def get_output_shape_for(self, input_shape):
if self.output_size is not None:
size = self.output_size
if isinstance(self.output_size, T.Variable):
size = (None, None)
return input_shape[0], self.num_filters, size[0], size[1], size[2]
# If self.output_size is not specified, return the smallest shape
# when called from the constructor, self.crop is still called self.pad:
crop = getattr(self, 'crop', getattr(self, 'pad', None))
crop = crop if isinstance(crop, tuple) else (crop, ) * self.n
batchsize = input_shape[0]
return ((batchsize, self.num_filters) + tuple(
conv_input_length(input, filter, stride, p)
for input, filter, stride, p in zip(
input_shape[2:], self.filter_size, self.stride, crop)))
def test_conv_input_length():
from lasagne.layers.conv import conv_input_length
# using the examples from https://github.com/vdumoulin/conv_arithmetic
# no padding, no strides
assert conv_input_length(2, 3, 1, 'valid') == 4
assert conv_input_length(2, 3, 1, 0) == 4
# padding, no strides
assert conv_input_length(6, 4, 1, 2) == 5
# no padding, strides
assert conv_input_length(2, 3, 2, 0) == 5
# padding, strides
assert conv_input_length(3, 3, 2, 'same') == 5
# full convolution
assert conv_input_length(3, 3, 2, 'full') == 3
with pytest.raises(ValueError) as exc:
conv_input_length(3, 5, 3, '_nonexistent_mode')
assert "Invalid pad: " in exc.value.args[0]
def test_conv_input_length():
from lasagne.layers.conv import conv_input_length
# using the examples from https://github.com/vdumoulin/conv_arithmetic
# no padding, no strides
assert conv_input_length(2, 3, 1, 'valid') == 4
assert conv_input_length(2, 3, 1, 0) == 4
# padding, no strides
assert conv_input_length(6, 4, 1, 2) == 5
# no padding, strides
assert conv_input_length(2, 3, 2, 0) == 5
# padding, strides
assert conv_input_length(3, 3, 2, 'same') == 5
# full convolution
assert conv_input_length(3, 3, 2, 'full') == 3
with pytest.raises(ValueError) as exc:
conv_input_length(3, 5, 3, '_nonexistent_mode')
assert "Invalid pad: " in exc.value.args[0]