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"""Hyperparameters for YAMNet."""
from dataclasses import dataclass
# The following hyperparameters (except patch_hop_seconds) were used to train YAMNet,
# so expect some variability in performance if you change these. The patch hop can
# be changed arbitrarily: a smaller hop should give you more patches from the same
# clip and possibly better performance at a larger computational cost.
@dataclass(frozen=True) # Instances of this class are immutable.
class Params:
sample_rate: float = 16000.0
stft_window_seconds: float = 0.025
stft_hop_seconds: float = 0.010
mel_bands: int = 64
mel_min_hz: float = 125.0
mel_max_hz: float = 7500.0
log_offset: float = 0.001
patch_window_seconds: float = 0.96
patch_hop_seconds: float = 0.48
@property
def patch_frames(self):
return int(round(self.patch_window_seconds / self.stft_hop_seconds))
@property
def patch_bands(self):
return self.mel_bands
num_classes: int = 521
conv_padding: str = 'same'
batchnorm_center: bool = True
batchnorm_scale: bool = False
batchnorm_epsilon: float = 1e-4
classifier_activation: str = 'sigmoid'
tflite_compatible: bool = True
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