def __init__(
self,
freq_masks=0,
time_masks=0,
freq_width=10,
time_width=10,
rect_masks=0,
rect_time=5,
rect_freq=20,
rng=None,
mask_value=0.0,
use_numba_spec_augment: bool = True,
):
super().__init__()
if rect_masks > 0:
self.spec_cutout = SpecCutout(
rect_masks=rect_masks,
rect_time=rect_time,
rect_freq=rect_freq,
rng=rng,
)
# self.spec_cutout.to(self._device)
else:
self.spec_cutout = lambda input_spec: input_spec
if freq_masks + time_masks > 0:
self.spec_augment = SpecAugment(
freq_masks=freq_masks,
time_masks=time_masks,
freq_width=freq_width,
time_width=time_width,
rng=rng,
mask_value=mask_value,
)
else:
self.spec_augment = lambda input_spec: input_spec
# Check if numba is supported, and use a Numba kernel if it is
if use_numba_spec_augment and numba_utils.numba_cuda_is_supported(
__NUMBA_MINIMUM_VERSION__):
self.spec_augment_numba = SpecAugmentNumba(
freq_masks=freq_masks,
time_masks=time_masks,
freq_width=freq_width,
time_width=time_width,
rng=rng,
mask_value=mask_value,
)
else:
self.spec_augment_numba = None
def __init__(
self, patch_size: int = 48, mask_patches: float = 10.0, freq_masks: int = 0, freq_width: int = 0,
):
super().__init__()
self.patch_size = patch_size
if mask_patches >= 1:
self.mask_patches = int(mask_patches)
elif mask_patches >= 0:
self._mask_fraction = mask_patches
self.mask_patches = None
else:
raise ValueError('mask_patches cannot be negative')
if freq_masks > 0:
self.spec_augment = SpecAugment(freq_masks=freq_masks, time_masks=0, freq_width=freq_width, time_width=0,)
else:
self.spec_augment = None
def __init__(
self,
patch_size: int = 48,
mask_patches: int = 10,
freq_masks: int = 0,
freq_width: int = 0,
):
super().__init__()
self.patch_size = patch_size
self.mask_patches = mask_patches
if freq_masks > 0:
self.spec_augment = SpecAugment(
freq_masks=freq_masks,
time_masks=0,
freq_width=freq_width,
time_width=0,
)
else:
self.spec_augment = None