def test_get_dimension_is_correct(self):
feedforward = FeedForward(input_dim=10,
num_layers=1,
hidden_dims=10,
activations="linear")
encoder = FeedForwardEncoder(feedforward)
assert encoder.get_input_dim() == feedforward.get_input_dim()
assert encoder.get_output_dim() == feedforward.get_output_dim()
def test_feedforward_encoder_exactly_match_feedforward_each_item(self):
feedforward = FeedForward(input_dim=10,
num_layers=1,
hidden_dims=10,
activations=Activation.by_name("linear")())
encoder = FeedForwardEncoder(feedforward)
tensor = torch.randn([2, 3, 10])
output = encoder(tensor)
target = feedforward(tensor)
numpy.testing.assert_array_almost_equal(target.detach().cpu().numpy(),
output.detach().cpu().numpy())
# mask should work
mask = torch.LongTensor([[1, 1, 1], [1, 0, 0]])
output = encoder(tensor, mask)
target = feedforward(tensor) * mask.unsqueeze(dim=-1).float()
numpy.testing.assert_array_almost_equal(target.detach().cpu().numpy(),
output.detach().cpu().numpy())