def test_collapse_None(self, input_data, input_var, input_layer_with_None):
from lasagne.layers.shape import DimshuffleLayer
ds_ok = DimshuffleLayer(input_layer_with_None, [0, 1, 3, 4])
ds_bad = DimshuffleLayer(input_layer_with_None, [0, 1, 2, 4])
assert ds_ok.get_output_shape() == (2, 3, 5, 7)
assert ds_ok.get_output_for(input_var).eval(
{input_var: input_data}).shape == (2, 3, 5, 7)
with pytest.raises(ValueError):
ds_bad.get_output_shape()
def test_invalid_pattern(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
with pytest.raises(ValueError):
DimshuffleLayer(input_layer, ['q'])
with pytest.raises(ValueError):
DimshuffleLayer(input_layer, [0, 0, 1, 3, 4])
# There is no dimension 42
ds_bad = DimshuffleLayer(input_layer, [0, 1, 2, 4, 42])
with pytest.raises(ValueError):
ds_bad.get_output_shape()
def test_collapse_None(self, input_data, input_var, input_layer_with_None):
from lasagne.layers.shape import DimshuffleLayer
ds_ok = DimshuffleLayer(input_layer_with_None, [0, 1, 3, 4])
ds_bad = DimshuffleLayer(input_layer_with_None, [0, 1, 2, 4])
assert ds_ok.get_output_shape() == (2, 3, 5, 7)
assert ds_ok.get_output_for(input_var).eval({
input_var: input_data
}).shape == (2, 3, 5, 7)
with pytest.raises(ValueError):
ds_bad.get_output_shape()
def test_invalid_pattern(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
with pytest.raises(ValueError):
DimshuffleLayer(input_layer, ['q'])
with pytest.raises(ValueError):
DimshuffleLayer(input_layer, [0, 0, 1, 3, 4])
# There is no dimension 42
ds_bad = DimshuffleLayer(input_layer, [0, 1, 2, 4, 42])
with pytest.raises(ValueError):
ds_bad.get_output_shape()
def test_broadcast(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
ds = DimshuffleLayer(input_layer, [0, 1, 2, 3, 4, 'x'])
assert ds.get_output_shape() == (2, 3, 1, 5, 7, 1)
assert ds.get_output_for(input_var).eval({
input_var: input_data
}).shape == (2, 3, 1, 5, 7, 1)
def test_rearrange(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
ds = DimshuffleLayer(input_layer, [4, 3, 2, 1, 0])
assert ds.get_output_shape() == (7, 5, 1, 3, 2)
assert ds.get_output_for(input_var).eval({
input_var: input_data
}).shape == (7, 5, 1, 3, 2)
def test_broadcast(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
ds = DimshuffleLayer(input_layer, [0, 1, 2, 3, 4, 'x'])
assert ds.get_output_shape() == (2, 3, 1, 5, 7, 1)
assert ds.get_output_for(input_var).eval(
{input_var: input_data}).shape == (2, 3, 1, 5, 7, 1)
def test_rearrange(self, input_data, input_var, input_layer):
from lasagne.layers.shape import DimshuffleLayer
ds = DimshuffleLayer(input_layer, [4, 3, 2, 1, 0])
assert ds.get_output_shape() == (7, 5, 1, 3, 2)
assert ds.get_output_for(input_var).eval(
{input_var: input_data}).shape == (7, 5, 1, 3, 2)