Bind current symbol to get an optimized trt executor.

    Parameters
    ----------
    symbol : Symbol
        The symbol you wish to bind, and optimize with TensorRT.

    ctx : Context
        The device context the generated executor to run on.

    all_params : Dict of str->ndarray
        A dictionary of mappings from parameter names to parameter NDArrays.

    type_dict  : Dict of str->numpy.dtype
        Input type dictionary, name->dtype

    stype_dict  : Dict of str->str
        Input storage type dictionary, name->storage_type

    group2ctx : Dict of string to mx.Context
        The dict mapping the `ctx_group` attribute to the context assignment.

    kwargs : Dict of str->shape
        Input shape dictionary, name->shape

    Returns
    -------
    executor : mxnet.Executor
        An optimized TensorRT executor.

def tensorrt_bind(symbol, ctx, all_params, type_dict=None, stype_dict=None, group2ctx=None,
                  **kwargs):
    """Bind current symbol to get an optimized trt executor.

    Parameters
    ----------
    symbol : Symbol
        The symbol you wish to bind, and optimize with TensorRT.

    ctx : Context
        The device context the generated executor to run on.

    all_params : Dict of str->ndarray
        A dictionary of mappings from parameter names to parameter NDArrays.

    type_dict  : Dict of str->numpy.dtype
        Input type dictionary, name->dtype

    stype_dict  : Dict of str->str
        Input storage type dictionary, name->storage_type

    group2ctx : Dict of string to mx.Context
        The dict mapping the `ctx_group` attribute to the context assignment.

    kwargs : Dict of str->shape
        Input shape dictionary, name->shape

    Returns
    -------
    executor : mxnet.Executor
        An optimized TensorRT executor.
    """
    kwargs['shared_buffer'] = all_params
    return symbol.simple_bind(ctx, type_dict=type_dict, stype_dict=stype_dict,
                              group2ctx=group2ctx, **kwargs)