def test_layers_sequential_from_config():
"""Test from_config on sequential"""
config = {
"type": "deepr.layers.Sequential",
"*": [{"type": "deepr.layers.Dense", "units": 10}, {"type": "deepr.layers.Identity"}],
}
sequential = dpr.from_config(config)
assert [type(layer) for layer in sequential.layers] == [dpr.layers.Dense, dpr.layers.Identity]
def test_example_multiply_configs(tmpdir):
"""Test for examples.multiply.configs"""
path_model = str(tmpdir.join("model"))
path_dataset = str(tmpdir.join("dataset"))
config = dpr.io.read_json(PATH_CONFIG / "config.json")
macros = dpr.io.read_json(PATH_CONFIG / "macros.json")
macros["paths"]["path_model"] = path_model
macros["paths"]["path_dataset"] = path_dataset
parsed = dpr.parse_config(config, macros)
job = dpr.from_config(parsed)
job.run()
def test_layers_dag_from_config():
"""Test from_config on dag"""
config = {
"type":
"deepr.layers.DAG",
"*": [{
"type": "deepr.layers.Dense",
"units": 10
}, {
"type": "deepr.layers.Identity"
}],
}
dag = deepr.from_config(config)
assert [type(layer) for layer in dag.layers
] == [deepr.layers.Dense, deepr.layers.Identity]
def test_prepros_serial_from_config():
"""Test from_config on Serial"""
config = {
"type":
"deepr.prepros.Serial",
"*": [{
"type": "deepr.prepros.Repeat",
"count": 1
}, {
"type": "deepr.prepros.Batch",
"batch_size": 32
}],
}
serial = deepr.from_config(config)
assert [type(prepro) for prepro in serial.preprocessors
] == [deepr.prepros.Repeat, deepr.prepros.Batch]
def test_example_configs():
"""Test for example.configs"""
config = dpr.io.read_json(PATH_CONFIG / "config.json")
macros = dpr.io.read_json(PATH_CONFIG / "macros.json")
parsed = dpr.parse_config(config, macros)
dpr.from_config(parsed)
def test_config_from_config(item, expected):
assert dpr.from_config(item) == expected
def test_config_from_config_constructor(item, kwargs, expected):
constructor = dpr.from_config(item)
instance = constructor(**kwargs)
assert instance == expected
