[ErnieDoc P0] add PretrainedConfig and unit test

paddlenlp/transformers/__init__.py

@@ -86,6 +86,7 @@
 from .ernie_ctm.tokenizer import *
 from .ernie_doc.modeling import *
 from .ernie_doc.tokenizer import *
+from .ernie_doc.configuration import *
 from .ernie_gen.modeling import ErnieForGeneration
 from .ernie_gram.modeling import *
 from .ernie_gram.tokenizer import *

paddlenlp/transformers/ernie_doc/configuration.py

@@ -0,0 +1,162 @@
+# 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.
+""" DalleBart model configuration"""
+from __future__ import annotations
+
+from paddlenlp.transformers.configuration_utils import PretrainedConfig
+
+__all__ = ["ERNIE_DOC_PRETRAINED_INIT_CONFIGURATION", "ErnieDocConfig", "ERNIE_DOC_PRETRAINED_RESOURCE_FILES_MAP"]
+
+ERNIE_DOC_PRETRAINED_INIT_CONFIGURATION = {
+    "ernie-doc-base-en": {
+        "attention_dropout_prob": 0.0,
+        "hidden_act": "gelu",
+        "hidden_dropout_prob": 0.0,
+        "relu_dropout": 0.0,
+        "hidden_size": 768,
+        "initializer_range": 0.02,
+        "max_position_embeddings": 512,
+        "num_attention_heads": 12,
+        "num_hidden_layers": 12,
+        "task_type_vocab_size": 3,
+        "vocab_size": 50265,
+        "memory_len": 128,
+        "epsilon": 1e-12,
+        "pad_token_id": 1,
+    },
+    "ernie-doc-base-zh": {
+        "attention_dropout_prob": 0.1,
+        "hidden_act": "gelu",
+        "hidden_dropout_prob": 0.1,
+        "relu_dropout": 0.0,
+        "hidden_size": 768,
+        "initializer_range": 0.02,
+        "max_position_embeddings": 512,
+        "num_attention_heads": 12,
+        "num_hidden_layers": 12,
+        "task_type_vocab_size": 3,
+        "vocab_size": 28000,
+        "memory_len": 128,
+        "epsilon": 1e-12,
+        "pad_token_id": 0,
+    },
+}
+
+ERNIE_DOC_PRETRAINED_RESOURCE_FILES_MAP = {
+    "model_state": {
+        "ernie-doc-base-en": "https://bj.bcebos.com/paddlenlp/models/transformers/ernie-doc-base-en/ernie-doc-base-en.pdparams",
+        "ernie-doc-base-zh": "https://bj.bcebos.com/paddlenlp/models/transformers/ernie-doc-base-zh/ernie-doc-base-zh.pdparams",
+    }
+}
+
+
+class ErnieDocConfig(PretrainedConfig):
+    """
+    The bare ERNIE-Doc Model outputting raw hidden-states.
+
+    This model inherits from :class:`~paddlenlp.transformers.model_utils.PretrainedModel`.
+    Refer to the superclass documentation for the generic methods.
+
+    This model is also a `paddle.nn.Layer <https://www.paddlepaddle.org.cn/documentation
+    /docs/en/api/paddle/fluid/dygraph/layers/Layer_en.html>`__ subclass. Use it as a regular Paddle Layer
+    and refer to the Paddle documentation for all matter related to general usage and behavior.
+
+    Args:
+        num_hidden_layers (int):
+            The number of hidden layers in the Transformer encoder.
+        num_attention_heads (int):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        hidden_size (int):
+            Dimensionality of the embedding layers, encoder layers and pooler layer.
+        hidden_dropout_prob (int):
+            The dropout probability for all fully connected layers in the embeddings and encoder.
+        attention_dropout_prob (int):
+            The dropout probability used in MultiHeadAttention in all encoder layers to drop some attention target.
+        relu_dropout (int):
+            The dropout probability of FFN.
+        hidden_act (str):
+            The non-linear activation function of FFN.
+        memory_len (int):
+            The number of tokens to cache. If not 0, the last `memory_len` hidden states
+            in each layer will be cached into memory.
+        vocab_size (int):
+            Vocabulary size of `inputs_ids` in `ErnieDocModel`. 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 `ErnieDocModel`.
+        max_position_embeddings (int):
+            The maximum value of the dimensionality of position encoding, which dictates the maximum supported length of an input
+            sequence. Defaults to `512`.
+        task_type_vocab_size (int, optional):
+            The vocabulary size of the `token_type_ids`. Defaults to `3`.
+        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 `False`.
+        epsilon (float, optional):
+            The `epsilon` parameter used in :class:`paddle.nn.LayerNorm` for
+            initializing layer normalization layers. Defaults to `1e-5`.
+        rel_pos_params_sharing (bool, optional):
+            Whether to share the relative position parameters.
+            Defaults to `False`.
+        initializer_range (float, optional):
+            The standard deviation of the normal initializer for initializing all weight matrices.
+            Defaults to `0.02`.
+        pad_token_id (int, optional):
+            The token id of [PAD] token whose parameters won't be updated when training.
+            Defaults to `0`.
+        cls_token_idx (int, optional):
+            The token id of [CLS] token. Defaults to `-1`.
+    """
+
+    model_type = "ernie_doc"
+    pretrained_init_configuration = ERNIE_DOC_PRETRAINED_INIT_CONFIGURATION
+
+    def __init__(
+        self,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        hidden_size=768,
+        hidden_dropout_prob=0.1,
+        attention_dropout_prob=0.1,
+        relu_dropout=0.0,
+        hidden_act="gelu",
+        memory_len=128,
+        vocab_size=28000,
+        max_position_embeddings=512,
+        task_type_vocab_size=3,
+        normalize_before=False,
+        epsilon=1e-5,
+        rel_pos_params_sharing=False,
+        initializer_range=0.02,
+        pad_token_id=0,
+        cls_token_idx=-1,
+        **kwargs
+    ):
+        super(ErnieDocConfig, self).__init__(pad_token_id=pad_token_id, **kwargs)
+        self.vocab_size = vocab_size
+        self.attention_dropout_prob = attention_dropout_prob
+        self.relu_dropout = relu_dropout
+        self.hidden_act = hidden_act
+        self.memory_len = memory_len
+        self.hidden_size = hidden_size
+        self.task_type_vocab_size = task_type_vocab_size
+        self.normalize_before = normalize_before
+        self.epsilon = epsilon
+        self.rel_pos_params_sharing = rel_pos_params_sharing
+        self.cls_token_idx = cls_token_idx
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.max_position_embeddings = max_position_embeddings
+        self.initializer_range = initializer_range