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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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)