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standardizing freq/time axis #401

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standardizing freq/time axis #401

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15c7303
standardizing freq/time axis.
vincentqb Jan 10, 2020
6f16657
update test.
vincentqb Jan 10, 2020
a1ea7df
keep batch, channel, in docstring.
vincentqb Jan 10, 2020
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8 changes: 4 additions & 4 deletions test/test_functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -560,7 +560,7 @@ def test_mask_along_axis(self):
specgram = torch.randn(2, 1025, 400)
mask_param = 100
mask_value = 30.
axis = 2
axis = -1

_test_torchscript_functional(F.mask_along_axis, specgram, mask_param, mask_value, axis)

Expand All @@ -569,7 +569,7 @@ def test_mask_along_axis_iid(self):
specgrams = torch.randn(4, 2, 1025, 400)
mask_param = 100
mask_value = 30.
axis = 2
axis = -2

_test_torchscript_functional(F.mask_along_axis_iid, specgrams, mask_param, mask_value, axis)

Expand Down Expand Up @@ -651,7 +651,7 @@ def test_complex_norm(complex_tensor, power):
])
@pytest.mark.parametrize('mask_param', [100])
@pytest.mark.parametrize('mask_value', [0., 30.])
@pytest.mark.parametrize('axis', [1, 2])
@pytest.mark.parametrize('axis', [-2, -1])
def test_mask_along_axis(specgram, mask_param, mask_value, axis):

mask_specgram = F.mask_along_axis(specgram, mask_param, mask_value, axis)
Expand All @@ -671,7 +671,7 @@ def test_mask_along_axis(specgram, mask_param, mask_value, axis):
])
@pytest.mark.parametrize('mask_param', [100])
@pytest.mark.parametrize('mask_value', [0., 30.])
@pytest.mark.parametrize('axis', [2, 3])
@pytest.mark.parametrize('axis', [-2, -1])
def test_mask_along_axis_iid(specgrams, mask_param, mask_value, axis):

mask_specgrams = F.mask_along_axis_iid(specgrams, mask_param, mask_value, axis)
Expand Down
10 changes: 5 additions & 5 deletions torchaudio/functional.py
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Expand Up @@ -823,13 +823,13 @@ def mask_along_axis_iid(specgrams, mask_param, mask_value, axis):
specgrams (Tensor): Real spectrograms (batch, channel, freq, time)
mask_param (int): Number of columns to be masked will be uniformly sampled from [0, mask_param]
mask_value (float): Value to assign to the masked columns
axis (int): Axis to apply masking on (2 -> frequency, 3 -> time)
axis (int): Axis to apply masking on (-2 -> frequency, -1 -> time)

Returns:
torch.Tensor: Masked spectrograms of dimensions (batch, channel, freq, time)
"""

if axis != 2 and axis != 3:
if axis != -2 and axis != -1:
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@mthrok mthrok May 6, 2020

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nit

Suggested change
if axis != -2 and axis != -1:
if axis not in [-1, -2]:

raise ValueError('Only Frequency and Time masking are supported')
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@mthrok mthrok May 6, 2020

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I feel it a little bit too strict to disallow positive indices, but as long as it is explained in doctoring, I think it's fair.

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@mthrok mthrok May 6, 2020

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oh wait, isn't this BC breaking?


value = torch.rand(specgrams.shape[:2]) * mask_param
Expand Down Expand Up @@ -859,7 +859,7 @@ def mask_along_axis(specgram, mask_param, mask_value, axis):
specgram (Tensor): Real spectrogram (channel, freq, time)
mask_param (int): Number of columns to be masked will be uniformly sampled from [0, mask_param]
mask_value (float): Value to assign to the masked columns
axis (int): Axis to apply masking on (1 -> frequency, 2 -> time)
axis (int): Axis to apply masking on (-2 -> frequency, -1 -> time)

Returns:
torch.Tensor: Masked spectrogram of dimensions (channel, freq, time)
Expand All @@ -876,9 +876,9 @@ def mask_along_axis(specgram, mask_param, mask_value, axis):
mask_end = (min_value.long() + value.long()).squeeze()

assert mask_end - mask_start < mask_param
if axis == 1:
if axis == -2:
specgram[:, mask_start:mask_end] = mask_value
elif axis == 2:
elif axis == -1:
specgram[:, :, mask_start:mask_end] = mask_value
else:
raise ValueError('Only Frequency and Time masking are supported')
Expand Down
6 changes: 3 additions & 3 deletions torchaudio/transforms.py
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Expand Up @@ -556,7 +556,7 @@ def forward(self, specgram, mask_value=0.):

# if iid_masks flag marked and specgram has a batch dimension
if self.iid_masks and specgram.dim() == 4:
return F.mask_along_axis_iid(specgram, self.mask_param, mask_value, self.axis + 1)
return F.mask_along_axis_iid(specgram, self.mask_param, mask_value, self.axis)
else:
return F.mask_along_axis(specgram, self.mask_param, mask_value, self.axis)

Expand All @@ -572,7 +572,7 @@ class FrequencyMasking(_AxisMasking):
"""

def __init__(self, freq_mask_param, iid_masks=False):
super(FrequencyMasking, self).__init__(freq_mask_param, 1, iid_masks)
super(FrequencyMasking, self).__init__(freq_mask_param, -2, iid_masks)


class TimeMasking(_AxisMasking):
Expand All @@ -586,4 +586,4 @@ class TimeMasking(_AxisMasking):
"""

def __init__(self, time_mask_param, iid_masks=False):
super(TimeMasking, self).__init__(time_mask_param, 2, iid_masks)
super(TimeMasking, self).__init__(time_mask_param, -1, iid_masks)