# Copyright (c) 2022 PaddlePaddle Authors. 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. """ UNIMO model configuration""" from __future__ import annotations from paddlenlp.transformers.configuration_utils import PretrainedConfig __all__ = ["UNIMO_PRETRAINED_INIT_CONFIGURATION", "UNIMOConfig", "UNIMO_PRETRAINED_RESOURCE_FILES_MAP"] UNIMO_PRETRAINED_INIT_CONFIGURATION = { "unimo-text-1.0": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-lcsts-new": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-summary": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-large": { "vocab_size": 12800, "hidden_size": 1024, "num_hidden_layers": 24, "num_attention_heads": 16, "intermediate_size": 4096, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 512, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 12088, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-dureader_qg": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-question-generation": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-question-generation-full_domain": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, "unimo-text-1.0-question-generation-dureader_qg": { "vocab_size": 18000, "hidden_size": 768, "num_hidden_layers": 12, "num_attention_heads": 12, "intermediate_size": 3072, "hidden_act": "relu", "hidden_dropout_prob": 0.1, "attention_probs_dropout_prob": 0.1, "normalize_before": False, "max_position_embeddings": 513, "type_vocab_size": 4, "initializer_range": 0.02, "unk_token_id": 17963, "pad_token_id": 0, "bos_token_id": 1, "eos_token_id": 3, "mask_token_id": 3, }, } UNIMO_PRETRAINED_RESOURCE_FILES_MAP = { "model_state": { "unimo-text-1.0": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0.pdparams", "unimo-text-1.0-lcsts-new": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-lcsts-new.pdparams", "unimo-text-1.0-large": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-large.pdparams", "unimo-text-1.0-summary": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-summary.pdparams", "unimo-text-1.0-dureader_qg": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-dureader_qg.pdparams", "unimo-text-1.0-question-generation": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-question-generation.pdparams", "unimo-text-1.0-question-generation-v2": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-question-generation-full_domain.pdparams", "unimo-text-1.0-question-generation-dureader_qg": "https://bj.bcebos.com/paddlenlp/models/transformers/unimo/unimo-text-1.0-question-generation-dureader_qg.pdparams", } } class UNIMOConfig(PretrainedConfig): r""" This is the configuration class to store the configuration of a [`UNIMOModel`]. It is used to instantiate a UNIMO 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 UNIMO unimo-text-1.0 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): Vocabulary size of `inputs_ids` in `UNIMOModel`. Also is the vocab size of token embedding matrix. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling `UNIMOModel`. Defaults to `18000`. hidden_size (int, optional): Dimensionality of the embedding layers and encoder layers. Defaults to `768`. num_hidden_layers (int, optional): The number of hidden layers in the Transformer encoder. Defaults to `12`. num_attention_heads (int, optional): Number of attention heads for each attention layer in the Transformer encoder. Defaults to `12`. intermediate_size (int, optional): Dimensionality of the feed-forward (ff) layer in the encoder. Input tensors to ff layers are firstly projected from `hidden_size` to `intermediate_size`, and then projected back to `hidden_size`. Typically `intermediate_size` is larger than `hidden_size`. Defaults to `3072`. hidden_act (str, optional): The non-linear activation function in the feed-forward layer. ``"gelu"``, ``"relu"`` and any other paddle supported activation functions are supported. Defaults to ``"gelu"``. hidden_dropout_prob(float, optional): The dropout probability used in pre-process and post-precess of MHA and FFN sub-layer. Defaults to 0.1. attention_probs_dropout_prob (float, optional): The dropout probability used in MultiHeadAttention in all encoder layers to drop some attention target. Defaults to `0.1`. normalize_before (bool, optional): Indicate whether to put layer normalization into preprocessing of MHA and FFN sub-layers. If True, pre-process is layer normalization and post-precess includes dropout, residual connection. Otherwise, no pre-process and post-precess includes dropout, residual connection, layer normalization. Defaults to `True`. max_position_embeddings (int, optional): The maximum value of the dimensionality of position encoding, which dictates the maximum supported length of an input sequence. Defaults to `512`. type_vocab_size (int, optional): The vocabulary size of the `token_type_ids` passed when calling `~transformers.UNIMOModel`. Defaults to `2`. initializer_range (float, optional): The standard deviation of the normal initializer. Defaults to `0.02`. .. note:: A normal_initializer initializes weight matrices as normal distributions. See :meth:`UNIMOPretrainedModel._init_weights()` for how weights are initialized in `UNIMOModel`. unk_token_id (int, optional): A special token representing the *unknown (out-of-vocabulary)* token. An unknown token is set to be `unk_token` in order to be converted to an ID. Defaults to `17963`. pad_token_id (int, optional): A special token used to make arrays of tokens the same size for batching purposes. Defaults to `0`. bos_token_id (int, optional): A special token representing the beginning of a sequence that was used during pretraining. Defaults to `1`. eos_token_id (int, optional): A special token representing the end of a sequence that was used during pretraining. Defaults to `3`. mask_token_id (int, optional): A special token representing a masked token. This is the token used in the masked language modeling task which the model tries to predict the original unmasked ones. Defaults to `3`. ```""" model_type = "unimo" pretrained_init_configuration = UNIMO_PRETRAINED_INIT_CONFIGURATION def __init__( self, vocab_size: int = 18000, hidden_size: int = 768, num_hidden_layers: int = 12, num_attention_heads: int = 12, intermediate_size: int = 3072, hidden_act: str = "relu", hidden_dropout_prob: float = 0.1, attention_probs_dropout_prob: float = 0.1, normalize_before: int = False, max_position_embeddings: int = 513, type_vocab_size: int = 4, initializer_range: float = 0.02, unk_token_id: int = 17963, pad_token_id: int = 0, bos_token_id: int = 1, eos_token_id: int = 3, mask_token_id: int = 3, **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.type_vocab_size = type_vocab_size self.initializer_range = initializer_range self.normalize_before = normalize_before self.unk_token_id = unk_token_id self.mask_token_id = mask_token_id