Discarded Configurations in Later Versions

INPUT_SHAPE_RANGE

This parameter has been discarded. Do not use it. If the shape range of the model input data needs to be specified, use the INPUT_SHAPE parameter.

Shape range of the input data of a model. This parameter is mutually exclusive with DYNAMIC_BATCH_SIZE, DYNAMIC_IMAGE_SIZE, and DYNAMIC_DIMS.

  • To set the shape range based on node names, the format is "input_name1:[n1,c1,h1,w1];input_name2:[n2,c2,h2,w2]", for example, "input_name1:[8~20,3,5,-1];input_name2:[5,3~9,10,-1]". The specified nodes must be enclosed in double quotation marks ("") and separated by semicolons (;). input_name must be the name of the original node before conversion, and the shape range values must be placed in []. As a best practice, you should set INPUT_SHAPE_RANGE based on data node names.
  • To set the shape range based on node indexes, the format is "[n1,c1,h1,w1],[n2,c2,h2,w2]", for example, "[8~20,3,5,-1],[5,3~9,10,-1]". If node names are not configured, the first pair of brackets ([]) denotes the first input node. Separate the nodes with commas (,). If INPUT_SHAPE_RANGE is set based on the index, the index attribute must be set sequentially from 0 for data nodes.
  • The size of a static dimension is specified by a determinant value. The size range of a dynamic dimension is specified by using a tilde (~). A dynamic dimension without size range specified is denoted by –1.
  • For a scalar input, enclose its shape range in square brackets ([]).
  • In the multi-input scenario, for example, there are three inputs. If only the second and third inputs have the shape range and the first input has a static shape, the static shape must be specified.

SHAPE_GENERALIZED_BUILD_MODE

Shape build mode during graph build. This parameter will be discarded in later versions. Do not use this parameter for new functions.

  • shape_generalized: fuzzy compilation. The system generalizes the runtime dimensions of dynamic-shape operators before compilation.

    This parameter is used when you want to run multiple inferences based on one compilation.

  • shape_precise: precise compilation. The system directly performs compilation based on the specified shape without any escape operations.