Python get_model_layers示例

示例#1

文件： feature_visualization.py 项目： sjoshi804/hierarchical-darts-neural-architecture-search

# Seed for reproducibility
torch.manual_seed(0)
random.seed(0)

# Device
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

# Constants
NUM_EPOCHS = 50

# Load model from argument
model = torch.load(sys.argv[1])
if torch.cuda.is_available():
    model.cuda()
model.eval()
print(util.get_model_layers(model))
''' Helper Functions'''


def parse_layer(layer):
    if "main_net" in layer:  # FIXME: Need to change for MNAS
        _, _, cell_num, _, edge, _ = tuple(layer.split("_"))
        return int(cell_num), edge
    else:
        raise error("Invalid Layer Name")


@torch.no_grad()
def get_layer(model, layer, X):
    #cell_num, edge = parse_layer(layer)
    hook = render.ModuleHook(model.main_net[0].ops[str((1, 2))].ops[str(

示例#2

def test_inceptionv1_import_layer_repr():
    model = inceptionv1()
    layer_names = util.get_model_layers(model, getLayerRepr=True)
    for layer_name in important_layer_names:
        assert layer_names[layer_name] == 'CatLayer()'

示例#3

文件： utils.py 项目： soumickmj/TorchEsegeta

def get_layers_for_lucent(model):
    print(get_model_layers(model))

示例#4

def test_inceptionv1_graph_import():
    model = inceptionv1()
    layer_names = util.get_model_layers(model)
    for layer_name in important_layer_names:
        assert layer_name in layer_names