group_num = inner_group_num

        self.hidden_act = hidden_act

        self.intermediate_size = intermediate_size

        self.hidden_dropout_prob = hidden_dropout_prob

        self.attention_probs_dropout_prob = attention_probs_dropout_prob

        self.max_position_embeddings = max_position_embeddings

        self.type_vocab_size = type_vocab_size

        self.initializer_range = initializer_range

        self.layer_norm_eps = layer_norm_eps