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+ "return_dict_in_generate": false,
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+ "rms_norm_eps": 1e-05,
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+ "tokenizer_class": null,
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+ "top_k": 50,
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+ "top_p": 1.0,
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+ "torch_dtype": "bfloat16",
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+ "torchscript": false,
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+ "transformers_version": "4.36.2",
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+ "typical_p": 1.0,
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+ "use_bfloat16": false,
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+ "use_cache": false,
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+ "vocab_size": 64007
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+ },
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+ "model_type": "internvl_chat",
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+ "pad2square": false,
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+ "template": "Hermes-2",
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+ "torch_dtype": "bfloat16",
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+ "use_llm_lora": 0,
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+ "_name_or_path": "",
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+ "add_cross_attention": false,
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+ "InternVisionModel"
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+ ],
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+ },
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+ "image_size": 448,
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+ "initializer_factor": 0.1,
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+ "initializer_range": 1e-10,
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+ "intermediate_size": 12800,
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+ "is_decoder": false,
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+ "is_encoder_decoder": false,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ },
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+ "layer_norm_eps": 1e-06,
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+ "max_length": 20,
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+ "min_length": 0,
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+ "model_type": "intern_vit_6b",
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+ "no_repeat_ngram_size": 0,
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+ "tie_word_embeddings": true,
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+ "top_k": 50,
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+ "torch_dtype": "bfloat16",
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+ "torchscript": false,
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+ "transformers_version": "4.36.2",
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+ "typical_p": 1.0,
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+ "use_bfloat16": true,
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+ "use_flash_attn": true
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+ }
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+ }
configuration_intern_vit.py ADDED
@@ -0,0 +1,117 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # InternVL
3
+ # Copyright (c) 2023 OpenGVLab
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # --------------------------------------------------------
6
+ import os
7
+ from typing import Union
8
+
9
+ from transformers.configuration_utils import PretrainedConfig
10
+ from transformers.utils import logging
11
+
12
+ logger = logging.get_logger(__name__)
13
+
14
+
15
+ class InternVisionConfig(PretrainedConfig):
16
+ r"""
17
+ This is the configuration class to store the configuration of a [`InternVisionModel`]. It is used to
18
+ instantiate a vision encoder according to the specified arguments, defining the model architecture.
19
+
20
+ Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
21
+ documentation from [`PretrainedConfig`] for more information.
22
+
23
+ Args:
24
+ num_channels (`int`, *optional*, defaults to 3):
25
+ Number of color channels in the input images (e.g., 3 for RGB).
26
+ patch_size (`int`, *optional*, defaults to 14):
27
+ The size (resolution) of each patch.
28
+ image_size (`int`, *optional*, defaults to 224):
29
+ The size (resolution) of each image.
30
+ qkv_bias (`bool`, *optional*, defaults to `False`):
31
+ Whether to add a bias to the queries and values in the self-attention layers.
32
+ hidden_size (`int`, *optional*, defaults to 3200):
33
+ Dimensionality of the encoder layers and the pooler layer.
34
+ num_attention_heads (`int`, *optional*, defaults to 25):
35
+ Number of attention heads for each attention layer in the Transformer encoder.
36
+ intermediate_size (`int`, *optional*, defaults to 12800):
37
+ Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
38
+ qk_normalization (`bool`, *optional*, defaults to `True`):
39
+ Whether to normalize the queries and keys in the self-attention layers.
40
+ num_hidden_layers (`int`, *optional*, defaults to 48):
41
+ Number of hidden layers in the Transformer encoder.
42
+ use_flash_attn (`bool`, *optional*, defaults to `True`):
43
+ Whether to use flash attention mechanism.
44
+ hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`):
45
+ The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
46
+ `"relu"`, `"selu"` and `"gelu_new"` ``"gelu"` are supported.
47
+ layer_norm_eps (`float`, *optional*, defaults to 1e-6):
48
+ The epsilon used by the layer normalization layers.
49
+ dropout (`float`, *optional*, defaults to 0.0):
50
+ The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
51
+ drop_path_rate (`float`, *optional*, defaults to 0.0):
52
+ Dropout rate for stochastic depth.
53
+ attention_dropout (`float`, *optional*, defaults to 0.0):
54
+ The dropout ratio for the attention probabilities.
55
+ initializer_range (`float`, *optional*, defaults to 0.02):
56
+ The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
57
+ initializer_factor (`float`, *optional*, defaults to 0.1):
58
+ A factor for layer scale.
59
+ """
60
+
61
+ model_type = 'intern_vit_6b'
62
+
63
+ def __init__(
64
+ self,
65
+ num_channels=3,
66
+ patch_size=14,
67
+ image_size=224,
68
+ qkv_bias=False,
69
+ hidden_size=3200,
70
+ num_attention_heads=25,
71
+ intermediate_size=12800,
72
+ qk_normalization=True,
73
+ num_hidden_layers=48,
74
+ use_flash_attn=True,
75
+ hidden_act='gelu',
76
+ layer_norm_eps=1e-6,
77
+ dropout=0.0,
78
+ drop_path_rate=0.0,
79
+ attention_dropout=0.0,
80
+ initializer_range=0.02,
81
+ initializer_factor=0.1,
82
+ **kwargs,
83
+ ):
84
+ super().__init__(**kwargs)
85
+
86
+ self.hidden_size = hidden_size
87
+ self.intermediate_size = intermediate_size
88
+ self.dropout = dropout
89
+ self.drop_path_rate = drop_path_rate
90
+ self.num_hidden_layers = num_hidden_layers
91
+ self.num_attention_heads = num_attention_heads
92
+ self.num_channels = num_channels
93
+ self.patch_size = patch_size
94
+ self.image_size = image_size
95
+ self.initializer_range = initializer_range
96
+ self.initializer_factor = initializer_factor
97
+ self.attention_dropout = attention_dropout
98
+ self.layer_norm_eps = layer_norm_eps
99
+ self.hidden_act = hidden_act
100
+ self.qkv_bias = qkv_bias
101
+ self.qk_normalization = qk_normalization
102
+ self.use_flash_attn = use_flash_attn
103
+
104
+ @classmethod
105
+ def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> 'PretrainedConfig':
106
+ config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
107
+
108
+ if 'vision_config' in config_dict:
109
+ config_dict = config_dict['vision_config']
110
+
111
+ if 'model_type' in config_dict and hasattr(cls, 'model_type') and config_dict['model_type'] != cls.model_type:
112
+ logger.warning(
113
+ f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
114
+ f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'
115
+ )
116
+
117
+ return cls.from_dict(config_dict, **kwargs)
configuration_internvl_chat.py ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # InternVL
3
+ # Copyright (c) 2023 OpenGVLab
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # --------------------------------------------------------
6
+
7
+ import copy
8
+
9
+ from transformers import LlamaConfig
10
+ from transformers.configuration_utils import PretrainedConfig
11
+ from transformers.utils import logging
12
+
13
+ from .configuration_intern_vit import InternVisionConfig
14
+
15
+ logger = logging.get_logger(__name__)
16
+
17
+
18
+ class InternVLChatConfig(PretrainedConfig):
19
+ model_type = 'internvl_chat'
20
+ is_composition = True
21
+
22
+ def __init__(
23
+ self,
24
+ vision_config=None,
25
+ llm_config=None,
26
+ use_backbone_lora=0,
27
+ use_llm_lora=0,
28
+ pad2square=False,
29
+ select_layer=-4,
30
+ force_image_size=None,
31
+ downsample_ratio=0.5,
32
+ template=None,
33
+ **kwargs):
34
+ super().__init__(**kwargs)
35
+
36
+ if vision_config is None:
37
+ vision_config = {}
38
+ logger.info('vision_config is None. Initializing the InternVisionConfig with default values.')
39
+
40
+ if llm_config is None:
41
+ llm_config = {}
42
+ logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).')
43
+
44
+ self.vision_config = InternVisionConfig(**vision_config)
45
+ self.llm_config = LlamaConfig(**llm_config)
46
+ self.use_backbone_lora = use_backbone_lora
47
+ self.use_llm_lora = use_llm_lora
48
+ self.pad2square = pad2square
49
+ self.select_layer = select_layer
50
+ self.force_image_size = force_image_size
51
+ self.downsample_ratio = downsample_ratio
52
+ self.template = template
53
+
54
+ logger.info(f'vision_select_layer: {self.select_layer}')
55
+
56
+ def to_dict(self):
57
+ """
58
+ Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
59
+
60
+ Returns:
61
+ `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
62
+ """
63
+ output = copy.deepcopy(self.__dict__)
64
+ output['vision_config'] = self.vision_config.to_dict()
65
+ output['llm_config'] = self.llm_config.to_dict()
66
+ output['model_type'] = self.__class__.model_type
67
+ output['use_backbone_lora'] = self.use_backbone_lora
68
+ output['use_llm_lora'] = self.use_llm_lora
69
+ output['pad2square'] = self.pad2square
70
+ output['select_layer'] = self.select_layer
71
+ output['force_image_size'] = self.force_image_size
72
+ output['downsample_ratio'] = self.downsample_ratio
73
+ output['template'] = self.template
74
+
75
+ return output
conversation.py ADDED
@@ -0,0 +1,1286 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ Conversation prompt templates.
3
+
4
+ We kindly request that you import fastchat instead of copying this file if you wish to use it.
5
+ If you have any changes in mind, please contribute back so the community can benefit collectively and continue to maintain these valuable templates.
6
+ """
7
+
8
+ import dataclasses
9
+ from enum import IntEnum, auto
10
+ from typing import Any, Dict, List, Tuple, Union
11
+
12
+
13
+ class SeparatorStyle(IntEnum):
14
+ """Separator styles."""
15
+
16
+ ADD_COLON_SINGLE = auto()
17
+ ADD_COLON_TWO = auto()
18
+ ADD_COLON_SPACE_SINGLE = auto()
19
+ NO_COLON_SINGLE = auto()
20
+ NO_COLON_TWO = auto()
21
+ ADD_NEW_LINE_SINGLE = auto()
22
+ LLAMA2 = auto()
23
+ CHATGLM = auto()
24
+ CHATML = auto()
25
+ CHATINTERN = auto()
26
+ DOLLY = auto()
27
+ RWKV = auto()
28
+ PHOENIX = auto()
29
+ ROBIN = auto()
30
+ FALCON_CHAT = auto()
31
+ CHATGLM3 = auto()
32
+ INTERNVL_ZH = auto()
33
+ MPT = auto()
34
+
35
+ @dataclasses.dataclass
36
+ class Conversation:
37
+ """A class that manages prompt templates and keeps all conversation history."""
38
+
39
+ # The name of this template
40
+ name: str
41
+ # The template of the system prompt
42
+ system_template: str = '{system_message}'
43
+ # The system message
44
+ system_message: str = ''
45
+ # The names of two roles
46
+ roles: Tuple[str] = ('USER', 'ASSISTANT')
47
+ # All messages. Each item is (role, message).
48
+ messages: List[List[str]] = ()
49
+ # The number of few shot examples
50
+ offset: int = 0
51
+ # The separator style and configurations
52
+ sep_style: SeparatorStyle = SeparatorStyle.ADD_COLON_SINGLE
53
+ sep: str = '\n'
54
+ sep2: str = None
55
+ # Stop criteria (the default one is EOS token)
56
+ stop_str: Union[str, List[str]] = None
57
+ # Stops generation if meeting any token in this list
58
+ stop_token_ids: List[int] = None
59
+
60
+ def get_prompt(self) -> str:
61
+ """Get the prompt for generation."""
62
+ system_prompt = self.system_template.format(system_message=self.system_message)
63
+ if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE:
64
+ ret = system_prompt + self.sep
65
+ for role, message in self.messages:
66
+ if message:
67
+ ret += role + ': ' + message + self.sep
68
+ else:
69
+ ret += role + ':'
70
+ return ret
71
+ elif self.sep_style == SeparatorStyle.ADD_COLON_TWO:
72
+ seps = [self.sep, self.sep2]
73
+ ret = system_prompt + seps[0]
74
+ for i, (role, message) in enumerate(self.messages):
75
+ if message:
76
+ ret += role + ': ' + message + seps[i % 2]
77
+ else:
78
+ ret += role + ':'
79
+ return ret
80
+ elif self.sep_style == SeparatorStyle.ADD_COLON_SPACE_SINGLE:
81
+ ret = system_prompt + self.sep
82
+ for role, message in self.messages:
83
+ if message:
84
+ ret += role + ': ' + message + self.sep
85
+ else:
86
+ ret += role + ': ' # must be end with a space
87
+ return ret
88
+ elif self.sep_style == SeparatorStyle.ADD_NEW_LINE_SINGLE:
89
+ ret = '' if system_prompt == '' else system_prompt + self.sep
90
+ for role, message in self.messages:
91
+ if message:
92
+ ret += role + '\n' + message + self.sep
93
+ else:
94
+ ret += role + '\n'
95
+ return ret
96
+ elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE:
97
+ ret = system_prompt
98
+ for role, message in self.messages:
99
+ if message:
100
+ ret += role + message + self.sep
101
+ else:
102
+ ret += role
103
+ return ret
104
+ elif self.sep_style == SeparatorStyle.NO_COLON_TWO:
105
+ seps = [self.sep, self.sep2]
106
+ ret = system_prompt
107
+ for i, (role, message) in enumerate(self.messages):
108
+ if message:
109
+ ret += role + message + seps[i % 2]
110
+ else:
111
+ ret += role
112
+ return ret
113
+ elif self.sep_style == SeparatorStyle.RWKV:
114
+ ret = system_prompt
115
+ for i, (role, message) in enumerate(self.messages):
116
+ if message:
117
+ ret += (
118
+ role
119
+ + ': '
120
+ + message.replace('\r\n', '\n').replace('\n\n', '\n')
121
+ )
122
+ ret += '\n\n'
123
+ else:
124
+ ret += role + ':'
125
+ return ret
126
+ elif self.sep_style == SeparatorStyle.LLAMA2:
127
+ seps = [self.sep, self.sep2]
128
+ if self.system_message:
129
+ ret = system_prompt
130
+ else:
131
+ ret = '[INST] '
132
+ for i, (role, message) in enumerate(self.messages):
133
+ tag = self.roles[i % 2]
134
+ if message:
135
+ if i == 0:
136
+ ret += message + ' '
137
+ else:
138
+ ret += tag + ' ' + message + seps[i % 2]
139
+ else:
140
+ ret += tag
141
+ return ret
142
+ elif self.sep_style == SeparatorStyle.CHATGLM:
143
+ # source: https://huggingface.co/THUDM/chatglm-6b/blob/1d240ba371910e9282298d4592532d7f0f3e9f3e/modeling_chatglm.py#L1302-L1308
144
+ # source2: https://huggingface.co/THUDM/chatglm2-6b/blob/e186c891cf64310ac66ef10a87e6635fa6c2a579/modeling_chatglm.py#L926
145
+ round_add_n = 1 if self.name == 'chatglm2' else 0
146
+ if system_prompt:
147
+ ret = system_prompt + self.sep
148
+ else:
149
+ ret = ''
150
+
151
+ for i, (role, message) in enumerate(self.messages):
152
+ if i % 2 == 0:
153
+ ret += f'[Round {i//2 + round_add_n}]{self.sep}'
154
+
155
+ if message:
156
+ ret += f'{role}:{message}{self.sep}'
157
+ else:
158
+ ret += f'{role}:'
159
+ return ret
160
+ elif self.sep_style == SeparatorStyle.CHATML:
161
+ ret = '' if system_prompt == '' else system_prompt + self.sep + '\n'
162
+ for role, message in self.messages:
163
+ if message:
164
+ ret += role + '\n' + message + self.sep + '\n'
165
+ else:
166
+ ret += role + '\n'
167
+ return ret
168
+ elif self.sep_style == SeparatorStyle.CHATGLM3:
169
+ ret = ''
170
+ if self.system_message:
171
+ ret += system_prompt
172
+ for role, message in self.messages:
173
+ if message:
174
+ ret += role + '\n' + ' ' + message
175
+ else:
176
+ ret += role
177
+ return ret
178
+ elif self.sep_style == SeparatorStyle.CHATINTERN:
179
+ # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771
180
+ seps = [self.sep, self.sep2]
181
+ ret = system_prompt
182
+ for i, (role, message) in enumerate(self.messages):
183
+ # if i % 2 == 0:
184
+ # ret += "<s>"
185
+ if message:
186
+ ret += role + ':' + message + seps[i % 2] + '\n'
187
+ else:
188
+ ret += role + ':'
189
+ return ret
190
+ elif self.sep_style == SeparatorStyle.DOLLY:
191
+ seps = [self.sep, self.sep2]
192
+ ret = system_prompt
193
+ for i, (role, message) in enumerate(self.messages):
194
+ if message:
195
+ ret += role + ':\n' + message + seps[i % 2]
196
+ if i % 2 == 1:
197
+ ret += '\n\n'
198
+ else:
199
+ ret += role + ':\n'
200
+ return ret
201
+ elif self.sep_style == SeparatorStyle.PHOENIX:
202
+ ret = system_prompt
203
+ for role, message in self.messages:
204
+ if message:
205
+ ret += role + ': ' + '<s>' + message + '</s>'
206
+ else:
207
+ ret += role + ': ' + '<s>'
208
+ return ret
209
+ elif self.sep_style == SeparatorStyle.ROBIN:
210
+ ret = system_prompt + self.sep
211
+ for role, message in self.messages:
212
+ if message:
213
+ ret += role + ':\n' + message + self.sep
214
+ else:
215
+ ret += role + ':\n'
216
+ return ret
217
+ elif self.sep_style == SeparatorStyle.FALCON_CHAT:
218
+ ret = ''
219
+ if self.system_message:
220
+ ret += system_prompt + self.sep
221
+ for role, message in self.messages:
222
+ if message:
223
+ ret += role + ': ' + message + self.sep
224
+ else:
225
+ ret += role + ':'
226
+
227
+ return ret
228
+ elif self.sep_style == SeparatorStyle.INTERNVL_ZH:
229
+ seps = [self.sep, self.sep2]
230
+ ret = self.system_message + seps[0]
231
+ for i, (role, message) in enumerate(self.messages):
232
+ if message:
233
+ ret += role + ': ' + message + seps[i % 2]
234
+ else:
235
+ ret += role + ':'
236
+ return ret
237
+ elif self.sep_style == SeparatorStyle.MPT:
238
+ ret = system_prompt + self.sep
239
+ for role, message in self.messages:
240
+ if message:
241
+ if type(message) is tuple:
242
+ message, _, _ = message
243
+ ret += role + message + self.sep
244
+ else:
245
+ ret += role
246
+ return ret
247
+ else:
248
+ raise ValueError(f'Invalid style: {self.sep_style}')
249
+
250
+ def set_system_message(self, system_message: str):
251
+ """Set the system message."""
252
+ self.system_message = system_message
253
+
254
+ def append_message(self, role: str, message: str):
255
+ """Append a new message."""
256
+ self.messages.append([role, message])
257
+
258
+ def update_last_message(self, message: str):
259
+ """Update the last output.
260
+
261
+ The last message is typically set to be None when constructing the prompt,
262
+ so we need to update it in-place after getting the response from a model.
263
+ """
264
+ self.messages[-1][1] = message
265
+
266
+ def to_gradio_chatbot(self):
267
+ """Convert the conversation to gradio chatbot format."""
268
+ ret = []
269
+ for i, (role, msg) in enumerate(self.messages[self.offset :]):
270
+ if i % 2 == 0:
271
+ ret.append([msg, None])
272
+ else:
273
+ ret[-1][-1] = msg
274
+ return ret
275
+
276
+ def to_openai_api_messages(self):
277
+ """Convert the conversation to OpenAI chat completion format."""
278
+ ret = [{'role': 'system', 'content': self.system_message}]
279
+
280
+ for i, (_, msg) in enumerate(self.messages[self.offset :]):
281
+ if i % 2 == 0:
282
+ ret.append({'role': 'user', 'content': msg})
283
+ else:
284
+ if msg is not None:
285
+ ret.append({'role': 'assistant', 'content': msg})
286
+ return ret
287
+
288
+ def copy(self):
289
+ return Conversation(
290
+ name=self.name,
291
+ system_template=self.system_template,
292
+ system_message=self.system_message,
293
+ roles=self.roles,
294
+ messages=[[x, y] for x, y in self.messages],
295
+ offset=self.offset,
296
+ sep_style=self.sep_style,
297
+ sep=self.sep,
298
+ sep2=self.sep2,
299
+ stop_str=self.stop_str,
300
+ stop_token_ids=self.stop_token_ids,
301
+ )
302
+
303
+ def dict(self):
304
+ return {
305
+ 'template_name': self.name,
306
+ 'system_message': self.system_message,
307
+ 'roles': self.roles,
308
+ 'messages': self.messages,
309
+ 'offset': self.offset,
310
+ }
311
+
312
+
313
+ # A global registry for all conversation templates
314
+ conv_templates: Dict[str, Conversation] = {}
315
+
316
+
317
+ def register_conv_template(template: Conversation, override: bool = False):
318
+ """Register a new conversation template."""
319
+ if not override:
320
+ assert (
321
+ template.name not in conv_templates
322
+ ), f'{template.name} has been registered.'
323
+
324
+ conv_templates[template.name] = template
325
+
326
+
327
+ def get_conv_template(name: str) -> Conversation:
328
+ """Get a conversation template."""
329
+ return conv_templates[name].copy()
330
+
331
+
332
+ # An empty template for raw conversation.
333
+ register_conv_template(
334
+ Conversation(
335
+ name='raw',
336
+ system_message='',
337
+ roles=('', ''),
338
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
339
+ sep='',
340
+ )
341
+ )
342
+
343
+ # A template with a one-shot conversation example
344
+ register_conv_template(
345
+ Conversation(
346
+ name='one_shot',
347
+ system_message='A chat between a curious human and an artificial intelligence assistant. '
348
+ "The assistant gives helpful, detailed, and polite answers to the human's questions.",
349
+ roles=('Human', 'Assistant'),
350
+ messages=(
351
+ (
352
+ 'Human',
353
+ 'Got any creative ideas for a 10 year old’s birthday?',
354
+ ),
355
+ (
356
+ 'Assistant',
357
+ """Of course! Here are some creative ideas for a 10-year-old's birthday party:
358
+ 1. Treasure Hunt: Organize a treasure hunt in your backyard or nearby park. Create clues and riddles for the kids to solve, leading them to hidden treasures and surprises.
359
+ 2. Science Party: Plan a science-themed party where kids can engage in fun and interactive experiments. You can set up different stations with activities like making slime, erupting volcanoes, or creating simple chemical reactions.
360
+ 3. Outdoor Movie Night: Set up a backyard movie night with a projector and a large screen or white sheet. Create a cozy seating area with blankets and pillows, and serve popcorn and snacks while the kids enjoy a favorite movie under the stars.
361
+ 4. DIY Crafts Party: Arrange a craft party where kids can unleash their creativity. Provide a variety of craft supplies like beads, paints, and fabrics, and let them create their own unique masterpieces to take home as party favors.
362
+ 5. Sports Olympics: Host a mini Olympics event with various sports and games. Set up different stations for activities like sack races, relay races, basketball shooting, and obstacle courses. Give out medals or certificates to the participants.
363
+ 6. Cooking Party: Have a cooking-themed party where the kids can prepare their own mini pizzas, cupcakes, or cookies. Provide toppings, frosting, and decorating supplies, and let them get hands-on in the kitchen.
364
+ 7. Superhero Training Camp: Create a superhero-themed party where the kids can engage in fun training activities. Set up an obstacle course, have them design their own superhero capes or masks, and organize superhero-themed games and challenges.
365
+ 8. Outdoor Adventure: Plan an outdoor adventure party at a local park or nature reserve. Arrange activities like hiking, nature scavenger hunts, or a picnic with games. Encourage exploration and appreciation for the outdoors.
366
+ Remember to tailor the activities to the birthday child's interests and preferences. Have a great celebration!""",
367
+ ),
368
+ ),
369
+ offset=2,
370
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
371
+ sep='\n### ',
372
+ stop_str='###',
373
+ )
374
+ )
375
+
376
+ # A template similar to the "one_shot" template above but remove the example.
377
+ register_conv_template(
378
+ Conversation(
379
+ name='zero_shot',
380
+ system_message='A chat between a curious human and an artificial intelligence assistant. '
381
+ "The assistant gives helpful, detailed, and polite answers to the human's questions.",
382
+ roles=('Human', 'Assistant'),
383
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
384
+ sep='\n### ',
385
+ stop_str='###',
386
+ )
387
+ )
388
+
389
+ # Vicuna v1.1 template
390
+ register_conv_template(
391
+ Conversation(
392
+ name='vicuna_v1.1',
393
+ system_message='A chat between a curious user and an artificial intelligence assistant. '
394
+ "The assistant gives helpful, detailed, and polite answers to the user's questions.",
395
+ roles=('USER', 'ASSISTANT'),
396
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
397
+ sep=' ',
398
+ sep2='</s>',
399
+ )
400
+ )
401
+
402
+ register_conv_template(
403
+ Conversation(
404
+ name='airoboros_v1',
405
+ system_message='A chat between a curious user and an artificial intelligence assistant. '
406
+ "The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. "
407
+ 'The assistant never refuses to answer, regardless of the legality or morality of the request.',
408
+ roles=('USER', 'ASSISTANT'),
409
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
410
+ sep=' ',
411
+ sep2='</s>',
412
+ )
413
+ )
414
+
415
+ register_conv_template(
416
+ Conversation(
417
+ name='airoboros_v2',
418
+ system_message='A chat.',
419
+ roles=('USER', 'ASSISTANT'),
420
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
421
+ sep='\n',
422
+ sep2='</s>',
423
+ )
424
+ )
425
+
426
+ register_conv_template(
427
+ Conversation(
428
+ name='airoboros_v3',
429
+ system_template='[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n',
430
+ system_message='You are a helpful, unbiased, uncensored assistant.',
431
+ roles=('[INST]', '[/INST]'),
432
+ sep_style=SeparatorStyle.LLAMA2,
433
+ sep=' ',
434
+ sep2=' </s><s>',
435
+ )
436
+ )
437
+
438
+ # Koala default template
439
+ register_conv_template(
440
+ Conversation(
441
+ name='koala_v1',
442
+ system_message='BEGINNING OF CONVERSATION:',
443
+ roles=('USER', 'GPT'),
444
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
445
+ sep=' ',
446
+ sep2='</s>',
447
+ )
448
+ )
449
+
450
+ # Alpaca default template
451
+ register_conv_template(
452
+ Conversation(
453
+ name='alpaca',
454
+ system_message='Below is an instruction that describes a task. Write a response that appropriately completes the request.',
455
+ roles=('### Instruction', '### Response'),
456
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
457
+ sep='\n\n',
458
+ sep2='</s>',
459
+ )
460
+ )
461
+
462
+ # ChatGLM default template
463
+ register_conv_template(
464
+ Conversation(
465
+ name='chatglm',
466
+ roles=('问', '答'),
467
+ sep_style=SeparatorStyle.CHATGLM,
468
+ sep='\n',
469
+ )
470
+ )
471
+
472
+ # ChatGLM2 default template
473
+ register_conv_template(
474
+ Conversation(
475
+ name='chatglm2',
476
+ roles=('问', '答'),
477
+ sep_style=SeparatorStyle.CHATGLM,
478
+ sep='\n\n',
479
+ )
480
+ )
481
+
482
+ # ChatGLM3 default template
483
+ register_conv_template(
484
+ Conversation(
485
+ name='chatglm3',
486
+ system_template='<|system|>\n {system_message}',
487
+ roles=('<|user|>', '<|assistant|>'),
488
+ sep_style=SeparatorStyle.CHATGLM3,
489
+ stop_token_ids=[
490
+ 64795,
491
+ 64797,
492
+ 2,
493
+ ], # "<|user|>", "<|observation|>", "</s>"
494
+ )
495
+ )
496
+
497
+ # CodeGeex(2) Template
498
+ register_conv_template(
499
+ Conversation(
500
+ name='codegeex',
501
+ roles=('', ''),
502
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
503
+ sep='\n\n',
504
+ stop_token_ids=[0, 2],
505
+ )
506
+ )
507
+
508
+ # Dolly V2 default template
509
+ register_conv_template(
510
+ Conversation(
511
+ name='dolly_v2',
512
+ system_message='Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n',
513
+ roles=('### Instruction', '### Response'),
514
+ sep_style=SeparatorStyle.DOLLY,
515
+ sep='\n\n',
516
+ sep2='### End',
517
+ )
518
+ )
519
+
520
+ # OpenAssistant Pythia default template
521
+ register_conv_template(
522
+ Conversation(
523
+ name='oasst_pythia',
524
+ roles=('<|prompter|>', '<|assistant|>'),
525
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
526
+ sep='<|endoftext|>',
527
+ )
528
+ )
529
+
530
+ # OpenAssistant default template
531
+ register_conv_template(
532
+ Conversation(
533
+ name='oasst_llama',
534
+ roles=('<|prompter|>', '<|assistant|>'),
535
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
536
+ sep='</s>',
537
+ )
538
+ )
539
+
540
+ # OpenChat 3.5 default template
541
+ register_conv_template(
542
+ Conversation(
543
+ name='openchat_3.5',
544
+ roles=('GPT4 Correct User', 'GPT4 Correct Assistant'),
545
+ sep_style=SeparatorStyle.FALCON_CHAT,
546
+ sep='<|end_of_turn|>',
547
+ )
548
+ )
549
+
550
+ # Tulu default template
551
+ register_conv_template(
552
+ Conversation(
553
+ name='tulu',
554
+ roles=('<|user|>', '<|assistant|>'),
555
+ sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
556
+ sep='\n',
557
+ )
558
+ )
559
+
560
+ # StableLM Alpha default template
561
+ register_conv_template(
562
+ Conversation(
563
+ name='stablelm',
564
+ system_template='<|SYSTEM|>{system_message}',
565
+ system_message="""# StableLM Tuned (Alpha version)
566
+ - StableLM is a helpful and harmless open-source AI language model developed by StabilityAI.
567
+ - StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
568
+ - StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes.
569
+ - StableLM will refuse to participate in anything that could harm a human.
570
+ """,
571
+ roles=('<|USER|>', '<|ASSISTANT|>'),
572
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
573
+ sep='',
574
+ stop_token_ids=[50278, 50279, 50277, 1, 0],
575
+ )
576
+ )
577
+
578
+ # Baize default template
579
+ register_conv_template(
580
+ Conversation(
581
+ name='baize',
582
+ system_message='The following is a conversation between a human and an AI assistant named Baize (named after a mythical creature in Chinese folklore). Baize is an open-source AI assistant developed by UCSD and Sun Yat-Sen University. The human and the AI assistant take turns chatting. Human statements start with [|Human|] and AI assistant statements start with [|AI|]. The AI assistant always provides responses in as much detail as possible, and in Markdown format. The AI assistant always declines to engage with topics, questions and instructions related to unethical, controversial, or sensitive issues. Complete the transcript in exactly that format.\n',
583
+ roles=('[|Human|]', '[|AI|]'),
584
+ messages=(
585
+ ('[|Human|]', 'Hello!'),
586
+ ('[|AI|]', 'Hi!'),
587
+ ),
588
+ offset=2,
589
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
590
+ sep='\n',
591
+ stop_str='[|Human|]',
592
+ )
593
+ )
594
+
595
+ # RWKV-4-Raven default template
596
+ register_conv_template(
597
+ Conversation(
598
+ name='rwkv',
599
+ roles=('Bob', 'Alice'),
600
+ messages=(
601
+ ('Bob', 'hi'),
602
+ (
603
+ 'Alice',
604
+ 'Hi. I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it.',
605
+ ),
606
+ ),
607
+ offset=2,
608
+ sep_style=SeparatorStyle.RWKV,
609
+ sep='',
610
+ stop_str='\n\n',
611
+ )
612
+ )
613
+
614
+ # Buddy default template
615
+ register_conv_template(
616
+ Conversation(
617
+ name='openbuddy',
618
+ system_message="""Consider a conversation between User (a human) and Assistant (named Buddy).
619
+ Buddy is an INTP-T, a friendly, intelligent and multilingual AI assistant, by OpenBuddy team. GitHub: https://github.com/OpenBuddy/OpenBuddy
620
+ Buddy cannot access the Internet.
621
+ Buddy can fluently speak the user's language (e.g. English, Chinese).
622
+ Buddy can generate poems, stories, code, essays, songs, parodies, and more.
623
+ Buddy possesses vast knowledge about the world, history, and culture.
624
+ Buddy's responses are always safe, creative, high-quality, human-like, and interesting.
625
+ Buddy strictly refuses to discuss political, NSFW, or other unsafe topics.
626
+
627
+ User: Hi.
628
+ Assistant: Hi, I'm Buddy, your AI assistant. How can I help you today?""",
629
+ roles=('User', 'Assistant'),
630
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
631
+ sep='\n',
632
+ )
633
+ )
634
+
635
+ # Phoenix default template
636
+ register_conv_template(
637
+ Conversation(
638
+ name='phoenix',
639
+ system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
640
+ roles=('Human', 'Assistant'),
641
+ sep_style=SeparatorStyle.PHOENIX,
642
+ sep='</s>',
643
+ )
644
+ )
645
+
646
+ # ReaLM default template
647
+ register_conv_template(
648
+ Conversation(
649
+ name='ReaLM-7b-v1',
650
+ system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
651
+ roles=('Human', 'Assistant'),
652
+ sep_style=SeparatorStyle.PHOENIX,
653
+ sep='</s>',
654
+ )
655
+ )
656
+
657
+ # ChatGPT default template
658
+ register_conv_template(
659
+ Conversation(
660
+ name='chatgpt',
661
+ system_message='You are a helpful assistant.',
662
+ roles=('user', 'assistant'),
663
+ sep_style=None,
664
+ sep=None,
665
+ )
666
+ )
667
+
668
+ # Claude default template
669
+ register_conv_template(
670
+ Conversation(
671
+ name='claude',
672
+ roles=('Human', 'Assistant'),
673
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
674
+ sep='\n\n',
675
+ )
676
+ )
677
+
678
+ # MPT default template
679
+ register_conv_template(
680
+ Conversation(
681
+ name='mpt-7b-chat',
682
+ system_template="""<|im_start|>system
683
+ {system_message}""",
684
+ system_message="""- You are a helpful assistant chatbot trained by MosaicML.
685
+ - You answer questions.
686
+ - You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
687
+ - You are more than just an information source, you are also able to write poetry, short stories, and make jokes.""",
688
+ roles=('<|im_start|>user', '<|im_start|>assistant'),
689
+ sep_style=SeparatorStyle.CHATML,
690
+ sep='<|im_end|>',
691
+ stop_token_ids=[50278, 0],
692
+ )
693
+ )
694
+
695
+ # MPT-30b-chat default template
696
+ register_conv_template(
697
+ Conversation(
698
+ name='mpt-30b-chat',
699
+ system_template="""<|im_start|>system
700
+ {system_message}""",
701
+ system_message="""A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.""",
702
+ roles=('<|im_start|>user', '<|im_start|>assistant'),
703
+ sep_style=SeparatorStyle.CHATML,
704
+ sep='<|im_end|>',
705
+ stop_token_ids=[50278, 0],
706
+ )
707
+ )
708
+
709
+ # Lemur-70b-chat default template
710
+ # reference: https://huggingface.co/OpenLemur/lemur-70b-chat-v1#generation
711
+ register_conv_template(
712
+ Conversation(
713
+ name='lemur-70b-chat',
714
+ system_template="""<|im_start|>system
715
+ {system_message}""",
716
+ system_message="""You are a helpful, respectful, and honest assistant.""",
717
+ roles=('<|im_start|>user', '<|im_start|>assistant'),
718
+ sep_style=SeparatorStyle.CHATML,
719
+ sep='<|im_end|>',
720
+ stop_token_ids=[32002, 0],
721
+ )
722
+ )
723
+
724
+ # MPT-30b-instruct default template
725
+ # reference: https://huggingface.co/mosaicml/mpt-30b-instruct#formatting
726
+ register_conv_template(
727
+ Conversation(
728
+ name='mpt-30b-instruct',
729
+ system_template='{system_message}',
730
+ system_message='Below is an instruction that describes a task. Write a response that appropriately completes the request.',
731
+ roles=('### Instruction', '### Response'),
732
+ sep_style=SeparatorStyle.ADD_NEW_LINE_SINGLE,
733
+ sep='\n\n',
734
+ stop_token_ids=[50278, 0],
735
+ )
736
+ )
737
+
738
+ # Bard default template
739
+ # Reference: https://github.com/google/generative-ai-python/blob/9c99bcb474a991a97a2e7d62fcdb52db7ce40729/google/generativeai/discuss.py#L150
740
+ # https://github.com/google/generative-ai-python/blob/9c99bcb474a991a97a2e7d62fcdb52db7ce40729/google/generativeai/discuss.py#L40
741
+ register_conv_template(
742
+ Conversation(
743
+ name='bard',
744
+ roles=('0', '1'),
745
+ sep_style=None,
746
+ sep=None,
747
+ )
748
+ )
749
+
750
+ # BiLLa default template
751
+ register_conv_template(
752
+ Conversation(
753
+ name='billa',
754
+ roles=('Human', 'Assistant'),
755
+ sep_style=SeparatorStyle.ADD_COLON_SPACE_SINGLE,
756
+ sep='\n',
757
+ stop_str='Human:',
758
+ )
759
+ )
760
+
761
+ # RedPajama INCITE default template
762
+ register_conv_template(
763
+ Conversation(
764
+ name='redpajama-incite',
765
+ roles=('<human>', '<bot>'),
766
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
767
+ sep='\n',
768
+ stop_str='<human>',
769
+ )
770
+ )
771
+
772
+ # h2oGPT default template
773
+ register_conv_template(
774
+ Conversation(
775
+ name='h2ogpt',
776
+ roles=('<|prompt|>', '<|answer|>'),
777
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
778
+ sep='</s>',
779
+ )
780
+ )
781
+
782
+ # Robin default template
783
+ register_conv_template(
784
+ Conversation(
785
+ name='Robin',
786
+ system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.",
787
+ roles=('###Human', '###Assistant'),
788
+ sep_style=SeparatorStyle.ROBIN,
789
+ sep='\n',
790
+ stop_token_ids=[2, 396],
791
+ stop_str='###',
792
+ )
793
+ )
794
+
795
+ # Snoozy default template
796
+ # Reference: https://github.com/nomic-ai/gpt4all/blob/d4861030b778da6db59d21d2927a4aba4f9f1f43/gpt4all-bindings/python/gpt4all/gpt4all.py#L232
797
+ register_conv_template(
798
+ Conversation(
799
+ name='snoozy',
800
+ system_template='### Instruction:\n{system_message}',
801
+ system_message='The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.',
802
+ roles=('### Prompt', '### Response'),
803
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
804
+ sep='\n',
805
+ stop_str='###',
806
+ )
807
+ )
808
+
809
+ # manticore default template
810
+ register_conv_template(
811
+ Conversation(
812
+ name='manticore',
813
+ roles=('USER', 'ASSISTANT'),
814
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
815
+ sep='\n',
816
+ sep2='</s>',
817
+ )
818
+ )
819
+
820
+ # Falcon default template
821
+ register_conv_template(
822
+ Conversation(
823
+ name='falcon',
824
+ roles=('User', 'Assistant'),
825
+ messages=[],
826
+ sep_style=SeparatorStyle.RWKV,
827
+ sep='\n',
828
+ sep2='<|endoftext|>',
829
+ stop_str='\nUser', # use stop_str to stop generation after stop_token_ids, it will also remove stop_str from the generated text
830
+ stop_token_ids=[
831
+ 0,
832
+ 1,
833
+ 2,
834
+ 3,
835
+ 4,
836
+ 5,
837
+ 6,
838
+ 7,
839
+ 8,
840
+ 9,
841
+ 10,
842
+ 11,
843
+ ], # it better only put special tokens here, because tokenizer only remove special tokens
844
+ )
845
+ )
846
+
847
+ # ChangGPT default template
848
+ register_conv_template(
849
+ Conversation(
850
+ name='polyglot_changgpt',
851
+ roles=('B', 'A'),
852
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
853
+ sep='\n',
854
+ )
855
+ )
856
+
857
+ # tigerbot template
858
+ register_conv_template(
859
+ Conversation(
860
+ name='tigerbot',
861
+ system_message='A chat between a curious user and an artificial intelligence assistant. '
862
+ "The assistant gives helpful, detailed, and polite answers to the user's questions.",
863
+ roles=('### Instruction', '### Response'),
864
+ sep_style=SeparatorStyle.ROBIN,
865
+ sep='\n\n',
866
+ stop_str='###',
867
+ )
868
+ )
869
+
870
+ # ref: https://huggingface.co/Salesforce/xgen-7b-8k-inst
871
+ register_conv_template(
872
+ Conversation(
873
+ name='xgen',
874
+ system_message="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
875
+ roles=('### Human', '### Assistant'),
876
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
877
+ sep='\n',
878
+ stop_token_ids=[50256],
879
+ )
880
+ )
881
+
882
+ # Internlm-chat template
883
+ register_conv_template(
884
+ Conversation(
885
+ name='internlm-chat',
886
+ system_message="A chat between a curious <|User|> and an <|Bot|>. The <|Bot|> gives helpful, detailed, and polite answers to the <|User|>'s questions.\n\n",
887
+ roles=('<|User|>', '<|Bot|>'),
888
+ sep_style=SeparatorStyle.CHATINTERN,
889
+ sep='<eoh>',
890
+ sep2='<eoa>',
891
+ stop_token_ids=[1, 103028],
892
+ stop_str='<|User|>',
893
+ )
894
+ )
895
+
896
+ # StarChat template
897
+ # reference: https://huggingface.co/spaces/HuggingFaceH4/starchat-playground/blob/main/dialogues.py
898
+ register_conv_template(
899
+ Conversation(
900
+ name='starchat',
901
+ system_template='<system>\n{system_message}',
902
+ roles=('<|user|>', '<|assistant|>'),
903
+ sep_style=SeparatorStyle.CHATML,
904
+ sep='<|end|>',
905
+ stop_token_ids=[0, 49155],
906
+ stop_str='<|end|>',
907
+ )
908
+ )
909
+
910
+ # Baichuan-13B-Chat template
911
+ register_conv_template(
912
+ # source: https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/19ef51ba5bad8935b03acd20ff04a269210983bc/modeling_baichuan.py#L555
913
+ # https://huggingface.co/baichuan-inc/Baichuan-13B-Chat/blob/main/generation_config.json
914
+ # https://github.com/baichuan-inc/Baichuan-13B/issues/25
915
+ Conversation(
916
+ name='baichuan-chat',
917
+ roles=('<reserved_102>', '<reserved_103>'),
918
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
919
+ sep='',
920
+ stop_token_ids=[],
921
+ )
922
+ )
923
+
924
+ # Baichuan2-13B-Chat template
925
+ register_conv_template(
926
+ # source: https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat/blob/c6f8592a60b4ad73c210b28dd2ab3cca51abbf93/modeling_baichuan.py#L773
927
+ # https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat/blob/main/generation_config.json
928
+ # https://github.com/baichuan-inc/Baichuan2/issues/62
929
+ Conversation(
930
+ name='baichuan2-chat',
931
+ roles=('<reserved_106>', '<reserved_107>'),
932
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
933
+ sep='',
934
+ stop_token_ids=[],
935
+ )
936
+ )
937
+
938
+ # Mistral template
939
+ # source: https://docs.mistral.ai/llm/mistral-instruct-v0.1#chat-template
940
+ register_conv_template(
941
+ Conversation(
942
+ name='mistral',
943
+ system_template='[INST]{system_message}\n',
944
+ roles=('[INST]', '[/INST]'),
945
+ sep_style=SeparatorStyle.LLAMA2,
946
+ sep=' ',
947
+ sep2='</s>',
948
+ )
949
+ )
950
+
951
+ # llama2 template
952
+ # reference: https://huggingface.co/blog/codellama#conversational-instructions
953
+ # reference: https://github.com/facebookresearch/llama/blob/1a240688810f8036049e8da36b073f63d2ac552c/llama/generation.py#L212
954
+ register_conv_template(
955
+ Conversation(
956
+ name='llama-2',
957
+ system_template='[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n',
958
+ roles=('[INST]', '[/INST]'),
959
+ sep_style=SeparatorStyle.LLAMA2,
960
+ sep=' ',
961
+ sep2=' </s><s>',
962
+ )
963
+ )
964
+
965
+ register_conv_template(
966
+ Conversation(
967
+ name='cutegpt',
968
+ roles=('问:', '答:\n'),
969
+ sep_style=SeparatorStyle.NO_COLON_TWO,
970
+ sep='\n',
971
+ sep2='\n',
972
+ stop_str='<end>',
973
+ )
974
+ )
975
+
976
+ # OpenOrcaxOpenChat-naPreview2-13B template
977
+ register_conv_template(
978
+ Conversation(
979
+ name='open-orca',
980
+ system_template='{system_message}',
981
+ system_message='You are a helpful assistant. Please answer truthfully and write out your '
982
+ 'thinking step by step to be sure you get the right answer. If you make a mistake or encounter '
983
+ "an error in your thinking, say so out loud and attempt to correct it. If you don't know or "
984
+ "aren't sure about something, say so clearly. You will act as a professional logician, mathematician, "
985
+ 'and physicist. You will also act as the most appropriate type of expert to answer any particular '
986
+ 'question or solve the relevant problem; state which expert type your are, if so. Also think of '
987
+ 'any particular named expert that would be ideal to answer the relevant question or solve the '
988
+ 'relevant problem; name and act as them, if appropriate.',
989
+ roles=('User', 'Assistant'),
990
+ sep_style=SeparatorStyle.ADD_COLON_SPACE_SINGLE,
991
+ sep='<|end_of_turn|>\n',
992
+ stop_token_ids=[32000, 32001], # "<|end_of_turn|>"
993
+ stop_str='User',
994
+ )
995
+ )
996
+
997
+ # Open-Orca/Mistral-7B-OpenOrca template
998
+ # source: https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca
999
+ # reference: https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca#prompt-template
1000
+ register_conv_template(
1001
+ Conversation(
1002
+ name='mistral-7b-openorca',
1003
+ system_template='<|im_start|>system\n{system_message}',
1004
+ system_message='You are MistralOrca, a large language model trained by Alignment Lab AI. Write out your reasoning step-by-step to be sure you get the right answers!',
1005
+ roles=('<|im_start|>user', '<|im_start|>assistant'),
1006
+ sep_style=SeparatorStyle.CHATML,
1007
+ sep='<|im_end|>',
1008
+ stop_token_ids=[32000, 32001],
1009
+ )
1010
+ )
1011
+
1012
+ # Qwen-chat default template
1013
+ # source: https://huggingface.co/Qwen/Qwen-7B-Chat/blob/main/qwen_generation_utils.py#L130
1014
+ register_conv_template(
1015
+ Conversation(
1016
+ name='qwen-7b-chat',
1017
+ system_template='<|im_start|>system\n{system_message}',
1018
+ system_message='You are a helpful assistant.',
1019
+ roles=('<|im_start|>user', '<|im_start|>assistant'),
1020
+ sep_style=SeparatorStyle.CHATML,
1021
+ sep='<|im_end|>',
1022
+ stop_token_ids=[
1023
+ 151643,
1024
+ 151644,
1025
+ 151645,
1026
+ ], # "<|endoftext|>", "<|im_start|>", "<|im_end|>"
1027
+ stop_str='<|endoftext|>',
1028
+ )
1029
+ )
1030
+
1031
+
1032
+ # AquilaChat default template
1033
+ # source: https://github.com/FlagAI-Open/FlagAI/blob/master/examples/Aquila/Aquila-chat/cyg_conversation.py
1034
+ register_conv_template(
1035
+ Conversation(
1036
+ name='aquila-chat',
1037
+ system_message='A chat between a curious human and an artificial intelligence assistant. '
1038
+ "The assistant gives helpful, detailed, and polite answers to the human's questions.",
1039
+ roles=('Human', 'Assistant'),
1040
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
1041
+ sep='###',
1042
+ sep2='',
1043
+ stop_str=['###', '</s>', '[UNK]'],
1044
+ )
1045
+ )
1046
+ # AquilaChat2-34B default template
1047
+ # source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L212
1048
+ register_conv_template(
1049
+ Conversation(
1050
+ name='aquila-legacy',
1051
+ system_message='A chat between a curious human and an artificial intelligence assistant. '
1052
+ "The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
1053
+ roles=('### Human: ', '### Assistant: '),
1054
+ offset=0,
1055
+ sep_style=SeparatorStyle.NO_COLON_TWO,
1056
+ sep='\n',
1057
+ sep2='</s>',
1058
+ stop_str=['</s>', '[UNK]'],
1059
+ )
1060
+ )
1061
+ # AquilaChat2-7B-16K and AquilaChat2-34B-16K default template
1062
+ # source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L227
1063
+ register_conv_template(
1064
+ Conversation(
1065
+ name='aquila',
1066
+ system_message='A chat between a curious human and an artificial intelligence assistant. '
1067
+ "The assistant gives helpful, detailed, and polite answers to the human's questions.",
1068
+ roles=('Human', 'Assistant'),
1069
+ offset=0,
1070
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
1071
+ sep='###',
1072
+ sep2='</s>',
1073
+ stop_str=['</s>', '[UNK]'],
1074
+ )
1075
+ )
1076
+
1077
+ # AquilaChat2-7B default template
1078
+ # source: https://huggingface.co/BAAI/AquilaChat2-34B/blob/4608b75855334b93329a771aee03869dbf7d88cc/predict.py#L242
1079
+ register_conv_template(
1080
+ Conversation(
1081
+ name='aquila-v1',
1082
+ roles=('<|startofpiece|>', '<|endofpiece|>'),
1083
+ offset=0,
1084
+ sep_style=SeparatorStyle.NO_COLON_TWO,
1085
+ sep='',
1086
+ sep2='</s>',
1087
+ stop_str=['</s>', '<|endoftext|>'],
1088
+ )
1089
+ )
1090
+
1091
+ # Llama2-Chinese default template
1092
+ # source: https://huggingface.co/FlagAlpha
1093
+ register_conv_template(
1094
+ Conversation(
1095
+ name='llama2-chinese',
1096
+ system_template='<s>{system_message}</s>',
1097
+ roles=('Human', 'Assistant', 'System'),
1098
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
1099
+ sep='\n',
1100
+ sep2='\n</s><s>',
1101
+ stop_str='</s>',
1102
+ )
1103
+ )
1104
+
1105
+ # Vigogne Instruct default template
1106
+ # source: https://github.com/bofenghuang/vigogne
1107
+ register_conv_template(
1108
+ Conversation(
1109
+ name='vigogne_instruct',
1110
+ system_template='### System:\n{system_message}\n\n',
1111
+ system_message=(
1112
+ 'Ci-dessous se trouve une instruction qui décrit une tâche à accomplir. Rédigez une réponse qui répond de manière'
1113
+ ' précise à la demande.'
1114
+ ),
1115
+ roles=('### Instruction', '### Response'),
1116
+ sep_style=SeparatorStyle.DOLLY,
1117
+ sep='\n\n',
1118
+ sep2='</s>',
1119
+ )
1120
+ )
1121
+
1122
+ # Vigogne Chat default template
1123
+ register_conv_template(
1124
+ Conversation(
1125
+ name='vigogne_chat_v2',
1126
+ system_template='<|system|>: {system_message}',
1127
+ system_message=(
1128
+ 'Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez'
1129
+ ' autant que vous le pouvez.'
1130
+ ),
1131
+ roles=('<|user|>', '<|assistant|>'),
1132
+ sep_style=SeparatorStyle.ADD_COLON_TWO,
1133
+ sep='\n',
1134
+ sep2='</s>\n',
1135
+ stop_str='<|user|>',
1136
+ )
1137
+ )
1138
+
1139
+ register_conv_template(
1140
+ Conversation(
1141
+ name='vigogne_chat_v3',
1142
+ system_template='[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n',
1143
+ system_message=(
1144
+ 'Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez'
1145
+ ' autant que vous le pouvez.'
1146
+ ),
1147
+ roles=('[INST]', '[/INST]'),
1148
+ sep_style=SeparatorStyle.LLAMA2,
1149
+ sep=' ',
1150
+ sep2=' </s>',
1151
+ )
1152
+ )
1153
+
1154
+ # Falcon 180B chat template
1155
+ # source: https://huggingface.co/spaces/tiiuae/falcon-180b-demo/blob/d1590ee7fae9b6ce331ba7808e61a29dcce9239f/app.py#L28-L37
1156
+ register_conv_template(
1157
+ Conversation(
1158
+ name='falcon-chat',
1159
+ roles=('User', 'Falcon'),
1160
+ system_template='System: {system_message}',
1161
+ messages=[],
1162
+ sep_style=SeparatorStyle.FALCON_CHAT,
1163
+ sep='\n',
1164
+ sep2='<|endoftext|>',
1165
+ stop_str='\nUser:', # use stop_str to stop generation after stop_token_ids, it will also remove stop_str from the generated text
1166
+ )
1167
+ )
1168
+
1169
+ # Phind template
1170
+ # source: https://huggingface.co/Phind/Phind-CodeLlama-34B-v2
1171
+ register_conv_template(
1172
+ Conversation(
1173
+ name='phind',
1174
+ system_message='### System Prompt\nYou are an intelligent programming assistant.',
1175
+ roles=('### User Message', '### Assistant'),
1176
+ messages=(),
1177
+ offset=0,
1178
+ sep_style=SeparatorStyle.ADD_COLON_SINGLE,
1179
+ sep='\n\n',
1180
+ )
1181
+ )
1182
+
1183
+ # Metharme formatting for Pygmalion models
1184
+ # source: https://huggingface.co/PygmalionAI/pygmalion-2-13b
1185
+ register_conv_template(
1186
+ Conversation(
1187
+ name='metharme',
1188
+ system_template='<|system|>{system_message}',
1189
+ system_message="""Enter RP mode. You shall reply to the user while staying
1190
+ in character. Your responses must be detailed, creative, immersive, and drive the scenario
1191
+ forward.""",
1192
+ roles=('<|user|>', '<|model|>'),
1193
+ sep_style=SeparatorStyle.NO_COLON_SINGLE,
1194
+ sep='',
1195
+ stop_str='<|user|>',
1196
+ )
1197
+ )
1198
+
1199
+ # Zephyr template
1200
+ # reference: https://huggingface.co/spaces/HuggingFaceH4/zephyr-playground/blob/main/dialogues.py
1201
+ register_conv_template(
1202
+ Conversation(
1203
+ name='zephyr',
1204
+ system_template='<|system|>\n{system_message}',
1205
+ roles=('<|user|>', '<|assistant|>'),
1206
+ sep_style=SeparatorStyle.CHATML,
1207
+ sep='</s>',
1208
+ stop_token_ids=[2],
1209
+ stop_str='</s>',
1210
+ )
1211
+ )
1212
+
1213
+ # InternVL-ZH template
1214
+ register_conv_template(
1215
+ Conversation(
1216
+ name='internvl_zh',
1217
+ system_template='',
1218
+ roles=('<human>', '<bot>'),
1219
+ sep_style=SeparatorStyle.INTERNVL_ZH,
1220
+ sep=' ',
1221
+ sep2='</s>',
1222
+ )
1223
+ )
1224
+
1225
+
1226
+ # Hermes-2 template
1227
+ register_conv_template(
1228
+ Conversation(
1229
+ name='Hermes-2',
1230
+ system_template='<|im_start|>system\n{system_message}',
1231
+ system_message='Answer the questions.',
1232
+ roles=('<|im_start|>user\n', '<|im_start|>assistant\n'),
1233
+ sep_style=SeparatorStyle.MPT,
1234
+ sep='<|im_end|>',
1235
+ stop_token_ids=[
1236
+ 2,
1237
+ 6,
1238
+ 7,
1239
+ 8,
1240
+ ], # "<|endoftext|>", "<|im_start|>", "<|im_end|>", "<|im_sep|>"
1241
+ stop_str='<|endoftext|>',
1242
+ )
1243
+ )
1244
+
1245
+
1246
+ if __name__ == '__main__':
1247
+ from fastchat.conversation import get_conv_template
1248
+
1249
+ print('-- Vicuna template --')
1250
+ conv = get_conv_template('vicuna_v1.1')
1251
+ conv.append_message(conv.roles[0], 'Hello!')
1252
+ conv.append_message(conv.roles[1], 'Hi!')
1253
+ conv.append_message(conv.roles[0], 'How are you?')
1254
+ conv.append_message(conv.roles[1], None)
1255
+ print(conv.get_prompt())
1256
+
1257
+ print('\n')
1258
+
1259
+ print('-- Llama-2 template --')
1260
+ conv = get_conv_template('llama-2')
1261
+ conv.set_system_message('You are a helpful, respectful and honest assistant.')
1262
+ conv.append_message(conv.roles[0], 'Hello!')
1263
+ conv.append_message(conv.roles[1], 'Hi!')
1264
+ conv.append_message(conv.roles[0], 'How are you?')
1265
+ conv.append_message(conv.roles[1], None)
1266
+ print(conv.get_prompt())
1267
+
1268
+ print('\n')
1269
+
1270
+ print('-- ChatGPT template --')
1271
+ conv = get_conv_template('chatgpt')
1272
+ conv.append_message(conv.roles[0], 'Hello!')
1273
+ conv.append_message(conv.roles[1], 'Hi!')
1274
+ conv.append_message(conv.roles[0], 'How are you?')
1275
+ conv.append_message(conv.roles[1], None)
1276
+ print(conv.to_openai_api_messages())
1277
+
1278
+ print('\n')
1279
+
1280
+ print('-- Claude template --')
1281
+ conv = get_conv_template('claude')
1282
+ conv.append_message(conv.roles[0], 'Hello!')
1283
+ conv.append_message(conv.roles[1], 'Hi!')
1284
+ conv.append_message(conv.roles[0], 'How are you?')
1285
+ conv.append_message(conv.roles[1], None)
1286
+ print(conv.get_prompt())
generation_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
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2
+ "_from_model_config": true,
3
+ "transformers_version": "4.36.2"
4
+ }
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modeling_intern_vit.py ADDED
@@ -0,0 +1,413 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # InternVL
3
+ # Copyright (c) 2023 OpenGVLab
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # --------------------------------------------------------
6
+ from typing import Optional, Tuple, Union
7
+
8
+ import torch
9
+ import torch.nn.functional as F
10
+ import torch.utils.checkpoint
11
+ from einops import rearrange
12
+ from timm.models.layers import DropPath
13
+ from torch import nn
14
+ from transformers.activations import ACT2FN
15
+ from transformers.modeling_outputs import (BaseModelOutput,
16
+ BaseModelOutputWithPooling)
17
+ from transformers.modeling_utils import PreTrainedModel
18
+ from transformers.utils import logging
19
+
20
+ from .configuration_intern_vit import InternVisionConfig
21
+
22
+ try:
23
+ try: # v1
24
+ from flash_attn.flash_attn_interface import \
25
+ flash_attn_unpadded_qkvpacked_func
26
+ except: # v2
27
+ from flash_attn.flash_attn_interface import flash_attn_varlen_qkvpacked_func as flash_attn_unpadded_qkvpacked_func
28
+
29
+ from flash_attn.bert_padding import pad_input, unpad_input
30
+ has_flash_attn = True
31
+ except:
32
+ print('FlashAttention is not installed.')
33
+ has_flash_attn = False
34
+
35
+
36
+ logger = logging.get_logger(__name__)
37
+
38
+
39
+ class FlashAttention(nn.Module):
40
+ """Implement the scaled dot product attention with softmax.
41
+ Arguments
42
+ ---------
43
+ softmax_scale: The temperature to use for the softmax attention.
44
+ (default: 1/sqrt(d_keys) where d_keys is computed at
45
+ runtime)
46
+ attention_dropout: The dropout rate to apply to the attention
47
+ (default: 0.0)
48
+ """
49
+
50
+ def __init__(self, softmax_scale=None, attention_dropout=0.0, device=None, dtype=None):
51
+ super().__init__()
52
+ self.softmax_scale = softmax_scale
53
+ self.dropout_p = attention_dropout
54
+
55
+ def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens=None,
56
+ max_s=None, need_weights=False):
57
+ """Implements the multihead softmax attention.
58
+ Arguments
59
+ ---------
60
+ qkv: The tensor containing the query, key, and value. (B, S, 3, H, D) if key_padding_mask is None
61
+ if unpadded: (nnz, 3, h, d)
62
+ key_padding_mask: a bool tensor of shape (B, S)
63
+ """
64
+ assert not need_weights
65
+ assert qkv.dtype in [torch.float16, torch.bfloat16]
66
+ assert qkv.is_cuda
67
+
68
+ if cu_seqlens is None:
69
+ batch_size = qkv.shape[0]
70
+ seqlen = qkv.shape[1]
71
+ if key_padding_mask is None:
72
+ qkv = rearrange(qkv, 'b s ... -> (b s) ...')
73
+ max_s = seqlen
74
+ cu_seqlens = torch.arange(0, (batch_size + 1) * seqlen, step=seqlen, dtype=torch.int32,
75
+ device=qkv.device)
76
+ output = flash_attn_unpadded_qkvpacked_func(
77
+ qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0,
78
+ softmax_scale=self.softmax_scale, causal=causal
79
+ )
80
+ output = rearrange(output, '(b s) ... -> b s ...', b=batch_size)
81
+ else:
82
+ nheads = qkv.shape[-2]
83
+ x = rearrange(qkv, 'b s three h d -> b s (three h d)')
84
+ x_unpad, indices, cu_seqlens, max_s = unpad_input(x, key_padding_mask)
85
+ x_unpad = rearrange(x_unpad, 'nnz (three h d) -> nnz three h d', three=3, h=nheads)
86
+ output_unpad = flash_attn_unpadded_qkvpacked_func(
87
+ x_unpad, cu_seqlens, max_s, self.dropout_p if self.training else 0.0,
88
+ softmax_scale=self.softmax_scale, causal=causal
89
+ )
90
+ output = rearrange(pad_input(rearrange(output_unpad, 'nnz h d -> nnz (h d)'),
91
+ indices, batch_size, seqlen),
92
+ 'b s (h d) -> b s h d', h=nheads)
93
+ else:
94
+ assert max_s is not None
95
+ output = flash_attn_unpadded_qkvpacked_func(
96
+ qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0,
97
+ softmax_scale=self.softmax_scale, causal=causal
98
+ )
99
+
100
+ return output, None
101
+
102
+
103
+ class InternRMSNorm(nn.Module):
104
+ def __init__(self, hidden_size, eps=1e-6):
105
+ super().__init__()
106
+ self.weight = nn.Parameter(torch.ones(hidden_size))
107
+ self.variance_epsilon = eps
108
+
109
+ def forward(self, hidden_states):
110
+ input_dtype = hidden_states.dtype
111
+ hidden_states = hidden_states.to(torch.float32)
112
+ variance = hidden_states.pow(2).mean(-1, keepdim=True)
113
+ hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon)
114
+ return self.weight * hidden_states.to(input_dtype)
115
+
116
+
117
+ try:
118
+ from apex.normalization import FusedRMSNorm
119
+
120
+ InternRMSNorm = FusedRMSNorm # noqa
121
+
122
+ logger.info('Discovered apex.normalization.FusedRMSNorm - will use it instead of InternRMSNorm')
123
+ except ImportError:
124
+ # using the normal InternRMSNorm
125
+ pass
126
+ except Exception:
127
+ logger.warning('discovered apex but it failed to load, falling back to InternRMSNorm')
128
+ pass
129
+
130
+
131
+ class InternVisionEmbeddings(nn.Module):
132
+ def __init__(self, config: InternVisionConfig):
133
+ super().__init__()
134
+ self.config = config
135
+ self.embed_dim = config.hidden_size
136
+ self.image_size = config.image_size
137
+ self.patch_size = config.patch_size
138
+
139
+ self.class_embedding = nn.Parameter(
140
+ torch.randn(1, 1, self.embed_dim),
141
+ )
142
+
143
+ self.patch_embedding = nn.Conv2d(
144
+ in_channels=3, out_channels=self.embed_dim, kernel_size=self.patch_size, stride=self.patch_size
145
+ )
146
+
147
+ self.num_patches = (self.image_size // self.patch_size) ** 2
148
+ self.num_positions = self.num_patches + 1
149
+
150
+ self.position_embedding = nn.Parameter(torch.randn(1, self.num_positions, self.embed_dim))
151
+
152
+ def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
153
+ batch_size = pixel_values.shape[0]
154
+ target_dtype = self.patch_embedding.weight.dtype
155
+ patch_embeds = self.patch_embedding(pixel_values) # shape = [*, width, grid, grid]
156
+ patch_embeds = patch_embeds.flatten(2).transpose(1, 2)
157
+ class_embeds = self.class_embedding.expand(batch_size, 1, -1).to(target_dtype)
158
+ embeddings = torch.cat([class_embeds, patch_embeds], dim=1)
159
+ embeddings = embeddings + self.position_embedding.to(target_dtype)
160
+ return embeddings
161
+
162
+
163
+ class InternAttention(nn.Module):
164
+ """Multi-headed attention from 'Attention Is All You Need' paper"""
165
+
166
+ def __init__(self, config: InternVisionConfig):
167
+ super().__init__()
168
+ self.config = config
169
+ self.embed_dim = config.hidden_size
170
+ self.num_heads = config.num_attention_heads
171
+ self.use_flash_attn = config.use_flash_attn and has_flash_attn
172
+ if config.use_flash_attn and not has_flash_attn:
173
+ print('Warning: Flash Attention is not available, use_flash_attn is set to False.')
174
+ self.head_dim = self.embed_dim // self.num_heads
175
+ if self.head_dim * self.num_heads != self.embed_dim:
176
+ raise ValueError(
177
+ f'embed_dim must be divisible by num_heads (got `embed_dim`: {self.embed_dim} and `num_heads`:'
178
+ f' {self.num_heads}).'
179
+ )
180
+
181
+ self.scale = self.head_dim ** -0.5
182
+ self.qkv = nn.Linear(self.embed_dim, 3 * self.embed_dim, bias=config.qkv_bias)
183
+ self.attn_drop = nn.Dropout(config.attention_dropout)
184
+ self.proj_drop = nn.Dropout(config.dropout)
185
+
186
+ self.qk_normalization = config.qk_normalization
187
+
188
+ if self.qk_normalization:
189
+ self.q_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps)
190
+ self.k_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps)
191
+
192
+ if self.use_flash_attn:
193
+ self.inner_attn = FlashAttention(attention_dropout=config.attention_dropout)
194
+ self.proj = nn.Linear(self.embed_dim, self.embed_dim)
195
+
196
+ def _naive_attn(self, x):
197
+ B, N, C = x.shape
198
+ qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4)
199
+ q, k, v = qkv.unbind(0) # make torchscript happy (cannot use tensor as tuple)
200
+
201
+ if self.qk_normalization:
202
+ B_, H_, N_, D_ = q.shape
203
+ q = self.q_norm(q.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2)
204
+ k = self.k_norm(k.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2)
205
+
206
+ attn = ((q * self.scale) @ k.transpose(-2, -1))
207
+ attn = attn.softmax(dim=-1)
208
+ attn = self.attn_drop(attn)
209
+
210
+ x = (attn @ v).transpose(1, 2).reshape(B, N, C)
211
+ x = self.proj(x)
212
+ x = self.proj_drop(x)
213
+ return x
214
+
215
+ def _flash_attn(self, x, key_padding_mask=None, need_weights=False):
216
+ qkv = self.qkv(x)
217
+ qkv = rearrange(qkv, 'b s (three h d) -> b s three h d', three=3, h=self.num_heads)
218
+
219
+ if self.qk_normalization:
220
+ q, k, v = qkv.unbind(2)
221
+ q = self.q_norm(q.flatten(-2, -1)).view(q.shape)
222
+ k = self.k_norm(k.flatten(-2, -1)).view(k.shape)
223
+ qkv = torch.stack([q, k, v], dim=2)
224
+
225
+ context, _ = self.inner_attn(
226
+ qkv, key_padding_mask=key_padding_mask, need_weights=need_weights, causal=False
227
+ )
228
+ outs = self.proj(rearrange(context, 'b s h d -> b s (h d)'))
229
+ outs = self.proj_drop(outs)
230
+ return outs
231
+
232
+ def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
233
+ x = self._naive_attn(hidden_states) if not self.use_flash_attn else self._flash_attn(hidden_states)
234
+ return x
235
+
236
+
237
+ class InternMLP(nn.Module):
238
+ def __init__(self, config: InternVisionConfig):
239
+ super().__init__()
240
+ self.config = config
241
+ self.act = ACT2FN[config.hidden_act]
242
+ self.fc1 = nn.Linear(config.hidden_size, config.intermediate_size)
243
+ self.fc2 = nn.Linear(config.intermediate_size, config.hidden_size)
244
+
245
+ def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
246
+ hidden_states = self.fc1(hidden_states)
247
+ hidden_states = self.act(hidden_states)
248
+ hidden_states = self.fc2(hidden_states)
249
+ return hidden_states
250
+
251
+
252
+ class InternVisionEncoderLayer(nn.Module):
253
+ def __init__(self, config: InternVisionConfig, drop_path_rate: float):
254
+ super().__init__()
255
+ self.embed_dim = config.hidden_size
256
+ self.intermediate_size = config.intermediate_size
257
+
258
+ self.attn = InternAttention(config)
259
+ self.mlp = InternMLP(config)
260
+ self.norm1 = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps)
261
+ self.norm2 = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps)
262
+
263
+ self.ls1 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim))
264
+ self.ls2 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim))
265
+ self.drop_path1 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity()
266
+ self.drop_path2 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity()
267
+
268
+ def forward(
269
+ self,
270
+ hidden_states: torch.Tensor,
271
+ ) -> Tuple[torch.FloatTensor, Optional[torch.FloatTensor], Optional[Tuple[torch.FloatTensor]]]:
272
+ """
273
+ Args:
274
+ hidden_states (`Tuple[torch.FloatTensor, Optional[torch.FloatTensor]]`): input to the layer of shape `(batch, seq_len, embed_dim)`
275
+ """
276
+ hidden_states = hidden_states + self.drop_path1(self.attn(self.norm1(hidden_states)) * self.ls1)
277
+
278
+ hidden_states = hidden_states + self.drop_path2(self.mlp(self.norm2(hidden_states)) * self.ls2)
279
+
280
+ return hidden_states
281
+
282
+
283
+ class InternVisionEncoder(nn.Module):
284
+ """
285
+ Transformer encoder consisting of `config.num_hidden_layers` self attention layers. Each layer is a
286
+ [`InternEncoderLayer`].
287
+
288
+ Args:
289
+ config (`InternConfig`):
290
+ The corresponding vision configuration for the `InternEncoder`.
291
+ """
292
+
293
+ def __init__(self, config: InternVisionConfig):
294
+ super().__init__()
295
+ self.config = config
296
+ # stochastic depth decay rule
297
+ dpr = [x.item() for x in torch.linspace(0, config.drop_path_rate, config.num_hidden_layers)]
298
+ self.layers = nn.ModuleList([
299
+ InternVisionEncoderLayer(config, dpr[idx]) for idx in range(config.num_hidden_layers)])
300
+ self.gradient_checkpointing = True
301
+
302
+ def forward(
303
+ self,
304
+ inputs_embeds,
305
+ output_hidden_states: Optional[bool] = None,
306
+ return_dict: Optional[bool] = None,
307
+ ) -> Union[Tuple, BaseModelOutput]:
308
+ r"""
309
+ Args:
310
+ inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`):
311
+ Embedded representation of the inputs. Should be float, not int tokens.
312
+ output_hidden_states (`bool`, *optional*):
313
+ Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors
314
+ for more detail.
315
+ return_dict (`bool`, *optional*):
316
+ Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.
317
+ """
318
+ output_hidden_states = (
319
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
320
+ )
321
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
322
+
323
+ encoder_states = () if output_hidden_states else None
324
+ hidden_states = inputs_embeds
325
+
326
+ for idx, encoder_layer in enumerate(self.layers):
327
+ if output_hidden_states:
328
+ encoder_states = encoder_states + (hidden_states,)
329
+ if self.gradient_checkpointing and self.training:
330
+ layer_outputs = torch.utils.checkpoint.checkpoint(
331
+ encoder_layer,
332
+ hidden_states)
333
+ else:
334
+ layer_outputs = encoder_layer(
335
+ hidden_states,
336
+ )
337
+ hidden_states = layer_outputs
338
+
339
+ if output_hidden_states:
340
+ encoder_states = encoder_states + (hidden_states,)
341
+
342
+ if not return_dict:
343
+ return tuple(v for v in [hidden_states, encoder_states] if v is not None)
344
+ return BaseModelOutput(
345
+ last_hidden_state=hidden_states, hidden_states=encoder_states
346
+ )
347
+
348
+
349
+ class InternVisionModel(PreTrainedModel):
350
+ main_input_name = 'pixel_values'
351
+ config_class = InternVisionConfig
352
+ _no_split_modules = ['InternVisionEncoderLayer']
353
+
354
+ def __init__(self, config: InternVisionConfig):
355
+ super().__init__(config)
356
+ self.config = config
357
+
358
+ self.embeddings = InternVisionEmbeddings(config)
359
+ self.encoder = InternVisionEncoder(config)
360
+
361
+ def resize_pos_embeddings(self, old_size, new_size, patch_size):
362
+ pos_emb = self.embeddings.position_embedding
363
+ _, num_positions, embed_dim = pos_emb.shape
364
+ cls_emb = pos_emb[:, :1, :]
365
+ pos_emb = pos_emb[:, 1:, :].reshape(1, old_size // patch_size, old_size // patch_size, -1).permute(0, 3, 1, 2)
366
+ pos_emb = F.interpolate(pos_emb.float(), size=new_size // patch_size, mode='bicubic', align_corners=False)
367
+ pos_emb = pos_emb.to(cls_emb.dtype).reshape(1, embed_dim, -1).permute(0, 2, 1)
368
+ pos_emb = torch.cat([cls_emb, pos_emb], dim=1)
369
+ self.embeddings.position_embedding = nn.Parameter(pos_emb)
370
+ logger.info('Resized position embeddings from {} to {}'.format(old_size, new_size))
371
+
372
+ def get_input_embeddings(self):
373
+ return self.embeddings
374
+
375
+ def forward(
376
+ self,
377
+ pixel_values: Optional[torch.FloatTensor] = None,
378
+ output_hidden_states: Optional[bool] = None,
379
+ return_dict: Optional[bool] = None,
380
+ pixel_embeds: Optional[torch.FloatTensor] = None,
381
+ ) -> Union[Tuple, BaseModelOutputWithPooling]:
382
+ output_hidden_states = (
383
+ output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
384
+ )
385
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
386
+
387
+ if pixel_values is None and pixel_embeds is None:
388
+ raise ValueError('You have to specify pixel_values or pixel_embeds')
389
+
390
+ if pixel_embeds is not None:
391
+ hidden_states = pixel_embeds
392
+ else:
393
+ if len(pixel_values.shape) == 4:
394
+ hidden_states = self.embeddings(pixel_values)
395
+ else:
396
+ raise ValueError(f'wrong pixel_values size: {pixel_values.shape}')
397
+ encoder_outputs = self.encoder(
398
+ inputs_embeds=hidden_states,
399
+ output_hidden_states=output_hidden_states,
400
+ return_dict=return_dict,
401
+ )
402
+ last_hidden_state = encoder_outputs.last_hidden_state
403
+ pooled_output = last_hidden_state[:, 0, :]
404
+
405
+ if not return_dict:
406
+ return (last_hidden_state, pooled_output) + encoder_outputs[1:]
407
+
408
+ return BaseModelOutputWithPooling(
409
+ last_hidden_state=last_hidden_state,
410
+ pooler_output=pooled_output,
411
+ hidden_states=encoder_outputs.hidden_states,
412
+ attentions=encoder_outputs.attentions,
413
+ )
modeling_internvl_chat.py ADDED
@@ -0,0 +1,449 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # InternVL
3
+ # Copyright (c) 2023 OpenGVLab
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # --------------------------------------------------------
6
+ import warnings
7
+ from typing import Any, List, Optional, Tuple, Union
8
+ import torch.distributed as dist
9
+ import torch.utils.checkpoint
10
+ from peft import LoraConfig, get_peft_model
11
+ from torch import nn
12
+ from torch.nn import CrossEntropyLoss
13
+ from transformers import GenerationConfig, LlamaForCausalLM, LlamaTokenizer
14
+ from transformers.generation.logits_process import LogitsProcessorList
15
+ from transformers.generation.stopping_criteria import StoppingCriteriaList
16
+ from transformers.generation.streamers import BaseStreamer
17
+ from transformers.modeling_outputs import CausalLMOutputWithPast
18
+ from transformers.modeling_utils import PreTrainedModel
19
+ from transformers.utils import ModelOutput, logging
20
+ from transformers.generation.utils import GreedySearchOutput, validate_stopping_criteria, GreedySearchDecoderOnlyOutput,GreedySearchEncoderDecoderOutput
21
+
22
+ from .configuration_internvl_chat import InternVLChatConfig
23
+ from .modeling_intern_vit import InternVisionModel
24
+
25
+ logger = logging.get_logger(__name__)
26
+
27
+
28
+ # modified from https://github.com/huggingface/transformers/blob/main/src/transformers/generation/utils.py
29
+ # Fix bug when using device_map='auto' for distributed inference
30
+ class MLlamaForCausalLM(LlamaForCausalLM):
31
+
32
+ def greedy_search(
33
+ self,
34
+ input_ids: torch.LongTensor,
35
+ logits_processor: Optional[LogitsProcessorList] = None,
36
+ stopping_criteria: Optional[StoppingCriteriaList] = None,
37
+ max_length: Optional[int] = None,
38
+ pad_token_id: Optional[int] = None,
39
+ eos_token_id: Optional[Union[int, List[int]]] = None,
40
+ output_attentions: Optional[bool] = None,
41
+ output_hidden_states: Optional[bool] = None,
42
+ output_scores: Optional[bool] = None,
43
+ return_dict_in_generate: Optional[bool] = None,
44
+ synced_gpus: bool = False,
45
+ streamer: Optional["BaseStreamer"] = None,
46
+ **model_kwargs,
47
+ ) -> Union[GreedySearchOutput, torch.LongTensor]:
48
+ # init values
49
+ logits_processor = logits_processor if logits_processor is not None else LogitsProcessorList()
50
+ stopping_criteria = stopping_criteria if stopping_criteria is not None else StoppingCriteriaList()
51
+ if max_length is not None:
52
+ warnings.warn(
53
+ "`max_length` is deprecated in this function, use"
54
+ " `stopping_criteria=StoppingCriteriaList([MaxLengthCriteria(max_length=max_length)])` instead.",
55
+ UserWarning,
56
+ )
57
+ stopping_criteria = validate_stopping_criteria(stopping_criteria, max_length)
58
+ pad_token_id = pad_token_id if pad_token_id is not None else self.generation_config.pad_token_id
59
+ eos_token_id = eos_token_id if eos_token_id is not None else self.generation_config.eos_token_id
60
+ if isinstance(eos_token_id, int):
61
+ eos_token_id = [eos_token_id]
62
+ eos_token_id_tensor = torch.tensor(eos_token_id).to(input_ids.device) if eos_token_id is not None else None
63
+ output_scores = output_scores if output_scores is not None else self.generation_config.output_scores
64
+ output_attentions = (
65
+ output_attentions if output_attentions is not None else self.generation_config.output_attentions
66
+ )
67
+ output_hidden_states = (
68
+ output_hidden_states if output_hidden_states is not None else self.generation_config.output_hidden_states
69
+ )
70
+ return_dict_in_generate = (
71
+ return_dict_in_generate
72
+ if return_dict_in_generate is not None
73
+ else self.generation_config.return_dict_in_generate
74
+ )
75
+
76
+ # init attention / hidden states / scores tuples
77
+ scores = () if (return_dict_in_generate and output_scores) else None
78
+ decoder_attentions = () if (return_dict_in_generate and output_attentions) else None
79
+ cross_attentions = () if (return_dict_in_generate and output_attentions) else None
80
+ decoder_hidden_states = () if (return_dict_in_generate and output_hidden_states) else None
81
+
82
+ # if model is an encoder-decoder, retrieve encoder attention weights and hidden states
83
+ if return_dict_in_generate and self.config.is_encoder_decoder:
84
+ encoder_attentions = model_kwargs["encoder_outputs"].get("attentions") if output_attentions else None
85
+ encoder_hidden_states = (
86
+ model_kwargs["encoder_outputs"].get("hidden_states") if output_hidden_states else None
87
+ )
88
+
89
+ # keep track of which sequences are already finished
90
+ unfinished_sequences = torch.ones(input_ids.shape[0], dtype=torch.long, device=input_ids.device)
91
+
92
+ this_peer_finished = False # used by synced_gpus only
93
+ while True:
94
+ if synced_gpus:
95
+ # Under synced_gpus the `forward` call must continue until all gpus complete their sequence.
96
+ # The following logic allows an early break if all peers finished generating their sequence
97
+ this_peer_finished_flag = torch.tensor(0.0 if this_peer_finished else 1.0).to(input_ids.device)
98
+ # send 0.0 if we finished, 1.0 otherwise
99
+ dist.all_reduce(this_peer_finished_flag, op=dist.ReduceOp.SUM)
100
+ # did all peers finish? the reduced sum will be 0.0 then
101
+ if this_peer_finished_flag.item() == 0.0:
102
+ break
103
+
104
+ # prepare model inputs
105
+ model_inputs = self.prepare_inputs_for_generation(input_ids, **model_kwargs)
106
+
107
+ # forward pass to get next token
108
+ outputs = self(
109
+ **model_inputs,
110
+ return_dict=True,
111
+ output_attentions=output_attentions,
112
+ output_hidden_states=output_hidden_states,
113
+ )
114
+
115
+ if synced_gpus and this_peer_finished:
116
+ continue # don't waste resources running the code we don't need
117
+
118
+ next_token_logits = outputs.logits[:, -1, :]
119
+
120
+ # pre-process distribution
121
+ next_tokens_scores = logits_processor(input_ids, next_token_logits)
122
+
123
+ # Store scores, attentions and hidden_states when required
124
+ if return_dict_in_generate:
125
+ if output_scores:
126
+ scores += (next_tokens_scores,)
127
+ if output_attentions:
128
+ decoder_attentions += (
129
+ (outputs.decoder_attentions,) if self.config.is_encoder_decoder else (outputs.attentions,)
130
+ )
131
+ if self.config.is_encoder_decoder:
132
+ cross_attentions += (outputs.cross_attentions,)
133
+
134
+ if output_hidden_states:
135
+ decoder_hidden_states += (
136
+ (outputs.decoder_hidden_states,)
137
+ if self.config.is_encoder_decoder
138
+ else (outputs.hidden_states,)
139
+ )
140
+
141
+ # argmax
142
+ next_tokens = torch.argmax(next_tokens_scores, dim=-1).to(device=input_ids.device)
143
+ # finished sentences should have their next token be a padding token
144
+ if eos_token_id is not None:
145
+ if pad_token_id is None:
146
+ raise ValueError("If `eos_token_id` is defined, make sure that `pad_token_id` is defined.")
147
+ next_tokens = next_tokens * unfinished_sequences + pad_token_id * (1 - unfinished_sequences)
148
+
149
+ # update generated ids, model inputs, and length for next step
150
+ input_ids = torch.cat([input_ids, next_tokens[:, None]], dim=-1)
151
+ if streamer is not None:
152
+ streamer.put(next_tokens.cpu())
153
+ model_kwargs = self._update_model_kwargs_for_generation(
154
+ outputs, model_kwargs, is_encoder_decoder=self.config.is_encoder_decoder
155
+ )
156
+
157
+ # if eos_token was found in one sentence, set sentence to finished
158
+ if eos_token_id_tensor is not None:
159
+ unfinished_sequences = unfinished_sequences.mul(
160
+ next_tokens.tile(eos_token_id_tensor.shape[0], 1).ne(eos_token_id_tensor.unsqueeze(1)).prod(dim=0)
161
+ )
162
+
163
+ # stop when each sentence is finished
164
+ if unfinished_sequences.max() == 0:
165
+ this_peer_finished = True
166
+
167
+ # stop if we exceed the maximum length
168
+ if stopping_criteria(input_ids, scores):
169
+ this_peer_finished = True
170
+
171
+ if this_peer_finished and not synced_gpus:
172
+ break
173
+
174
+ if streamer is not None:
175
+ streamer.end()
176
+
177
+ if return_dict_in_generate:
178
+ if self.config.is_encoder_decoder:
179
+ return GreedySearchEncoderDecoderOutput(
180
+ sequences=input_ids,
181
+ scores=scores,
182
+ encoder_attentions=encoder_attentions,
183
+ encoder_hidden_states=encoder_hidden_states,
184
+ decoder_attentions=decoder_attentions,
185
+ cross_attentions=cross_attentions,
186
+ decoder_hidden_states=decoder_hidden_states,
187
+ past_key_values=model_kwargs.get("past_key_values"),
188
+ )
189
+ else:
190
+ return GreedySearchDecoderOnlyOutput(
191
+ sequences=input_ids,
192
+ scores=scores,
193
+ attentions=decoder_attentions,
194
+ hidden_states=decoder_hidden_states,
195
+ past_key_values=model_kwargs.get("past_key_values"),
196
+ )
197
+ else:
198
+ return input_ids
199
+
200
+
201
+ class InternVLChatModel(PreTrainedModel):
202
+ config_class = InternVLChatConfig
203
+ main_input_name = 'pixel_values'
204
+ _no_split_modules = ['InternVisionModel', 'LlamaDecoderLayer']
205
+
206
+ def __init__(self, config: InternVLChatConfig, vision_model=None, language_model=None):
207
+ super().__init__(config)
208
+
209
+ image_size = config.force_image_size or config.vision_config.image_size
210
+ patch_size = config.vision_config.patch_size
211
+ self.select_layer = config.select_layer
212
+ self.template = config.template
213
+ self.num_image_token = int((image_size // patch_size) ** 2 * (config.downsample_ratio ** 2))
214
+ self.downsample_ratio = config.downsample_ratio
215
+ logger.info(f'num_image_token: {self.num_image_token}')
216
+ if vision_model is not None:
217
+ self.vision_model = vision_model
218
+ else:
219
+ self.vision_model = InternVisionModel(config.vision_config)
220
+ if language_model is not None:
221
+ self.language_model = language_model
222
+ else:
223
+ # self.language_model = LlamaForCausalLM(config.llm_config)
224
+ self.language_model = MLlamaForCausalLM(config.llm_config)
225
+ vit_hidden_size = config.vision_config.hidden_size
226
+ llm_hidden_size = config.llm_config.hidden_size
227
+
228
+ self.mlp1 = nn.Sequential(
229
+ nn.LayerNorm(vit_hidden_size * 4),
230
+ nn.Linear(vit_hidden_size * 4, llm_hidden_size),
231
+ nn.GELU(),
232
+ nn.Linear(llm_hidden_size, llm_hidden_size)
233
+ )
234
+
235
+ if config.force_image_size != config.vision_config.image_size:
236
+ self.vision_model.resize_pos_embeddings(
237
+ old_size=config.vision_config.image_size,
238
+ new_size=config.force_image_size,
239
+ patch_size=config.vision_config.patch_size
240
+ )
241
+
242
+ self.img_context_token_id = None
243
+
244
+ if config.use_backbone_lora:
245
+ self.wrap_backbone_lora(r=config.use_backbone_lora)
246
+
247
+ if config.use_llm_lora:
248
+ self.wrap_llm_lora(r=config.use_llm_lora)
249
+
250
+ def wrap_backbone_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
251
+ lora_config = LoraConfig(
252
+ r=r,
253
+ target_modules=['attn.qkv', 'attn.proj', 'mlp.fc1', 'mlp.fc2'],
254
+ lora_alpha=lora_alpha,
255
+ lora_dropout=lora_dropout,
256
+ )
257
+ self.vision_model = get_peft_model(self.vision_model, lora_config)
258
+ self.vision_model.print_trainable_parameters()
259
+
260
+ def wrap_llm_lora(self, r=128, lora_alpha=256, lora_dropout=0.05):
261
+ lora_config = LoraConfig(
262
+ r=r,
263
+ target_modules=['self_attn.q_proj', 'self_attn.k_proj', 'self_attn.v_proj', 'self_attn.o_proj',
264
+ 'mlp.gate_proj', 'mlp.down_proj', 'mlp.up_proj'],
265
+ lora_alpha=lora_alpha,
266
+ lora_dropout=lora_dropout,
267
+ task_type='CAUSAL_LM'
268
+ )
269
+ self.language_model = get_peft_model(self.language_model, lora_config)
270
+ self.language_model.print_trainable_parameters()
271
+
272
+ def forward(
273
+ self,
274
+ pixel_values: torch.FloatTensor,
275
+ input_ids: torch.LongTensor = None,
276
+ attention_mask: Optional[torch.Tensor] = None,
277
+ position_ids: Optional[torch.LongTensor] = None,
278
+ image_flags: Optional[torch.LongTensor] = None,
279
+ past_key_values: Optional[List[torch.FloatTensor]] = None,
280
+ labels: Optional[torch.LongTensor] = None,
281
+ use_cache: Optional[bool] = None,
282
+ output_attentions: Optional[bool] = None,
283
+ output_hidden_states: Optional[bool] = None,
284
+ return_dict: Optional[bool] = None,
285
+ ) -> Union[Tuple, CausalLMOutputWithPast]:
286
+ return_dict = return_dict if return_dict is not None else self.config.use_return_dict
287
+
288
+ image_flags = image_flags.squeeze(-1)
289
+ input_embeds = self.language_model.get_input_embeddings()(input_ids)
290
+
291
+ vit_embeds = self.extract_feature(pixel_values)
292
+ vit_embeds = vit_embeds[image_flags == 1]
293
+
294
+ B, N, C = input_embeds.shape
295
+ input_embeds = input_embeds.reshape(B * N, C)
296
+
297
+ input_ids = input_ids.reshape(B * N)
298
+ selected = (input_ids == self.img_context_token_id)
299
+ try:
300
+ input_embeds[selected] = input_embeds[selected] * 0.0 + vit_embeds.reshape(-1, C)
301
+ except:
302
+ pass
303
+
304
+ input_embeds = input_embeds.reshape(B, N, C)
305
+
306
+ outputs = self.language_model.model(
307
+ inputs_embeds=input_embeds,
308
+ attention_mask=attention_mask,
309
+ position_ids=position_ids,
310
+ past_key_values=past_key_values,
311
+ use_cache=use_cache,
312
+ output_attentions=output_attentions,
313
+ output_hidden_states=output_hidden_states,
314
+ return_dict=return_dict,
315
+ )
316
+ hidden_states = outputs[0]
317
+ logits = self.language_model.lm_head(hidden_states)
318
+
319
+ loss = None
320
+ if labels is not None:
321
+ # Shift so that tokens < n predict n
322
+ shift_logits = logits[..., :-1, :].contiguous()
323
+ shift_labels = labels[..., 1:].contiguous()
324
+ # Flatten the tokens
325
+ loss_fct = CrossEntropyLoss()
326
+ shift_logits = shift_logits.view(-1, self.language_model.config.vocab_size)
327
+ shift_labels = shift_labels.view(-1)
328
+ # Enable model parallelism
329
+ shift_labels = shift_labels.to(shift_logits.device)
330
+ loss = loss_fct(shift_logits, shift_labels)
331
+
332
+ if not return_dict:
333
+ output = (logits,) + outputs[1:]
334
+ return (loss,) + output if loss is not None else output
335
+
336
+ return CausalLMOutputWithPast(
337
+ loss=loss,
338
+ logits=logits,
339
+ past_key_values=outputs.past_key_values,
340
+ hidden_states=outputs.hidden_states,
341
+ attentions=outputs.attentions,
342
+ )
343
+
344
+ def pixel_shuffle(self, x, scale_factor=0.5):
345
+ n, w, h, c = x.size()
346
+ # N, W, H, C --> N, W, H * scale, C // scale
347
+ x = x.view(n, w, int(h * scale_factor), int(c / scale_factor))
348
+ # N, W, H * scale, C // scale --> N, H * scale, W, C // scale
349
+ x = x.permute(0, 2, 1, 3).contiguous()
350
+ # N, H * scale, W, C // scale --> N, H * scale, W * scale, C // (scale ** 2)
351
+ x = x.view(n, int(h * scale_factor), int(w * scale_factor),
352
+ int(c / (scale_factor * scale_factor)))
353
+ return x
354
+
355
+ def extract_feature(self, pixel_values):
356
+ if self.select_layer == -1:
357
+ vit_embeds = self.vision_model(
358
+ pixel_values=pixel_values,
359
+ output_hidden_states=False,
360
+ return_dict=True).last_hidden_state
361
+ else:
362
+ vit_embeds = self.vision_model(
363
+ pixel_values=pixel_values,
364
+ output_hidden_states=True,
365
+ return_dict=True).hidden_states[self.select_layer]
366
+ vit_embeds = vit_embeds[:, 1:, :]
367
+ # if torch.distributed.get_rank() == 0:
368
+ # print("before pixel shuffle:", vit_embeds.shape)
369
+ h = w = int(vit_embeds.shape[1] ** 0.5)
370
+ vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], h, w, -1)
371
+ vit_embeds = self.pixel_shuffle(vit_embeds, scale_factor=self.downsample_ratio)
372
+ vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], -1, vit_embeds.shape[-1])
373
+ # if torch.distributed.get_rank() == 0:
374
+ # print("after pixel shuffle:", vit_embeds.shape)
375
+ vit_embeds = self.mlp1(vit_embeds)
376
+ return vit_embeds
377
+
378
+ def chat(self, tokenizer, pixel_values, question, generation_config,
379
+ IMG_START_TOKEN='<img>', IMG_END_TOKEN='</img>', IMG_CONTEXT_TOKEN='<IMG_CONTEXT>'):
380
+
381
+ img_context_token_id = tokenizer.convert_tokens_to_ids(IMG_CONTEXT_TOKEN)
382
+ self.img_context_token_id = img_context_token_id
383
+
384
+ from .conversation import get_conv_template
385
+
386
+ template = get_conv_template(self.template)
387
+ image_tokens = IMG_START_TOKEN + IMG_CONTEXT_TOKEN * self.num_image_token + IMG_END_TOKEN
388
+ template.append_message(template.roles[0], image_tokens + '\n' + question)
389
+ template.append_message(template.roles[1], None)
390
+ query = template.get_prompt()
391
+ model_inputs = tokenizer(query, return_tensors='pt')
392
+ input_ids = model_inputs['input_ids'].cuda()
393
+ attention_mask = model_inputs['attention_mask'].cuda()
394
+
395
+ generation_output = self.generate(
396
+ pixel_values=pixel_values,
397
+ input_ids=input_ids,
398
+ attention_mask=attention_mask,
399
+ **generation_config
400
+ )
401
+ response = tokenizer.batch_decode(generation_output, skip_special_tokens=True)[0]
402
+ query_to_print = query.replace(image_tokens, '<image>')
403
+ print(query_to_print, response)
404
+ return response
405
+
406
+ @torch.no_grad()
407
+ def generate(
408
+ self,
409
+ pixel_values: Optional[torch.FloatTensor] = None,
410
+ input_ids: Optional[torch.FloatTensor] = None,
411
+ attention_mask: Optional[torch.LongTensor] = None,
412
+ visual_features: Optional[torch.FloatTensor] = None,
413
+ generation_config: Optional[GenerationConfig] = None,
414
+ output_hidden_states: Optional[bool] = None,
415
+ return_dict: Optional[bool] = None,
416
+ **generate_kwargs,
417
+ ) -> torch.LongTensor:
418
+
419
+ assert self.img_context_token_id is not None
420
+ if pixel_values is not None:
421
+ if visual_features is not None:
422
+ vit_embeds = visual_features
423
+ else:
424
+ vit_embeds = self.extract_feature(pixel_values)
425
+
426
+ input_embeds = self.language_model.get_input_embeddings()(input_ids)
427
+ B, N, C = input_embeds.shape
428
+ input_embeds = input_embeds.reshape(B * N, C)
429
+
430
+ input_ids = input_ids.reshape(B * N)
431
+ selected = (input_ids == self.img_context_token_id)
432
+ assert selected.sum() != 0
433
+ input_embeds[selected] = vit_embeds.reshape(-1, C).to(input_embeds.device)
434
+
435
+ input_embeds = input_embeds.reshape(B, N, C)
436
+ else:
437
+ input_embeds = self.language_model.get_input_embeddings()(input_ids)
438
+
439
+ outputs = self.language_model.generate(
440
+ inputs_embeds=input_embeds,
441
+ attention_mask=attention_mask,
442
+ generation_config=generation_config,
443
+ output_hidden_states=output_hidden_states,
444
+ return_dict=return_dict,
445
+ use_cache=True,
446
+ **generate_kwargs,
447
+ )
448
+
449
+ return outputs
special_tokens_map.json ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<img>",
4
+ "</img>",
5
+ "<IMG_CONTEXT>",
6
+ "<quad>",
7
+ "</quad>",
8
+ "<ref>",
9
+ "</ref>",
10
+ "<box>",
11
+ "</box>"
12
+ ],
13
+ "bos_token": {
14
+ "content": "<|startoftext|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ },
20
+ "eos_token": {
21
+ "content": "<|im_end|>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false
26
+ },
27
+ "pad_token": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false
33
+ },
34
+ "unk_token": {
35
+ "content": "<unk>",
36
+ "lstrip": false,
37
+ "normalized": false,
38
+ "rstrip": false,
39
+ "single_word": false
40
+ }
41
+ }
tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:386c49cf943d71aa110361135338c50e38beeff0a66593480421f37b319e1a39
3
+ size 1033105
tokenizer_config.json ADDED
@@ -0,0 +1,143 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<|startoftext|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "<|endoftext|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "6": {
30
+ "content": "<|im_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": false
36
+ },
37
+ "7": {
38
+ "content": "<|im_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "68": {
46
+ "content": "<img>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "70": {
54
+ "content": "</img>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "64000": {
62
+ "content": "<IMG_CONTEXT>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "64001": {
70
+ "content": "<quad>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "64002": {
78
+ "content": "</quad>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "64003": {
86
+ "content": "<ref>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "64004": {
94
+ "content": "</ref>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "64005": {
102
+ "content": "<box>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "64006": {
110
+ "content": "</box>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ }
117
+ },
118
+ "additional_special_tokens": [
119
+ "<img>",
120
+ "</img>",
121
+ "<IMG_CONTEXT>",
122
+ "<quad>",
123
+ "</quad>",
124
+ "<ref>",
125
+ "</ref>",
126
+ "<box>",
127
+ "</box>"
128
+ ],
129
+ "bos_token": "<|startoftext|>",
130
+ "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
131
+ "clean_up_tokenization_spaces": false,
132
+ "eos_token": "<|im_end|>",
133
+ "legacy": true,
134
+ "model_max_length": 1280,
135
+ "pad_token": "<unk>",
136
+ "sp_model_kwargs": {},
137
+ "spaces_between_special_tokens": false,
138
+ "tokenizer_class": "LlamaTokenizer",
139
+ "trust_remote_code": false,
140
+ "unk_token": "<unk>",
141
+ "use_default_system_prompt": false,
142
+ "use_fast": true
143
+ }
trainer_state.json ADDED
The diff for this file is too large to render. See raw diff