106 lines
4.1 KiB
Python
106 lines
4.1 KiB
Python
# coding=utf-8
|
|
# Copyright 2024 HuggingFace Inc. team. All rights reserved.
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""Pixtral model configuration"""
|
|
|
|
from ...configuration_utils import PretrainedConfig
|
|
from ...utils import logging
|
|
|
|
|
|
logger = logging.get_logger(__name__)
|
|
|
|
|
|
class PixtralVisionConfig(PretrainedConfig):
|
|
r"""
|
|
This is the configuration class to store the configuration of a [`PixtralVisionModel`]. It is used to instantiate an
|
|
Pixtral vision encoder according to the specified arguments, defining the model architecture. Instantiating a configuration
|
|
with the defaults will yield a similar configuration to the vision encoder used by Pixtral-12B.
|
|
|
|
e.g. [pixtral-hf/pixtral-9b](https://huggingface.co/pixtral-hf/pixtral-9b)
|
|
|
|
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
|
documentation from [`PretrainedConfig`] for more information.
|
|
|
|
Args:
|
|
hidden_size (`int`, *optional*, defaults to 1024):
|
|
Dimension of the hidden representations.
|
|
intermediate_size (`int`, *optional*, defaults to 4096):
|
|
Dimension of the MLP representations.
|
|
num_hidden_layers (`int`, *optional*, defaults to 24):
|
|
Number of hidden layers in the Transformer encoder.
|
|
num_attention_heads (`int`, *optional*, defaults to 16):
|
|
Number of attention heads in the Transformer encoder.
|
|
num_channels (`int`, *optional*, defaults to 3):
|
|
Number of input channels in the input images.
|
|
image_size (`int`, *optional*, defaults to 1024):
|
|
Max dimension of the input images.
|
|
patch_size (`int`, *optional*, defaults to 16):
|
|
Size of the image patches.
|
|
hidden_act (`str`, *optional*, defaults to `"gelu"`):
|
|
Activation function used in the hidden layers.
|
|
attention_dropout (`float`, *optional*, defaults to 0.0):
|
|
Dropout probability for the attention layers.
|
|
rope_theta (`float`, *optional*, defaults to 10000.0):
|
|
The base period of the RoPE embeddings.
|
|
initializer_range (`float`, *optional*, defaults to 0.02):
|
|
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
|
|
|
Example:
|
|
|
|
```python
|
|
>>> from transformers import PixtralVisionModel, PixtralVisionConfig
|
|
|
|
>>> # Initializing a Pixtral-12B style configuration
|
|
>>> config = PixtralVisionConfig()
|
|
|
|
>>> # Initializing a model (with randomly initialized weights) from the configuration
|
|
>>> model = PixtralVisionModel(configuration)
|
|
|
|
>>> # Accessing the model configuration
|
|
>>> configuration = model.config
|
|
```"""
|
|
|
|
model_type = "pixtral"
|
|
|
|
def __init__(
|
|
self,
|
|
hidden_size=1024,
|
|
intermediate_size=4096,
|
|
num_hidden_layers=24,
|
|
num_attention_heads=16,
|
|
num_channels=3,
|
|
image_size=1024,
|
|
patch_size=16,
|
|
hidden_act="gelu",
|
|
attention_dropout=0.0,
|
|
rope_theta=10000.0,
|
|
initializer_range=0.02,
|
|
**kwargs,
|
|
):
|
|
super().__init__(**kwargs)
|
|
|
|
self.hidden_size = hidden_size
|
|
self.intermediate_size = intermediate_size
|
|
self.num_hidden_layers = num_hidden_layers
|
|
self.num_attention_heads = num_attention_heads
|
|
self.num_channels = num_channels
|
|
self.patch_size = patch_size
|
|
self.image_size = image_size
|
|
self.attention_dropout = attention_dropout
|
|
self.hidden_act = hidden_act
|
|
self.rope_theta = rope_theta
|
|
self.head_dim = hidden_size // num_attention_heads
|
|
self.initializer_range = initializer_range
|
|
|
|
|
|
__all__ = ["PixtralVisionConfig"]
|