def test_save(self):
self.assertFalse(self.net.layers, "la red tiene capas")
layer = Input(name="input")
self.net.add_layer(layer)
path = self.net.save(self.root_dir)
result = path.open().read_yaml()
expected = {
'name': 'test_save',
'order_layers': ['input'],
'layers': {
'input': {
'batch_size': None,
'input_var': 'int64',
'name': 'input',
'name': 'input',
'shape': [None],
'type': 'chibi_genjuu.network.Input',
}
}
}
self.assertEqual(expected, result)
def setUp(self):
super().setUp()
self.net = Network(name=self._testMethodName)
self.input_layer = Input(
name="input",
shape=(2, ),
)
self.net.add_layer(self.input_layer)
self.softplus = Dense(name="softplus",
input=self.input_layer,
number_units=2,
function_no_liniarity='softplus')
self.sigmoid = Dense(name="sigmoid",
input=self.softplus,
number_units=1,
function_no_liniarity='sigmoid')
self.net.add_layer(self.softplus)
self.net.add_layer(self.sigmoid)
def test_add_layer_input(self):
self.assertFalse(self.net.layers, "la red tiene capas")
layer = Input(name="input")
self.net.add_layer(layer)
self.assertEqual(layer, self.net.layers[layer.name])
def setUp(self):
super().setUp()
self.input_layer = Input(name="input")
self.layer = Dense(name="dense", input=self.input_layer)
def test_from_dict(self):
d = self.layer.dict
result_layer = Input.from_dict(d)
self.assertEqual(result_layer.dict, self.layer.dict)
def test_can_parse_int_for_use_in_the_input_var(self):
self.layer = Input(name="input", input_var='int32')
self.assertEqual(self.layer.type_input_var, 'int32')
def setUp(self):
super().setUp()
self.layer = Input(name="input")