72 lines
3.4 KiB
Python
72 lines
3.4 KiB
Python
from .configuration_utils import PretrainedConfig
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class AlbertConfig(PretrainedConfig):
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"""Configuration for `AlbertModel`.
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The default settings match the configuration of model `albert_xxlarge`.
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"""
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def __init__(self,
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vocab_size_or_config_json_file,
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embedding_size=128,
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hidden_size=4096,
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num_hidden_layers=12,
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num_hidden_groups=1,
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num_attention_heads=64,
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intermediate_size=16384,
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inner_group_num=1,
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down_scale_factor=1,
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hidden_act="gelu",
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hidden_dropout_prob=0,
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attention_probs_dropout_prob=0,
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max_position_embeddings=512,
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type_vocab_size=2,
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initializer_range=0.02,
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layer_norm_eps=1e-12, **kwargs):
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"""Constructs AlbertConfig.
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Args:
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vocab_size: Vocabulary size of `inputs_ids` in `AlbertModel`.
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embedding_size: size of voc embeddings.
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hidden_size: Size of the encoder layers and the pooler layer.
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num_hidden_layers: Number of hidden layers in the Transformer encoder.
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num_hidden_groups: Number of group for the hidden layers, parameters in
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the same group are shared.
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num_attention_heads: Number of attention heads for each attention layer in
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the Transformer encoder.
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intermediate_size: The size of the "intermediate" (i.e., feed-forward)
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layer in the Transformer encoder.
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inner_group_num: int, number of inner repetition of attention and ffn.
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down_scale_factor: float, the scale to apply
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hidden_act: The non-linear activation function (function or string) in the
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encoder and pooler.
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hidden_dropout_prob: The dropout probability for all fully connected
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layers in the embeddings, encoder, and pooler.
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attention_probs_dropout_prob: The dropout ratio for the attention
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probabilities.
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max_position_embeddings: The maximum sequence length that this model might
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ever be used with. Typically set this to something large just in case
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(e.g., 512 or 1024 or 2048).
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type_vocab_size: The vocabulary size of the `token_type_ids` passed into
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`AlbertModel`.
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initializer_range: The stdev of the truncated_normal_initializer for
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initializing all weight matrices.
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"""
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super(AlbertConfig, self).__init__(**kwargs)
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self.vocab_size = vocab_size_or_config_json_file
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self.embedding_size = embedding_size
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self.hidden_size = hidden_size
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self.num_hidden_layers = num_hidden_layers
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self.num_hidden_groups = num_hidden_groups
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self.num_attention_heads = num_attention_heads
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self.inner_group_num = inner_group_num
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self.down_scale_factor = down_scale_factor
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self.hidden_act = hidden_act
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self.intermediate_size = intermediate_size
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self.hidden_dropout_prob = hidden_dropout_prob
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self.attention_probs_dropout_prob = attention_probs_dropout_prob
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self.max_position_embeddings = max_position_embeddings
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self.type_vocab_size = type_vocab_size
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self.initializer_range = initializer_range
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self.layer_norm_eps = layer_norm_eps |