def test_layer_from_shape_valid_get_output(self, layer_from_shape,
get_outputs):
layer = layer_from_shape
inputs = {layer: theano.tensor.matrix()}
assert get_outputs(layer, inputs) == (inputs[layer], )
inputs = {None: theano.tensor.matrix()}
layer.get_outputs_for = Mock()
assert get_outputs(layer, inputs) is layer.get_outputs_for.return_value
layer.get_outputs_for.assert_called_with((inputs[None], ))
def test_get_output_with_unused_kwarg(self, layers, get_outputs):
l1, l2, l3 = layers
l2.get_outputs_for = lambda data, asdf=123, **kwargs: (data, )
unused_kwarg = object()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
get_outputs(l3, kwagg=unused_kwarg)
assert len(w) == 1
assert issubclass(w[0].category, UserWarning)
assert 'perhaps you meant kwarg' in str(w[0].message)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
get_outputs(l3, adsf=unused_kwarg)
assert len(w) == 1
assert issubclass(w[0].category, UserWarning)
assert 'perhaps you meant asdf' in str(w[0].message)
def test_get_output_without_arguments(self, layers, get_outputs):
l1, l2, l3 = layers
output = get_outputs(l3)
# expected: l3.get_output_for(l2.get_output_for(l1.input_var))
assert output == l3.get_outputs_for.return_value
l3.get_outputs_for.assert_called_with(l2.get_outputs_for.return_value)
l2.get_outputs_for.assert_called_with((l1.input_var, ))
def test_get_output_input_is_a_mapping_no_key(self, layers, get_outputs):
l1, l2, l3 = layers
output = get_outputs(l3, {})
# expected: l3.get_output_for(l2.get_output_for(l1.input_var))
assert output == l3.get_outputs_for.return_value
l3.get_outputs_for.assert_called_with(l2.get_outputs_for.return_value)
l2.get_outputs_for.assert_called_with((l1.input_var, ))
def test_get_output_with_single_argument(self, layers, get_outputs):
l1, l2, l3 = layers
inputs, kwarg = theano.tensor.matrix(), object()
output = get_outputs(l3, inputs, kwarg=kwarg)
# expected: l3.get_output_for(l2.get_output_for(inputs, kwarg=kwarg),
# kwarg=kwarg)
assert output == l3.get_outputs_for.return_value
l3.get_outputs_for.assert_called_with(l2.get_outputs_for.return_value,
kwarg=kwarg)
l2.get_outputs_for.assert_called_with((inputs, ), kwarg=kwarg)
def test_get_output_input_is_a_mapping(self, layers, get_outputs):
l1, l2, l3 = layers
p = PropertyMock()
type(l1).input_var = p
inputs = {l3: theano.tensor.matrix()}
# expected: inputs[l3]
assert get_outputs(l3, inputs) == (inputs[l3], )
# l3.get_output_for, l2.get_output_for should not have been called
assert l3.get_output_for.call_count == 0
assert l2.get_output_for.call_count == 0
# l1.input_var should not have been accessed
assert p.call_count == 0
def test_get_output_input_is_a_mapping_to_array(self, layers, get_outputs):
l1, l2, l3 = layers
p = PropertyMock()
type(l1).input_var = p
inputs = {l3: [[1, 2, 3]]}
output = get_outputs(l3, inputs)
# expected: inputs[l3]
assert numpy.all(output[0].eval() == inputs[l3])
# l3.get_output_for, l2.get_output_for should not have been called
assert l3.get_output_for.call_count == 0
assert l2.get_output_for.call_count == 0
# l1.input_var should not have been accessed
assert p.call_count == 0
def test_layer_from_shape_invalid_get_output(self, layer_from_shape,
get_outputs):
layer = layer_from_shape
with pytest.raises(ValueError):
get_outputs(layer)
with pytest.raises(ValueError):
get_outputs(layer, [1, 2])
with pytest.raises(ValueError):
get_outputs(layer, {layer.input_layers[1]: [1, 2]})
def test_get_output_input_is_a_mapping_for_layer(self, layers,
get_outputs):
l1, l2, l3 = layers
p = PropertyMock()
type(l1).input_var = p
input_expr, kwarg = theano.tensor.matrix(), object()
inputs = {l2: input_expr}
output = get_outputs(l3, inputs, kwarg=kwarg)
# expected: l3.get_output_for(input_expr, kwarg=kwarg)
assert output == l3.get_outputs_for.return_value
l3.get_outputs_for.assert_called_with((input_expr, ), kwarg=kwarg)
# l2.get_output_for should not have been called
assert l2.get_outputs_for.call_count == 0
# l1.input_var should not have been accessed
assert p.call_count == 0
def test_get_output_without_arguments(self, layer, get_outputs):
assert get_outputs(layer) == (layer.input_var, )
def test_get_output_with_single_argument_fails(self, layers, get_outputs):
l1, l2, l3 = layers
inputs, kwarg = theano.tensor.matrix(), object()
# expected to fail: only gave one expression for two input layers
with pytest.raises(ValueError):
output = get_outputs(l3, inputs, kwarg=kwarg)
def test_get_output_with_no_unused_kwarg(self, layers, get_outputs):
l1, l2, l3 = layers
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
get_outputs(l3)
assert len(w) == 0
def test_get_output_input_is_a_mapping(self, layer, get_outputs):
inputs = {layer: theano.tensor.matrix()}
assert get_outputs(layer, inputs) == (inputs[layer], )
def test_get_output_input_is_array(self, layer, get_outputs):
inputs = [[1, 2, 3]]
output = get_outputs(layer, inputs)
assert numpy.all(output[0].eval() == inputs)
def test_get_output_input_is_variable(self, layer, get_outputs):
variable = theano.Variable("myvariable")
assert get_outputs(layer, variable) == (variable, )