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Add padding direction #2121

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Add padding direction #2121

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152c0fb
Add padding direction
smsm8898 Mar 14, 2023
16edbd1
Add padding direction
smsm8898 Mar 14, 2023
bb1f1c0
follow flake8 and name
smsm8898 Mar 21, 2023
4846f9b
Add PadTransform Unittest - begin, end
smsm8898 Mar 21, 2023
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80 changes: 56 additions & 24 deletions test/torchtext_unittest/test_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -218,42 +218,74 @@ def _pad_transform(self, test_scripting):

input_1d_tensor = torch.ones(5)
input_2d_tensor = torch.ones((8, 5))
pad_long = transforms.PadTransform(max_length=7, pad_value=0)
pad_long_end = PadTransform(max_length=7, pad_value=0, begin=False)
pad_long_begin = PadTransform(max_length=7, pad_value=0, begin=True)
if test_scripting:
pad_long = torch.jit.script(pad_long)
padded_1d_tensor_actual = pad_long(input_1d_tensor)
padded_1d_tensor_expected = torch.cat([torch.ones(5), torch.zeros(2)])
pad_long_end = torch.jit.script(pad_long_end)
pad_long_begin = torch.jit.script(pad_long_begin)
padded_1d_tensor_actual_end = pad_long_end(input_1d_tensor)
padded_1d_tensor_expected_end = torch.cat([torch.ones(5), torch.zeros(2)])
torch.testing.assert_close(
padded_1d_tensor_actual,
padded_1d_tensor_expected,
msg=f"actual: {padded_1d_tensor_actual}, expected: {padded_1d_tensor_expected}",
padded_1d_tensor_actual_end,
padded_1d_tensor_expected_end,
msg=f"actual: {padded_1d_tensor_actual_end}, expected: {padded_1d_tensor_expected_end}",
)
padded_1d_tensor_actual_begin = pad_long_begin(input_1d_tensor)
padded_1d_tensor_expected_begin = torch.cat([torch.zeros(2), torch.ones(5)])
torch.testing.assert_close(
padded_1d_tensor_actual_begin,
padded_1d_tensor_expected_begin,
msg=f"actual: {padded_1d_tensor_actual_begin}, expected: {padded_1d_tensor_expected_begin}",
)

padded_2d_tensor_actual = pad_long(input_2d_tensor)
padded_2d_tensor_expected = torch.cat([torch.ones(8, 5), torch.zeros(8, 2)], axis=-1)
padded_2d_tensor_actual_end = pad_long_end(input_2d_tensor)
padded_2d_tensor_expected_end = torch.cat([torch.ones(8, 5), torch.zeros(8, 2)], axis=-1)
torch.testing.assert_close(
padded_2d_tensor_actual_end,
padded_2d_tensor_expected_end,
msg=f"actual: {padded_2d_tensor_actual_end}, expected: {padded_2d_tensor_expected_end}",
)
padded_2d_tensor_actual_begin = pad_long_begin(input_2d_tensor)
padded_2d_tensor_expected_begin = torch.cat([torch.zeros(8, 2), torch.ones(8, 5),], axis=-1)
torch.testing.assert_close(
padded_2d_tensor_actual,
padded_2d_tensor_expected,
msg=f"actual: {padded_2d_tensor_actual}, expected: {padded_2d_tensor_expected}",
padded_2d_tensor_actual_begin,
padded_2d_tensor_expected_begin,
msg=f"actual: {padded_2d_tensor_actual_begin}, expected: {padded_2d_tensor_expected_begin}",
)

pad_short = transforms.PadTransform(max_length=3, pad_value=0)
pad_short_end = PadTransform(max_length=3, pad_value=0)
pad_short_begin = PadTransform(max_length=3, pad_value=0, begin=True)
if test_scripting:
pad_short = torch.jit.script(pad_short)
padded_1d_tensor_actual = pad_short(input_1d_tensor)
padded_1d_tensor_expected = input_1d_tensor
pad_short_end = torch.jit.script(pad_short_end)
pad_short_begin = torch.jit.script(pad_short_begin)
padded_1d_tensor_actual_end = pad_short_end(input_1d_tensor)
padded_1d_tensor_expected_end = input_1d_tensor
torch.testing.assert_close(
padded_1d_tensor_actual,
padded_1d_tensor_expected,
msg=f"actual: {padded_1d_tensor_actual}, expected: {padded_1d_tensor_expected}",
padded_1d_tensor_actual_end,
padded_1d_tensor_expected_end,
msg=f"actual: {padded_1d_tensor_actual_end}, expected: {padded_1d_tensor_expected_end}",
)
padded_1d_tensor_actual_begin = pad_short_begin(input_1d_tensor)
padded_1d_tensor_expected_begin = input_1d_tensor
torch.testing.assert_close(
padded_1d_tensor_actual_begin,
padded_1d_tensor_expected_begin,
msg=f"actual: {padded_1d_tensor_actual_begin}, expected: {padded_1d_tensor_expected_begin}",
)

padded_2d_tensor_actual = pad_short(input_2d_tensor)
padded_2d_tensor_expected = input_2d_tensor
padded_2d_tensor_actual_end = pad_short_end(input_2d_tensor)
padded_2d_tensor_expected_end = input_2d_tensor
torch.testing.assert_close(
padded_2d_tensor_actual_end,
padded_2d_tensor_expected_end,
msg=f"actual: {padded_2d_tensor_actual_end}, expected: {padded_2d_tensor_expected_end}",
)
padded_2d_tensor_actual_begin = pad_short_begin(input_2d_tensor)
padded_2d_tensor_expected_begin = input_2d_tensor
torch.testing.assert_close(
padded_2d_tensor_actual,
padded_2d_tensor_expected,
msg=f"actual: {padded_2d_tensor_actual}, expected: {padded_2d_tensor_expected}",
padded_2d_tensor_actual_begin,
padded_2d_tensor_expected_begin,
msg=f"actual: {padded_2d_tensor_actual_begin}, expected: {padded_2d_tensor_expected_begin}",
)

def test_pad_transform(self) -> None:
Expand Down
12 changes: 9 additions & 3 deletions torchtext/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -237,13 +237,16 @@ class PadTransform(Module):
:param max_length: Maximum length to pad to
:type max_length: int
:param pad_value: Value to pad the tensor with
:type pad_value: bool
:type pad_value: int
:param begin: Whether to insert pad_value at start or end, defaults to False
:type begin: bool
"""

def __init__(self, max_length: int, pad_value: int) -> None:
def __init__(self, max_length: int, pad_value: int, begin: bool = False) -> None:
super().__init__()
self.max_length = max_length
self.pad_value = float(pad_value)
self.begin = begin

def forward(self, x: Tensor) -> Tensor:
"""
Expand All @@ -255,7 +258,10 @@ def forward(self, x: Tensor) -> Tensor:
max_encoded_length = x.size(-1)
if max_encoded_length < self.max_length:
pad_amount = self.max_length - max_encoded_length
x = torch.nn.functional.pad(x, (0, pad_amount), value=self.pad_value)
if self.begin:
x = torch.nn.functional.pad(x, (pad_amount, 0), value=self.pad_value)
else:
x = torch.nn.functional.pad(x, (0, pad_amount), value=self.pad_value)
return x


Expand Down