def METHOD_NAME(self, name: str, input: dict, filter: dict, bias: dict, padding: str,
               stride: dict, dilation: dict, output: dict, fused_act: str):
    """
    Called after Conv2D layer execution
    name: output tensor name (string)
    opcode: opcode name (string)
    input: Tensor
    filter: Tensor
    bias: Tensor
    padding: Padding (string)
    stride: Stride
    dilation: Dilation
    output: Tensor
    fused_act: Fused activation functions (string)
    """
    print("name", name)
    print("input", input)
    print("filter", filter)
    print("bias", bias)
    print("padding", padding)
    print("stride", stride)
    print("dilation", dilation)
    print("output shape", output['data'].shape)
    print("output type", output['data'].dtype)
    print("fused activation", fused_act)