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from transformers import PretrainedConfig
class SincNetConfig(PretrainedConfig):
model_type = "sincnet"
def __init__(
self,
stride: int = 10,
num_sinc_filters: int = 80,
sinc_filter_length: int = 251,
num_conv_filters: int = 60,
conv_filter_length: int = 5,
pool_kernel_size: int = 3,
pool_stride: int = 3,
sample_rate: int = 16000,
sinc_filter_stride: int = 10,
sinc_filter_padding: int = 0,
sinc_filter_dilation: int = 1,
min_low_hz: int = 50,
min_band_hz: int = 50,
sinc_filter_in_channels: int = 1,
num_wavform_channels: int = 1,
**kwargs
):
self.sample_rate = sample_rate
self.stride = stride
self.num_sinc_filters = num_sinc_filters
self.sinc_filter_length = sinc_filter_length
self.num_conv_filters = num_conv_filters
self.conv_filter_length = conv_filter_length
self.pool_kernel_size = pool_kernel_size
self.pool_stride = pool_stride
self.sinc_filter_stride = sinc_filter_stride
self.sinc_filter_padding = sinc_filter_padding
self.sinc_filter_dilation = sinc_filter_dilation
self.min_low_hz = min_low_hz
self.min_band_hz = min_band_hz
self.sinc_filter_in_channels = sinc_filter_in_channels
self.num_wavform_channels = num_wavform_channels
super().__init__(**kwargs)
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