# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. # Copyright 2021 Microsoft Research and The HuggingFace Inc. 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. """ LayoutLMv2 model configuration""" from typing import Dict from ..configuration_utils import PretrainedConfig __all__ = ["LAYOUTLMV2_PRETRAINED_INIT_CONFIGURATION", "LayoutLMv2Config", "LAYOUTLMV2_PRETRAINED_RESOURCE_FILES_MAP"] LAYOUTLMV2_PRETRAINED_INIT_CONFIGURATION = { "layoutlmv2-base-uncased": { "attention_probs_dropout_prob": 0.1, "coordinate_size": 128, "fast_qkv": True, "gradient_checkpointing": False, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 768, "image_feature_pool_shape": [7, 7, 256], "initializer_range": 0.02, "intermediate_size": 3072, "layer_norm_eps": 1e-12, "max_2d_position_embeddings": 1024, "max_position_embeddings": 512, "max_rel_2d_pos": 256, "max_rel_pos": 128, "model_type": "layoutlmv2", "num_attention_heads": 12, "num_hidden_layers": 12, "output_past": True, "pad_token_id": 0, "shape_size": 128, "rel_2d_pos_bins": 64, "rel_pos_bins": 32, "type_vocab_size": 2, "vocab_size": 30522, "has_relative_attention_bias": True, "has_spatial_attention_bias": True, "has_visual_segment_embedding": False, "use_visual_backbone": True, }, "layoutlmv2-large-uncased": { "attention_probs_dropout_prob": 0.1, "coordinate_size": 171, "fast_qkv": False, "gradient_checkpointing": False, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 1024, "image_feature_pool_shape": [7, 7, 256], "initializer_range": 0.02, "intermediate_size": 4096, "layer_norm_eps": 1e-12, "max_2d_position_embeddings": 1024, "max_position_embeddings": 512, "max_rel_2d_pos": 256, "max_rel_pos": 128, "model_type": "layoutlmv2", "num_attention_heads": 16, "num_hidden_layers": 24, "output_past": True, "pad_token_id": 0, "shape_size": 170, "rel_2d_pos_bins": 64, "rel_pos_bins": 32, "type_vocab_size": 2, "vocab_size": 30522, "has_relative_attention_bias": True, "has_spatial_attention_bias": True, "has_visual_segment_embedding": False, "use_visual_backbone": True, }, "vi-layoutlmv2-base-uncased": { "attention_probs_dropout_prob": 0.1, "coordinate_size": 128, "fast_qkv": True, "gradient_checkpointing": False, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 768, "image_feature_pool_shape": [7, 7, 256], "initializer_range": 0.02, "intermediate_size": 3072, "layer_norm_eps": 1e-12, "max_2d_position_embeddings": 1024, "max_position_embeddings": 512, "max_rel_2d_pos": 256, "max_rel_pos": 128, "model_type": "layoutlmv2", "num_attention_heads": 12, "num_hidden_layers": 12, "output_past": True, "pad_token_id": 0, "shape_size": 128, "rel_2d_pos_bins": 64, "rel_pos_bins": 32, "type_vocab_size": 2, "vocab_size": 30522, "has_relative_attention_bias": True, "has_spatial_attention_bias": True, "has_visual_segment_embedding": False, "use_visual_backbone": False, }, } LAYOUTLMV2_PRETRAINED_RESOURCE_FILES_MAP = { "model_state": { "layoutlmv2-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/layoutlmv2-base-uncased/model_state.pdparams", "layoutlmv2-large-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/layoutlmv2-large-uncased/model_state.pdparams", "vi-layoutlmv2-base-uncased": "https://bj.bcebos.com/paddlenlp/models/transformers/layoutlmv2/vi-layoutlmv2-base-uncased/model_state.pdparams", } } class LayoutLMv2Config(PretrainedConfig): r""" This is the configuration class to store the configuration of an [`LayoutLMv2Model`]. It is used to instantiate an LayoutLMv2 Model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the LayoutLMv2 layoutlmv2-base-uncased architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: vocab_size (`int`, optional, defaults to 21128): Vocabulary size of the NEZHA model. Defines the different tokens that can be represented by the *inputs_ids* passed to the forward method of [`NezhaModel`]. embedding_size (`int`, optional, defaults to 128): Dimensionality of vocabulary embeddings. hidden_size (`int`, optional, defaults to 768): Dimensionality of the encoder layers and the pooler layer. num_hidden_layers (`int`, optional, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, optional, defaults to 12): Number of attention heads for each attention layer in the Transformer encoder. intermediate_size (`int`, optional, defaults to 3072): The dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. hidden_act (`str` or `function`, optional, defaults to "gelu"): The non-linear activation function (function or string) in the encoder and pooler. hidden_dropout_prob (`float`, optional, defaults to 0.1): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (`float`, optional, defaults to 0.1): The dropout ratio for the attention probabilities. max_position_embeddings (`int`, optional, defaults to 512): The maximum sequence length that this model might ever be used with. Typically set this to something large (e.g., 512 or 1024 or 2048). type_vocab_size (`int`, optional, defaults to 2): The vocabulary size of the *token_type_ids* passed into [`NezhaModel`]. initializer_range (`float`, optional, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (`float`, optional, defaults to 1e-12): The epsilon used by the layer normalization layers. classifier_dropout (`float`, optional, defaults to 0.1): The dropout ratio for attached classifiers. is_decoder (`bool`, *optional*, defaults to `False`): Whether the model is used as a decoder or not. If `False`, the model is used as an encoder. Example: ```python >>> from paddlenlp.transformers import NeZhaConfig, NeZhaModel >>> # Initializing an Nezha configuration >>> configuration = NeZhaConfig() >>> # Initializing a model (with random weights) from the Nezha-base style configuration model >>> model = NeZhaModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" attribute_map: Dict[str, str] = {"dropout": "classifier_dropout", "num_classes": "num_labels"} pretrained_init_configuration = LAYOUTLMV2_PRETRAINED_INIT_CONFIGURATION model_type = "layoutlmv2" def __init__( self, vocab_size=30522, hidden_size=768, num_hidden_layers=12, num_attention_heads=12, intermediate_size=3072, hidden_act="gelu", hidden_dropout_prob=0.1, attention_probs_dropout_prob=0.1, max_position_embeddings=512, max_2d_position_embeddings=1024, max_rel_pos=128, max_rel_2d_pos=256, rel_pos_bins=32, rel_2d_pos_bins=64, type_vocab_size=2, initializer_range=0.02, layer_norm_eps=1e-12, coordinate_size=128, shape_size=128, image_feature_pool_shape=[7, 7, 256], fast_qkv=True, has_relative_attention_bias=True, has_spatial_attention_bias=True, has_visual_segment_embedding=False, output_past=True, gradient_checkpointing=False, classifier_dropout=0.1, pad_token_id=0, bos_token_id=2, eos_token_id=3, use_cache=True, with_pool="tanh", use_visual_backbone=True, **kwargs ): super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs) self.vocab_size = vocab_size self.hidden_size = hidden_size self.num_hidden_layers = num_hidden_layers self.num_attention_heads = num_attention_heads self.intermediate_size = intermediate_size self.hidden_act = hidden_act self.hidden_dropout_prob = hidden_dropout_prob self.attention_probs_dropout_prob = attention_probs_dropout_prob self.max_position_embeddings = max_position_embeddings self.max_2d_position_embeddings = max_2d_position_embeddings self.max_rel_pos = max_rel_pos self.max_rel_2d_pos = max_rel_2d_pos self.rel_pos_bins = rel_pos_bins self.rel_2d_pos_bins = rel_2d_pos_bins self.type_vocab_size = type_vocab_size self.initializer_range = initializer_range self.layer_norm_eps = layer_norm_eps self.coordinate_size = coordinate_size self.shape_size = shape_size self.image_feature_pool_shape = image_feature_pool_shape self.fast_qkv = fast_qkv self.has_relative_attention_bias = has_relative_attention_bias self.has_spatial_attention_bias = has_spatial_attention_bias self.has_visual_segment_embedding = has_visual_segment_embedding self.output_past = output_past self.gradient_checkpointing = gradient_checkpointing self.classifier_dropout = classifier_dropout self.pad_token_id = pad_token_id self.bos_token_id = bos_token_id self.eos_token_id = eos_token_id self.use_cache = use_cache self.with_pool = with_pool self.use_visual_backbone = use_visual_backbone