def init_args_from_config(cls, config): """ :rtype: dict[str] :returns the kwarg for cls.from_json() """ num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) return { "n_in": num_inputs, "n_out": num_outputs, "sparse_input": config.bool("sparse_input", False), "target": config.value('target', 'classes') }
def test_num_inputs_outputs_special_dataset(): config = Config() config.update({ "train": {"class": "CopyTaskDataset", "num_seqs": 1000, "nsymbols": 80, "minlen": 100, "maxlen": 100}, "num_outputs": {"data": [80, 1], "classes": [80, 1]}}) num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) assert_equal(num_inputs, 80) assert_in("data", num_outputs) assert_in("classes", num_outputs) assert_equal(num_outputs["classes"], [80, 1]) assert_equal(num_outputs["data"], [80, 1])
def test_num_inputs_outputs_old(): n_in = 5 n_out = 10 config = Config() config.update({"num_inputs": n_in, "num_outputs": n_out}) num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) assert_equal(num_inputs, n_in) assert_is_instance(num_outputs, dict) assert_equal(len(num_outputs), 1) assert_in("classes", num_outputs) assert_equal(num_outputs["classes"], [n_out, 1])
def test_num_inputs_outputs_special_dataset(): config = Config() config.update({ "train": {"class": "CopyTaskDataset", "num_seqs": 1000, "nsymbols": 80, "minlen": 100, "maxlen": 100}, "num_outputs": {"data": [80, 1], "classes": [80, 1]}}) num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) assert_equal(num_inputs, 80) assert_in("data", num_outputs) assert_in("classes", num_outputs) assert_equal(num_outputs["classes"], [80, 1]) assert_equal(num_outputs["data"], [80, 1])
def test_num_inputs_outputs_old(): n_in = 5 n_out = 10 config = Config() config.update({"num_inputs": n_in, "num_outputs": n_out}) num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) assert_equal(num_inputs, n_in) assert_is_instance(num_outputs, dict) assert_equal(len(num_outputs), 1) assert_in("classes", num_outputs) assert_equal(num_outputs["classes"], [n_out, 1])
def init_args_from_config(cls, config): """ :rtype: dict[str] :returns the kwarg for cls.from_json() """ num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config) return { "n_in": num_inputs, "n_out": num_outputs, "sparse_input": config.bool("sparse_input", False), "target": config.value('target', 'classes') }