114 lines
4.5 KiB
Python
114 lines
4.5 KiB
Python
# coding=utf-8
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# Copyright 2024 Descript and The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Dac model configuration"""
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import math
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import numpy as np
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from ...configuration_utils import PretrainedConfig
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from ...utils import logging
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logger = logging.get_logger(__name__)
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class DacConfig(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of an [`DacModel`]. It is used to instantiate a
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Dac model according to the specified arguments, defining the model architecture. Instantiating a configuration
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with the defaults will yield a similar configuration to that of the
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[descript/dac_16khz](https://huggingface.co/descript/dac_16khz) architecture.
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Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
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documentation from [`PretrainedConfig`] for more information.
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Args:
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encoder_hidden_size (`int`, *optional*, defaults to 64):
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Intermediate representation dimension for the encoder.
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downsampling_ratios (`list[int]`, *optional*, defaults to `[2, 4, 8, 8]`):
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Ratios for downsampling in the encoder. These are used in reverse order for upsampling in the decoder.
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decoder_hidden_size (`int`, *optional*, defaults to 1536):
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Intermediate representation dimension for the decoder.
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n_codebooks (`int`, *optional*, defaults to 9):
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Number of codebooks in the VQVAE.
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codebook_size (`int`, *optional*, defaults to 1024):
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Number of discrete codes in each codebook.
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codebook_dim (`int`, *optional*, defaults to 8):
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Dimension of the codebook vectors. If not defined, uses `encoder_hidden_size`.
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quantizer_dropout (`bool`, *optional*, defaults to 0):
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Whether to apply dropout to the quantizer.
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commitment_loss_weight (float, *optional*, defaults to 0.25):
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Weight of the commitment loss term in the VQVAE loss function.
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codebook_loss_weight (float, *optional*, defaults to 1.0):
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Weight of the codebook loss term in the VQVAE loss function.
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sampling_rate (`int`, *optional*, defaults to 16000):
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The sampling rate at which the audio waveform should be digitalized expressed in hertz (Hz).
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Example:
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```python
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>>> from transformers import DacModel, DacConfig
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>>> # Initializing a "descript/dac_16khz" style configuration
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>>> configuration = DacConfig()
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>>> # Initializing a model (with random weights) from the "descript/dac_16khz" style configuration
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>>> model = DacModel(configuration)
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>>> # Accessing the model configuration
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>>> configuration = model.config
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```"""
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model_type = "dac"
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def __init__(
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self,
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encoder_hidden_size=64,
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downsampling_ratios=[2, 4, 8, 8],
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decoder_hidden_size=1536,
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n_codebooks=9,
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codebook_size=1024,
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codebook_dim=8,
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quantizer_dropout=0,
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commitment_loss_weight=0.25,
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codebook_loss_weight=1.0,
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sampling_rate=16000,
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**kwargs,
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):
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self.encoder_hidden_size = encoder_hidden_size
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self.downsampling_ratios = downsampling_ratios
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self.decoder_hidden_size = decoder_hidden_size
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self.upsampling_ratios = downsampling_ratios[::-1]
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self.n_codebooks = n_codebooks
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self.codebook_size = codebook_size
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self.codebook_dim = codebook_dim
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self.quantizer_dropout = quantizer_dropout
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self.sampling_rate = sampling_rate
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self.hidden_size = encoder_hidden_size * (2 ** len(downsampling_ratios))
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self.hop_length = int(np.prod(downsampling_ratios))
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self.commitment_loss_weight = commitment_loss_weight
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self.codebook_loss_weight = codebook_loss_weight
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super().__init__(**kwargs)
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@property
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def frame_rate(self) -> int:
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hop_length = np.prod(self.upsampling_ratios)
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return math.ceil(self.sampling_rate / hop_length)
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__all__ = ["DacConfig"]
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