Function C2f

models/api.py:98–128

(
    network: trt.INetworkDefinition,
    weights: OrderedDict,
    input: trt.ITensor,
    cout: int,
    n: int,
    shortcut: bool,
    group: int,
    scale: float,
    layer_name: str,
)

def C2f(
    network: trt.INetworkDefinition,
    weights: OrderedDict,
    input: trt.ITensor,
    cout: int,
    n: int,
    shortcut: bool,
    group: int,
    scale: float,
    layer_name: str,
) -> trt.ILayer:
    c_ = int(cout * scale)  # e:expand param
    conv1 = Conv(network, weights, input, 2 * c_, 1, 1, 1, layer_name + ".cv1")
    y1 = conv1.get_output(0)

    b, _, h, w = y1.shape
    slice = network.add_slice(y1, (0, c_, 0, 0), (b, c_, h, w), (1, 1, 1, 1))
    assert slice, "Add slice layer failed"
    y2 = slice.get_output(0)

    input_tensors = [y1]
    for i in range(n):
        b = Bottleneck(network, weights, y2, c_, c_, shortcut, group, 1.0, layer_name + ".m." + str(i))
        y2 = b.get_output(0)
        input_tensors.append(y2)

    cat = network.add_concatenation(input_tensors)
    assert cat, "Add concatenation layer failed"

    conv2 = Conv(network, weights, cat.get_output(0), cout, 1, 1, 1, layer_name + ".cv2")
    return conv2


def SPPF(