qbraid.runtime.schemas.QuboSolveParams
- class QuboSolveParams(**data)[source]
Parameters for solving a QUBO problem using NEC VA algorithm.
- offset
Offset for the normalized weight information stored in the QUBO.
- Type:
float
- num_reads
VA sampling rate. Must be between 1 and 20. Default is 1.
- Type:
Optional[int]
- num_results
Number of VA annealing results. Returns only the optimal solution when 1 or None is specified. Default is 1.
- Type:
Optional[int]
- num_sweeps
Number of VA annealing sweeps. Must be between 1 and 100000. Default is 500.
- Type:
Optional[int]
- beta_range
VA beta value in (start, end, steps) format. Default is (10.0, 100.0, 200).
- Type:
Optional[tuple[float, float, int]]
- beta_list
Beta value array for each VA sweep.
- Type:
Optional[list[float]]
- dense
VA matrix mode. True for dense matrix mode, False for sparse matrix mode. Default is None.
- Type:
Optional[bool]
- vector_mode
Mode during VA annealing. Options are ‘speed’ for speed priority or ‘accuracy’ for accuracy priority. Default is ‘accuracy’.
- Type:
Optional[str]
- timeout
Job execution timeout in seconds. Standard range is between 1 and 7200. Default is 1800.
- Type:
Optional[int]
- ve_num
Number of VEs used in VA annealing. Must be between 1 and the number of VEs installed on each server.
- Type:
Optional[int]
- onehot
VA onehot constraint parameter.
- Type:
Optional[list[str]]
- fixed
VA fixed constraint parameter.
- Type:
Optional[Union[dict[str, int], list[str]]]
- andzero
VA andzero constraint parameter.
- Type:
Optional[list[str]]
- orone
VA orone constraint parameter.
- Type:
Optional[list[str]]
- supplement
VA supplement constraint parameter.
- Type:
Optional[list[str]]
- maxone
VA maxone constraint parameter.
- Type:
Optional[list[str]]
- minmaxone
VA minmaxone constraint parameter.
- Type:
Optional[list[str]]
- init_spin
VA init_spin parameter.
- Type:
Optional[Union[dict[str, int], list[str]]]
- spin_list
VA spin_list parameter.
- Type:
Optional[list[str]]
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- __init__(**data)
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
Methods
__init__(**data)Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])copy(*[, include, exclude, update, deep])Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])from_orm(obj)json(*[, include, exclude, by_alias, ...])model_construct([_fields_set])Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
model_json_schema([by_alias, ref_template, ...])Generates a JSON schema for a model class.
model_parametrized_name(params)Compute the class name for parametrizations of generic classes.
model_post_init(_BaseModel__context)Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])parse_obj(obj)parse_raw(b, *[, content_type, encoding, ...])schema([by_alias, ref_template])schema_json(*[, by_alias, ref_template])update_forward_refs(**localns)validate(value)validate_beta_list(value)Validate the beta_list value.
validate_beta_range(value)Validate the beta_range value.
validate_num_reads(value)Validate the num_reads value.
validate_num_sweeps(value)Validate the num_sweeps value.
validate_offset(value)Validate the offset value.
validate_timeout(value)Validate the timeout value.
validate_ve_num(value)Validate the ve_num value.
validate_vector_mode(value)Validate the vector_mode value.
Attributes
model_computed_fieldsmodel_configConfiguration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extraGet extra fields set during validation.
model_fieldsmodel_fields_setReturns the set of fields that have been explicitly set on this model instance.