class_docstr: Instrument interface.
class_docstr_tok: ["Instrument","interface","."]
docstr: Creates a dictionary to initialize the Instrument.
  
  The output dictionary is such that the instruments can be initialized
  as follows:
  ```
  initializer = create_constructor_args(proto_list, **kwargs)
  instruments = [Instrument(**data) for data in initializer.values()]
  ```
  
  The keys of the output dictionary are unique identifiers of the batched
  instruments. This is useful for identifying an existing graph that could be
  reused for the instruments without the need of rebuilding the graph.
  
  Args:
    proto_list: A list of protos for which the initialization arguments are
      constructed.
    **kwargs: Any other keyword args needed by an implementation.
  
  Returns:
    A possibly nested dictionary such that each value provides initialization
    arguments for the Instrument.
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code: def create_constructor_args(
      cls, proto_list: List[types.ProtobufBaseType], **kwargs
  ) -> Dict[str, Any]:
      """Creates a dictionary to initialize the Instrument.
  
      The output dictionary is such that the instruments can be initialized
      as follows:
      ```
      initializer = create_constructor_args(proto_list, **kwargs)
      instruments = [Instrument(**data) for data in initializer.values()]
      ```
  
      The keys of the output dictionary are unique identifiers of the batched
      instruments. This is useful for identifying an existing graph that could be
      reused for the instruments without the need of rebuilding the graph.
  
      Args:
        proto_list: A list of protos for which the initialization arguments are
          constructed.
        **kwargs: Any other keyword args needed by an implementation.
  
      Returns:
        A possibly nested dictionary such that each value provides initialization
        arguments for the Instrument.
      """
      del proto_list, kwargs
      return dict()
  
file_path: tf-quant-finance/tf_quant_finance/experimental/pricing_platform/framework/core/instrument.py
imports: import abc
  from typing import Any, Dict, List
  import tensorflow.compat.v2
  from tf_quant_finance.experimental.pricing_platform.framework.core import processed_market_data
  from tf_quant_finance.experimental.pricing_platform.framework.core import types
label_desc: Use image node_id 2 for calling the Instrument obj's underlying member method code with example usage: obj.create_constructor_args(cls, proto_list) and returns: dict