class_docstr: A class which describes how to schedule a CascaderGraph as a series of disjoint Plans.
  
  Attributes
  ----------
  graph : CascaderGraph
      The CascaderGraph to which the Proposal applies.
  part_group : FrozenSet[Part]
      The Parts which are covered by the Proposal.
  plans : List[Plan]
      The Plans used in the Proposal.
  input_tensor_configs : Dict[Tensor, TensorConfig]
      The TensorConfigs indexed by Tensor in the Proposal which aren't produced by a Plan.
  cascade_region : MemoryRegion
      The MemoryRegion where cascading buffers should be homed.
  memory_usage : int
      The memory required to execute the Proposal in the cascading MemoryRegion.
  cycles : int
      The estimated cycles taken to execute the Proposal.
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docstr: The TensorConfigs indexed by Tensor in the Proposal which aren't produced by a Plan.
docstr_tok: ["The","TensorConfigs","indexed","by","Tensor","in","the","Proposal","which","are","n't","produced","by","a","Plan","."]
code: def input_tensor_configs(self) -> Dict[Tensor, TensorConfig]:
      """The TensorConfigs indexed by Tensor in the Proposal which aren't produced by a Plan."""
      return dict(self._input_tensor_configs)
  
file_path: tvm/python/tvm/contrib/ethosu/cascader/proposal.py
imports: from typing import Dict, FrozenSet, List
  import tvm._ffi
  from tvm.contrib.ethosu.cascader.plan import Plan
  from tvm.runtime import Object
  from .None import _ffi_api
  from .graph import Tensor, Part, CascaderGraph
  from .tensor_config import TensorConfig, MemoryRegion
label_desc: Use image node_id 5 for calling the Proposal obj's underlying member method code with example usage: obj.input_tensor_configs() and returns: dict