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more loss tests

This commit is contained in:
Eren Golge 2019-11-15 14:30:28 +01:00
parent 8af75cad46
commit 79cca4ac80
2 changed files with 14 additions and 2 deletions
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4
layers/losses.py
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@ -18,7 +18,7 @@ class L1LossMasked(nn.Module):
length: A Variable containing a LongTensor of size (batch,) length: A Variable containing a LongTensor of size (batch,)
which contains the length of each data in a batch. which contains the length of each data in a batch.
Returns: Returns:
loss: An average loss value masked by the length. loss: An average loss value in range [0, 1] masked by the length.
""" """
# mask: (batch, max_len, 1) # mask: (batch, max_len, 1)
target.requires_grad = False target.requires_grad = False
@ -44,7 +44,7 @@ class MSELossMasked(nn.Module):
length: A Variable containing a LongTensor of size (batch,) length: A Variable containing a LongTensor of size (batch,)
which contains the length of each data in a batch. which contains the length of each data in a batch.
Returns: Returns:
loss: An average loss value masked by the length. loss: An average loss value in range [0, 1] masked by the length.
""" """
# mask: (batch, max_len, 1) # mask: (batch, max_len, 1)
target.requires_grad = False target.requires_grad = False

12
tests/test_layers.py
View File

@ -118,6 +118,7 @@ class EncoderTests(unittest.TestCase):
class L1LossMaskedTests(unittest.TestCase): class L1LossMaskedTests(unittest.TestCase):
def test_in_out(self): def test_in_out(self):
# test input == target
layer = L1LossMasked() layer = L1LossMasked()
dummy_input = T.ones(4, 8, 128).float() dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.ones(4, 8, 128).float() dummy_target = T.ones(4, 8, 128).float()
@ -125,11 +126,14 @@ class L1LossMaskedTests(unittest.TestCase):
output = layer(dummy_input, dummy_target, dummy_length) output = layer(dummy_input, dummy_target, dummy_length)
assert output.item() == 0.0 assert output.item() == 0.0
# test input != target
dummy_input = T.ones(4, 8, 128).float() dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float() dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.ones(4) * 8).long() dummy_length = (T.ones(4) * 8).long()
output = layer(dummy_input, dummy_target, dummy_length) output = layer(dummy_input, dummy_target, dummy_length)
assert output.item() == 1.0, "1.0 vs {}".format(output.data[0]) assert output.item() == 1.0, "1.0 vs {}".format(output.data[0])
# test if padded values of input makes any difference
dummy_input = T.ones(4, 8, 128).float() dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float() dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.arange(5, 9)).long() dummy_length = (T.arange(5, 9)).long()
@ -137,3 +141,11 @@ class L1LossMaskedTests(unittest.TestCase):
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2) (sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length) output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 1.0, "1.0 vs {}".format(output.data[0]) assert output.item() == 1.0, "1.0 vs {}".format(output.data[0])
dummy_input = T.rand(4, 8, 128).float()
dummy_target = dummy_input.detach()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 0, "0 vs {}".format(output.data[0])