本文整理汇总了Python中nolearn.lasagne.NeuralNet.initialize_layers方法的典型用法代码示例。如果您正苦于以下问题：Python NeuralNet.initialize_layers方法的具体用法？Python NeuralNet.initialize_layers怎么用？Python NeuralNet.initialize_layers使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类nolearn.lasagne.NeuralNet的用法示例。
在下文中一共展示了NeuralNet.initialize_layers方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_diamond
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_diamond(self, NeuralNet):
input, hidden1, hidden2, concat, output = (
Mock(), Mock(), Mock(), Mock(), Mock())
nn = NeuralNet(
layers=[
('input', input),
('hidden1', hidden1),
('hidden2', hidden2),
('concat', concat),
('output', output),
],
input_shape=(10, 10),
hidden2_incoming='input',
concat_incoming=['hidden1', 'hidden2'],
)
nn.initialize_layers(nn.layers)
input.assert_called_with(name='input', shape=(10, 10))
hidden1.assert_called_with(incoming=input.return_value, name='hidden1')
hidden2.assert_called_with(incoming=input.return_value, name='hidden2')
concat.assert_called_with(
incoming=[hidden1.return_value, hidden2.return_value],
name='concat'
)
output.assert_called_with(incoming=concat.return_value, name='output')示例2: test_diamond
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_diamond(self, NeuralNet):
input = Mock(__name__='InputLayer', __bases__=(InputLayer,))
hidden1, hidden2, concat, output = [
Mock(__name__='MockLayer', __bases__=(Layer,)) for i in range(4)]
nn = NeuralNet(
layers=[
('input', input),
('hidden1', hidden1),
('hidden2', hidden2),
('concat', concat),
('output', output),
],
input_shape=(10, 10),
hidden2_incoming='input',
concat_incomings=['hidden1', 'hidden2'],
)
nn.initialize_layers(nn.layers)
input.assert_called_with(name='input', shape=(10, 10))
hidden1.assert_called_with(incoming=input.return_value, name='hidden1')
hidden2.assert_called_with(incoming=input.return_value, name='hidden2')
concat.assert_called_with(
incomings=[hidden1.return_value, hidden2.return_value],
name='concat'
)
output.assert_called_with(incoming=concat.return_value, name='output')示例3: test_initialization_legacy_with_unicode_names
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_legacy_with_unicode_names(self, NeuralNet):
# Test whether legacy initialization is triggered; if not,
# raises error.
input = Mock(__name__="InputLayer", __bases__=(InputLayer,))
hidden1, hidden2, output = [Mock(__name__="MockLayer", __bases__=(Layer,)) for i in range(3)]
nn = NeuralNet(
layers=[(u"input", input), (u"hidden1", hidden1), (u"hidden2", hidden2), (u"output", output)],
input_shape=(10, 10),
hidden1_some="param",
)
nn.initialize_layers()示例4: test_initialization_with_mask_input
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_with_mask_input(self, NeuralNet):
nn = NeuralNet(
layers=[
(InputLayer, {'shape': (None, 20, 32), 'name': 'l_in'}),
(InputLayer, {'shape': (None, 20), 'name': 'l_mask'}),
(RecurrentLayer, {'incoming': 'l_in',
'mask_input': 'l_mask',
'num_units': 2,
'name': 'l_rec'}),
])
nn.initialize_layers()
assert nn.layers_['l_rec'].mask_incoming_index == 1示例5: test_initialization_legacy
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_legacy(self, NeuralNet):
input = Mock(__name__='InputLayer', __bases__=(InputLayer,))
hidden1, hidden2, output = [
Mock(__name__='MockLayer', __bases__=(Layer,)) for i in range(3)]
nn = NeuralNet(
layers=[
('input', input),
('hidden1', hidden1),
('hidden2', hidden2),
('output', output),
],
input_shape=(10, 10),
hidden1_some='param',
)
out = nn.initialize_layers(nn.layers)
input.assert_called_with(
name='input', shape=(10, 10))
assert nn.layers_['input'] is input.return_value
hidden1.assert_called_with(
incoming=input.return_value, name='hidden1', some='param')
assert nn.layers_['hidden1'] is hidden1.return_value
hidden2.assert_called_with(
incoming=hidden1.return_value, name='hidden2')
assert nn.layers_['hidden2'] is hidden2.return_value
output.assert_called_with(
incoming=hidden2.return_value, name='output')
assert out[0] is nn.layers_['output']示例6: test_initialization_with_tuples
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_with_tuples(self, NeuralNet):
input = Mock(__name__='InputLayer', __bases__=(InputLayer,))
hidden1, hidden2, output = [
Mock(__name__='MockLayer', __bases__=(Layer,)) for i in range(3)]
nn = NeuralNet(
layers=[
(input, {'shape': (10, 10), 'name': 'input'}),
(hidden1, {'some': 'param', 'another': 'param'}),
(hidden2, {}),
(output, {'name': 'output'}),
],
input_shape=(10, 10),
mock1_some='iwin',
)
out = nn.initialize_layers(nn.layers)
input.assert_called_with(
name='input', shape=(10, 10))
assert nn.layers_['input'] is input.return_value
hidden1.assert_called_with(
incoming=input.return_value, name='mock1',
some='iwin', another='param')
assert nn.layers_['mock1'] is hidden1.return_value
hidden2.assert_called_with(
incoming=hidden1.return_value, name='mock2')
assert nn.layers_['mock2'] is hidden2.return_value
output.assert_called_with(
incoming=hidden2.return_value, name='output')
assert out[0] is nn.layers_['output']示例7: test_initialization_legacy
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_legacy(self, NeuralNet):
input, hidden1, hidden2, output = Mock(), Mock(), Mock(), Mock()
nn = NeuralNet(
layers=[
('input', input),
('hidden1', hidden1),
('hidden2', hidden2),
('output', output),
],
input_shape=(10, 10),
hidden1_some='param',
)
out = nn.initialize_layers(nn.layers)
input.assert_called_with(
name='input', shape=(10, 10))
nn.layers_['input'] is input.return_value
hidden1.assert_called_with(
incoming=input.return_value, name='hidden1', some='param')
nn.layers_['hidden1'] is hidden1.return_value
hidden2.assert_called_with(
incoming=hidden1.return_value, name='hidden2')
nn.layers_['hidden2'] is hidden2.return_value
output.assert_called_with(
incoming=hidden2.return_value, name='output')
assert out is nn.layers_['output']示例8: test_initialization_with_layer_instance
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_with_layer_instance(self, NeuralNet):
layer1 = InputLayer(shape=(128, 13)) # name will be assigned
layer2 = DenseLayer(layer1, name='output', num_units=2) # has name
nn = NeuralNet(layers=layer2)
out = nn.initialize_layers()
assert nn.layers_['output'] == layer2 == out[0]
assert nn.layers_['input0'] == layer1示例9: test_initialization_with_tuples
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_with_tuples(self, NeuralNet):
input = Mock(__name__="InputLayer", __bases__=(InputLayer,))
hidden1, hidden2, output = [Mock(__name__="MockLayer", __bases__=(Layer,)) for i in range(3)]
nn = NeuralNet(
layers=[
(input, {"shape": (10, 10), "name": "input"}),
(hidden1, {"some": "param", "another": "param"}),
(hidden2, {}),
(output, {"name": "output"}),
],
input_shape=(10, 10),
mock1_some="iwin",
)
out = nn.initialize_layers(nn.layers)
input.assert_called_with(name="input", shape=(10, 10))
assert nn.layers_["input"] is input.return_value
hidden1.assert_called_with(incoming=input.return_value, name="mock1", some="iwin", another="param")
assert nn.layers_["mock1"] is hidden1.return_value
hidden2.assert_called_with(incoming=hidden1.return_value, name="mock2")
assert nn.layers_["mock2"] is hidden2.return_value
output.assert_called_with(incoming=hidden2.return_value, name="output")
assert out is nn.layers_["output"]示例10: test_initialization
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization(self, NeuralNet):
input, hidden1, hidden2, output = Mock(), Mock(), Mock(), Mock()
nn = NeuralNet(
layers=[
(input, {'shape': (10, 10), 'name': 'input'}),
(hidden1, {'some': 'param', 'another': 'param'}),
(hidden2, {}),
(output, {'name': 'output'}),
],
input_shape=(10, 10),
mock1_some='iwin',
)
out = nn.initialize_layers(nn.layers)
input.assert_called_with(
name='input', shape=(10, 10))
nn.layers_['input'] is input.return_value
hidden1.assert_called_with(
incoming=input.return_value, name='mock1',
some='iwin', another='param')
nn.layers_['mock1'] is hidden1.return_value
hidden2.assert_called_with(
incoming=hidden1.return_value, name='mock2')
nn.layers_['mock2'] is hidden2.return_value
output.assert_called_with(
incoming=hidden2.return_value, name='output')
assert out is nn.layers_['output']示例11: test_initialization_legacy_with_unicode_names
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initialization_legacy_with_unicode_names(self, NeuralNet):
# Test whether legacy initialization is triggered; if not,
# raises error.
input = Mock(__name__='InputLayer', __bases__=(InputLayer,))
hidden1, hidden2, output = [
Mock(__name__='MockLayer', __bases__=(Layer,)) for i in range(3)]
nn = NeuralNet(
layers=[
(u'input', input),
(u'hidden1', hidden1),
(u'hidden2', hidden2),
(u'output', output),
],
input_shape=(10, 10),
hidden1_some='param',
)
nn.initialize_layers()示例12: test_initializtion_with_tuples_resolve_layers
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initializtion_with_tuples_resolve_layers(self, NeuralNet):
nn = NeuralNet(
layers=[
('lasagne.layers.InputLayer', {'shape': (None, 10)}),
('lasagne.layers.DenseLayer', {'num_units': 33}),
],
)
out, = nn.initialize_layers(nn.layers)
assert out.num_units == 33示例13: test_legacy_initialization_with_mask_input
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_legacy_initialization_with_mask_input(self, NeuralNet):
nn = NeuralNet(
layers=[
('l_in', InputLayer),
('l_mask', InputLayer),
('l_rec', RecurrentLayer),
],
l_in_shape=(None, 20, 32),
l_in_name='l_in',
l_mask_shape=(None, 20),
l_mask_name='l_mask',
l_rec_incoming='l_in',
l_rec_mask_input='l_mask',
l_rec_num_units=2,
l_rec_name='l_rec',
)
nn.initialize_layers()
assert nn.layers_['l_rec'].mask_incoming_index == 1示例14: test_initializtion_legacy_resolve_layers
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_initializtion_legacy_resolve_layers(self, NeuralNet):
nn = NeuralNet(
layers=[
('input', 'lasagne.layers.InputLayer'),
('output', 'lasagne.layers.DenseLayer'),
],
input_shape=(None, 10),
output_num_units=33,
)
out, = nn.initialize_layers(nn.layers)
assert out.num_units == 33示例15: test_diamond
# 需要导入模块: from nolearn.lasagne import NeuralNet [as 别名]
# 或者: from nolearn.lasagne.NeuralNet import initialize_layers [as 别名]
def test_diamond(self, NeuralNet):
input = Mock(__name__="InputLayer", __bases__=(InputLayer,))
hidden1, hidden2, concat, output = [Mock(__name__="MockLayer", __bases__=(Layer,)) for i in range(4)]
nn = NeuralNet(
layers=[
("input", input),
("hidden1", hidden1),
("hidden2", hidden2),
("concat", concat),
("output", output),
],
input_shape=(10, 10),
hidden2_incoming="input",
concat_incomings=["hidden1", "hidden2"],
)
nn.initialize_layers(nn.layers)
input.assert_called_with(name="input", shape=(10, 10))
hidden1.assert_called_with(incoming=input.return_value, name="hidden1")
hidden2.assert_called_with(incoming=input.return_value, name="hidden2")
concat.assert_called_with(incomings=[hidden1.return_value, hidden2.return_value], name="concat")
output.assert_called_with(incoming=concat.return_value, name="output")