add biogpt (#940)

mindnlp/transformers/models/__init__.py

@@ -22,6 +22,7 @@
     bart,
     bert,
     big_bird,
+    biogpt,
     bloom,
     clip,
     codegen,
@@ -84,6 +85,7 @@
 from .bart import *
 from .bert import *
 from .big_bird import *
+from .biogpt import *
 from .bloom import *
 from .clip import *
 from .codegen import *
@@ -146,6 +148,7 @@
 __all__.extend(bark.__all__)
 __all__.extend(bert.__all__)
 __all__.extend(big_bird.__all__)
+__all__.extend(biogpt.__all__)
 __all__.extend(bloom.__all__)
 __all__.extend(clip.__all__)
 __all__.extend(codegen.__all__)

mindnlp/transformers/models/auto/configuration_auto.py

@@ -38,6 +38,7 @@
         ("bart", "BartConfig"),
         ("bert", "BertConfig"),
         ("big_bird", "BigBirdConfig"),
+        ("biogpt", "BioGptConfig"),
         ("bloom", "BloomConfig"),
         ('chatglm', 'ChatGLMConfig'),
         ("clip", "CLIPConfig"),

mindnlp/transformers/models/auto/modeling_auto.py

@@ -37,6 +37,7 @@
         ("bart", "BartModel"),
         ("bert", "BertModel"),
         ("big_bird", "BigBirdModel"),
+        ("biogpt", "BioGptModel"),
         ("bloom", "BloomModel"),
         ("codegen", "CodeGenModel"),
         ("cpmant", "CpmAntModel"),
@@ -117,6 +118,7 @@
         # Model for Causal LM mapping
         ("bert", "BertLMHeadModel"),
         ("big_bird", "BigBirdForCausalLM"),
+        ("biogpt", "BioGptForCausalLM"),
         ("bloom", "BloomForCausalLM"),
         ("codegen", "CodeGenForCausalLM"),
         ("cpmant", "CpmAntForCausalLM"),
@@ -328,6 +330,7 @@
         ("bart", "BartForSequenceClassification"),
         ("bert", "BertForSequenceClassification"),
         ("big_bird", "BigBirdForSequenceClassification"),
+        ("biogpt", "BioGptForSequenceClassification"),
         ("bloom", "BloomForSequenceClassification"),
         ("deberta", "DebertaForSequenceClassification"),
         ("esm", "EsmForSequenceClassification"),

mindnlp/transformers/models/biogpt/__init__.py

@@ -0,0 +1,26 @@
+# Copyright 2024 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+Bert Model.
+"""
+from . import configuration_biogpt, modeling_biogpt, tokenization_biogpt
+from .configuration_biogpt import *
+from .modeling_biogpt import *
+from .tokenization_biogpt import *
+
+__all__ = []
+__all__.extend(configuration_biogpt.__all__)
+__all__.extend(modeling_biogpt.__all__)
+__all__.extend(tokenization_biogpt.__all__)

mindnlp/transformers/models/biogpt/configuration_biogpt.py

@@ -0,0 +1,139 @@
+# coding=utf-8
+# Copyright 2022 The HuggingFace Team and Microsoft Research AI4Science 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.
+# ============================================================================
+""" BioGPT model configuration"""
+
+from mindnlp.utils import logging
+from ...configuration_utils import PretrainedConfig
+
+
+logger = logging.get_logger(__name__)
+
+BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
+    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
+    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
+}
+
+
+class BioGptConfig(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`BioGptModel`]. It is used to instantiate an
+    BioGPT 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 BioGPT
+    [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) 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 42384):
+            Vocabulary size of the BioGPT model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`BioGptModel`].
+        hidden_size (`int`, *optional*, defaults to 1024):
+            Dimension of the encoder layers and the pooler layer.
+        num_hidden_layers (`int`, *optional*, defaults to 24):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 16):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        intermediate_size (`int`, *optional*, defaults to 4096):
+            Dimension 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. If string, `"gelu"`,
+            `"relu"`, `"selu"` and `"gelu_new"` are supported.
+        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 1024):
+            The maximum sequence length that this model might ever be used with. Typically set this to something large
+            just in case (e.g., 512 or 1024 or 2048).
+        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.
+        scale_embedding (`bool`, *optional*, defaults to `True`):
+            Scale embeddings by diving by sqrt(d_model).
+        use_cache (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should return the last key/values attentions (not used by all models). Only
+            relevant if `config.is_decoder=True`.
+        layerdrop (`float`, *optional*, defaults to 0.0):
+            Please refer to the paper about LayerDrop: https://arxiv.org/abs/1909.11556 for further details
+        activation_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout ratio for activations inside the fully connected layer.
+        pad_token_id (`int`, *optional*, defaults to 1):
+            Padding token id.
+        bos_token_id (`int`, *optional*, defaults to 0):
+            Beginning of stream token id.
+        eos_token_id (`int`, *optional*, defaults to 2):
+            End of stream token id.
+
+    Example:
+
+    ```python
+    >>> from transformers import BioGptModel, BioGptConfig
+
+    >>> # Initializing a BioGPT microsoft/biogpt style configuration
+    >>> configuration = BioGptConfig()
+
+    >>> # Initializing a model from the microsoft/biogpt style configuration
+    >>> model = BioGptModel(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "biogpt"
+
+    def __init__(
+        self,
+        vocab_size=42384,
+        hidden_size=1024,
+        num_hidden_layers=24,
+        num_attention_heads=16,
+        intermediate_size=4096,
+        hidden_act="gelu",
+        hidden_dropout_prob=0.1,
+        attention_probs_dropout_prob=0.1,
+        max_position_embeddings=1024,
+        initializer_range=0.02,
+        layer_norm_eps=1e-12,
+        scale_embedding=True,
+        use_cache=True,
+        layerdrop=0.0,
+        activation_dropout=0.0,
+        pad_token_id=1,
+        bos_token_id=0,
+        eos_token_id=2,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        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.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.scale_embedding = scale_embedding
+        self.use_cache = use_cache
+        self.layerdrop = layerdrop
+        self.activation_dropout = activation_dropout
+        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
+
+__all__ = ['BioGptConfig']