# coding=utf-8 # Copyright 2023 MURGe-Lab and The 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. """TVLT model configuration""" from ....configuration_utils import PretrainedConfig from ....utils import logging logger = logging.get_logger(__name__) class TvltConfig(PretrainedConfig): r""" This is the configuration class to store the configuration of a [`TvltModel`]. It is used to instantiate a TVLT model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the TVLT [ZinengTang/tvlt-base](https://huggingface.co/ZinengTang/tvlt-base) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: image_size (`int`, *optional*, defaults to 224): The size (resolution) of each image. spectrogram_length (`int`, *optional*, defaults to 2048): The time length of each audio spectrogram. frequency_length (`int`, *optional*, defaults to 128): The frequency length of audio spectrogram. image_patch_size (`List[int]`, *optional*, defaults to `[16, 16]`): The size (resolution) of each image patch. audio_patch_size (`List[int]`, *optional*, defaults to `[16, 16]`): The size (resolution) of each audio patch. num_image_channels (`int`, *optional*, defaults to 3): The number of input image channels. num_audio_channels (`int`, *optional*, defaults to 1): The number of input audio channels. num_frames (`int`, *optional*, defaults to 8): The maximum number of frames for an input video. hidden_size (`int`, *optional*, defaults to 768): Dimensionality of the encoder layers and the pooler layer. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 12): Number of attention heads for each attention layer in the Transformer encoder. intermediate_size (`int`, *optional*, defaults to 3072): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. hidden_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. qkv_bias (`bool`, *optional*, defaults to `True`): Whether to add a bias to the queries, keys and values. use_mean_pooling (`bool`, *optional*, defaults to `False`): Whether to mean pool the final hidden states instead of using the final hidden state of the [CLS] token. decoder_num_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the decoder. decoder_hidden_size (`int`, *optional*, defaults to 512): Dimensionality of the decoder. decoder_num_hidden_layers (`int`, *optional*, defaults to 8): Number of hidden layers in the decoder. decoder_intermediate_size (`int`, *optional*, defaults to 2048): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the decoder. pixel_mask_ratio (`float`, *optional*, defaults to 0.75): Image patch masking ratio. audio_mask_ratio (`float`, *optional*, defaults to 0.15): Audio patch masking ratio. audio_mask_type (`str`, *optional*, defaults to `"frame-level"`): Audio patch masking type, choose between "frame-level" and "patch-level". task_matching (`bool`, *optional*, defaults to `True`): Whether to use vision audio matching task in pretraining. task_mae (`bool`, *optional*, defaults to `True`): Whether to use the masked auto-encoder (MAE) in pretraining. loss_type (`str`, *optional*, defaults to `"classification"`): Loss types including regression and classification. Example: ```python >>> from transformers import TvltConfig, TvltModel >>> # # Initializing a TVLT ZinengTang/tvlt-base style configuration >>> configuration = TvltConfig() >>> # # Initializing a model (with random weights) from the ZinengTang/tvlt-base style configuration >>> model = TvltModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "tvlt" def __init__( self, image_size=224, spectrogram_length=2048, frequency_length=128, image_patch_size=[16, 16], audio_patch_size=[16, 16], num_image_channels=3, num_audio_channels=1, num_frames=8, hidden_size=768, num_hidden_layers=12, num_attention_heads=12, intermediate_size=3072, hidden_act="gelu", hidden_dropout_prob=0.0, attention_probs_dropout_prob=0.0, initializer_range=0.02, layer_norm_eps=1e-6, qkv_bias=True, use_mean_pooling=False, decoder_num_attention_heads=16, decoder_hidden_size=512, decoder_num_hidden_layers=8, decoder_intermediate_size=2048, pixel_mask_ratio=0.75, audio_mask_ratio=0.15, audio_mask_type="frame-level", task_matching=True, task_mae=True, loss_type="classification", **kwargs, ): super().__init__(**kwargs) if audio_mask_type not in ("frame-level", "patch_level"): raise ValueError( "audio_mask_type must be one of two acceptable strategies - {'frame_level', 'patch-level') " f"got {audio_mask_type}" ) self.image_size = image_size self.spectrogram_length = spectrogram_length self.frequency_length = frequency_length self.image_patch_size = image_patch_size self.audio_patch_size = audio_patch_size self.num_image_channels = num_image_channels self.num_audio_channels = num_audio_channels self.num_frames = num_frames self.hidden_size = hidden_size self.num_hidden_layers = num_hidden_layers self.num_attention_heads = num_attention_heads self.intermediate_size = intermediate_size self.hidden_act = hidden_act self.hidden_dropout_prob = hidden_dropout_prob self.attention_probs_dropout_prob = attention_probs_dropout_prob self.initializer_range = initializer_range self.layer_norm_eps = layer_norm_eps self.qkv_bias = qkv_bias self.use_mean_pooling = use_mean_pooling self.decoder_num_attention_heads = decoder_num_attention_heads self.decoder_hidden_size = decoder_hidden_size self.decoder_num_hidden_layers = decoder_num_hidden_layers self.decoder_intermediate_size = decoder_intermediate_size self.pixel_mask_ratio = pixel_mask_ratio self.audio_mask_ratio = audio_mask_ratio self.audio_mask_type = audio_mask_type self.task_matching = task_matching self.task_mae = task_mae self.loss_type = loss_type