wehub-resource-sync
78 lines
2.8 KiB
Python
78 lines
2.8 KiB
Python
# coding=utf-8
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from transformers.models.layoutlm.configuration_layoutlm import LayoutLMConfig
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from transformers.utils import logging
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logger = logging.get_logger(__name__)
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LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP = {
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"layoutlmv2-base-uncased": "https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json",
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"layoutlmv2-large-uncased": "https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json",
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}
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class LayoutLMv2Config(LayoutLMConfig):
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model_type = "layoutlmv2"
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def __init__(
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self,
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vocab_size=30522,
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hidden_size=768,
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num_hidden_layers=12,
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num_attention_heads=12,
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intermediate_size=3072,
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hidden_act="gelu",
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hidden_dropout_prob=0.1,
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attention_probs_dropout_prob=0.1,
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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,
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pad_token_id=0,
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gradient_checkpointing=False,
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max_2d_position_embeddings=1024,
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max_rel_pos=128,
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rel_pos_bins=32,
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fast_qkv=True,
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max_rel_2d_pos=256,
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rel_2d_pos_bins=64,
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convert_sync_batchnorm=True,
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image_feature_pool_shape=[7, 7, 256],
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coordinate_size=128,
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shape_size=128,
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has_relative_attention_bias=True,
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has_spatial_attention_bias=True,
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has_visual_segment_embedding=False,
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**kwargs
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):
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super().__init__(
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vocab_size=vocab_size,
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hidden_size=hidden_size,
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num_hidden_layers=num_hidden_layers,
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num_attention_heads=num_attention_heads,
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intermediate_size=intermediate_size,
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hidden_act=hidden_act,
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hidden_dropout_prob=hidden_dropout_prob,
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attention_probs_dropout_prob=attention_probs_dropout_prob,
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max_position_embeddings=max_position_embeddings,
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type_vocab_size=type_vocab_size,
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initializer_range=initializer_range,
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layer_norm_eps=layer_norm_eps,
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pad_token_id=pad_token_id,
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gradient_checkpointing=gradient_checkpointing,
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**kwargs,
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)
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self.max_2d_position_embeddings = max_2d_position_embeddings
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self.max_rel_pos = max_rel_pos
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self.rel_pos_bins = rel_pos_bins
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self.fast_qkv = fast_qkv
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self.max_rel_2d_pos = max_rel_2d_pos
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self.rel_2d_pos_bins = rel_2d_pos_bins
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self.convert_sync_batchnorm = convert_sync_batchnorm
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self.image_feature_pool_shape = image_feature_pool_shape
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self.coordinate_size = coordinate_size
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self.shape_size = shape_size
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self.has_relative_attention_bias = has_relative_attention_bias
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self.has_spatial_attention_bias = has_spatial_attention_bias
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self.has_visual_segment_embedding = has_visual_segment_embedding
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