eqc_direct.client
EqcClient
contains all RPC calls to process, get system status,
and fetch results.
- exception eqc_direct.client.InactiveRpcError[source]
Bases:
Exception
Custom exception wrapper around grpc._channel._InactiveRpcError.
- class eqc_direct.client.EqcResult[source]
Bases:
TypedDict
EQC results object. Will not contain a energy or solution if err_code is not 0.
- Parameters:
err_code – the error code for a given job. Full list of
err_code
values can be foundeqc_direct.utils.JobCodes
err_desc – the error description for a given job submission. Full list of
err_desc
values can be found ineqc_direct.utils.JobCodes
preprocessing_time – data validation and time to re-format input data for running on the device in seconds
runtime – solving time in seconds for Dirac hardware
energy – energy for best solution found (float32 precision)
solution – vector representing the lowest energy solution (float32 precision)
distilled_runtime – runtime for distillation of solutions in seconds
distilled_energy – energy for distilled solution for input polynomial (float32 precision)
distilled_solution – a vector representing the solution after the distillation procedure is applied to the original solution derived from the hardware. (float32 precision)
- Note:
solutions are length n vector of floats that sum to the device constraint
- err_code: int
- err_desc: str
- preprocessing_time: float
- runtime: float
- energy: float | None
- solution: List[float] | None
- distilled_runtime: float | None
- distilled_energy: float | None
- distilled_solution: List[float] | None
- class eqc_direct.client.EqcClient(ip_address: str = 'localhost', port: str = '50051', max_data_size: int = 536870912)[source]
Bases:
object
Provides calls to process jobs using EQC RPC server
- Parameters:
ip_address – The IP address of the RPC server
port – The port that the RPC server is running on
max_data_size – the max send and recieve message length for RPC server
Note
lock_id
is used by a variety of class functions. It is set to an empty string by default since default for device serverlock_id
is also an empty string. This allows for single user processing without having to acquire a device lock.- submit_job(poly_coefficients: ndarray, poly_indices: ndarray, num_variables: int | None = None, lock_id: str = '', sum_constraint: int | float = 10000, relaxation_schedule: int = 2, solution_precision: float | None = None) dict [source]
Submits data to be processed by EQC device
- Parameters:
poly_coefficients – coefficient values for the polynomial to be minimized
poly_indices – list of lists containing polynomial indices associated with coefficient values for problem to be optimized.
num_variables – the number of total variables for the submitted polynomial must not be less than max index in
poly_indices
. If no value is provided then will be set to max value inpoly_indices
.lock_id – a UUID to allow for multi-user processing
sum_constraint – a normalization constraint that is applied to the problem space that is used to calculate
energy
. This parameter will be rounded if exceeds float32 precision (e.g. 7-decimal places). Value must be between 1 and 10000.relaxation_schedule – four different schedules represented in integer parameter. Higher values reduce the variation in the analog spin values and therefore, are more probable to lead to improved objective function energy for input problem. Accepts range of values in set {1, 2, 3, 4}.
solution_precision – the level of precision to apply to the solutions. This parameter will be rounded if exceeds float32 precision (e.g. 7-decimal places). If specified a distillation method is applied to the continuous solutions to map them to the submitted
solution_precision
. Inputsolution_precision
must satisfysolution_precision
greater than or equal tosum_constraint
/10000 in order to be valid. Alsosum_constraint
must be divisible bysolution_precision
. Ifsolution_precision
is not specified no distillation will be applied to the solution derived by the device.
- Returns:
a member of
eqc_direct.utils.JobCodes
as a dict with the following keys:err_code: int- job submission error code
err_desc: str- error code description for submission
- fetch_result(lock_id: str = '') EqcResult [source]
Request last EQC job results. Returns results from the most recent run on the device.
- Parameters:
lock_id – a valid
lock_id
that matches current devicelock_id
- Returns:
an
EqcResult
object
- system_status() dict [source]
Client call to obtain EQC system status
- Returns:
a member of
eqc_direct.utils.SysStatus
as a dict:status_code: int- current system status code
status_desc: str- description of current system status
- acquire_lock() dict [source]
Makes a single attempt to acquire exclusive lock on hardware execution. Locking can be used to ensure orderly processing in multi-user environments. Lock can only be acquired when no other user has acquired the lock or when the system has been idle for 60 seconds while another user has the lock. This idle timeout prevents one user from blocking other users from using the machine even if they are not active.
- Returns:
a member of
eqc_direct.utils.LockManageStatus
as a dict along with an additional keylock_id
:lock_id: str- if acquired the current device lock_id else empty string
status_code: int- status code for lock id acquisition
status_desc: str- a description for the associated status code
- release_lock(lock_id: str = '') dict [source]
Releases exclusive lock for running health check or submitting job
- Parameters:
lock_id – a UUID with currently acquired exclusive device lock
- Returns:
a member of
eqc_direct.utils.LockManageStatus
as a dict:status_code: int- status code for lock id acquisition
status_desc: str- a description for the associated status code
- check_lock(lock_id: str = '') dict [source]
Checks if submitted
lock_id
has execution lock on the device- Parameters:
lock_id – a UUID which will be checked to determine if has exclusive device execution lock
- Returns:
a member of
eqc_direct.utils.LockCheckStatus
as a dict:status_code: int- status code for lock check
status_desc: str- a description for the associated status code
- stop_running_process(lock_id: str = '') dict [source]
Stops a running process either a health check or a Eqc job. Process locks will release automatically based on a timeout which is maintained in the server code if they are not released using this.
- Parameters:
lock_id – requires a lock_id that was acquired by
- Returns:
a member of
eqc_direct.utils.SysStatus
as dict with following keys:status_code: int- the system code after stopping
status_desc: str- the associated system status description
- wait_for_lock() tuple [source]
Waits for lock indefinitely calling
acquire_lock()
- Returns:
a tuple of the following items:
lock_id: str- exclusive lock for device execution with a timeout
start_queue_ts: int- time in ns on which lock was acquired is an int
end_queue_ts: int- time in ns on which queue for lock ended is an int.
- system_version() dict [source]
Provides information regarding Dirac server
- Returns:
a dict with a single item:
server_version: str - the current gRPC server version
- process_job(poly_coefficients: ndarray, poly_indices: ndarray, num_variables: int | None = None, lock_id: str = '', sum_constraint: int | float = 10000, relaxation_schedule: int = 2, solution_precision: float | None = None) dict [source]
- Processes a job by:
Submitting job
Checks for status, until completes or fails
Returns results
- Parameters:
poly_coefficients – coefficient values for the polynomial to be minimized
poly_indices – list of lists containing polynomial indices associated with coefficient values for problem to be optimized.
lock_id – a UUID to allow for multi-user processing
sum_constraint – a normalization constraint that is applied to the problem space that is used to calculate
energy
. This parameter will be rounded if exceeds float32 precision (e.g. 7-decimal places). Value must be between 1 and 10000.relaxation_schedule – four different schedules represented in integer parameter. Higher values reduce the variation in the analog spin values and therefore, are more probable to lead to improved objective function energy for input problem. Accepts range of values in set {1, 2, 3, 4}.
solution_precision – the level of precision to apply to the solutions. This parameter will be rounded if exceeds float32 precision (e.g. 7-decimal places). If specified a distillation method is applied to the continuous solutions to map them to the submitted
solution_precision
. Inputsolution_precision
must satisfysolution_precision
greater than or equal tosum_constraint
/10000 in order to be valid. Alsosum_constraint
must be divisible bysolution_precision
. Ifsolution_precision
is not specified no distillation will be applied to the solution derived by the device.
- Returns:
dict of results and timings with the following keys:
results:
EqcResult
dictstart_job_ts: time in ns marking start of job_submission
end_job_ts: time in ns marking end of job submission complete
eqc_direct.utils
Utilities for running server sim and client
- class eqc_direct.utils.SysStatus[source]
Bases:
object
Status codes for system paired with their descriptions.
- IDLE = {'status_code': 0, 'status_desc': 'IDLE'}
- JOB_RUNNING = {'status_code': 1, 'status_desc': 'JOB_RUNNING'}
- CALIBRATION = {'status_code': 2, 'status_desc': 'CALIBRATION'}
- HEALTH_CHECK = {'status_code': 3, 'status_desc': 'HEALTH_CHECK'}
- HARDWARE_FAILURE = {'status_code': [4, 5, 6, 7], 'status_desc': 'HARDWARE_FAILURE'}
- class eqc_direct.utils.LockCheckStatus[source]
Bases:
object
Statuses codes for checking lock status paired with their descriptions
- AVAILABLE = {'status_code': 0, 'status_desc': 'Lock available'}
- USER_LOCKED = {'status_code': 1, 'status_desc': 'lock_id matches current server lock_id'}
- UNAVAILABLE = {'status_code': 2, 'status_desc': 'Execution lock is in use by another user'}
- class eqc_direct.utils.LockManageStatus[source]
Bases:
object
Statuses and descriptions for acquiring and releasing lock
- SUCCESS = {'status_code': 0, 'status_desc': 'Success'}
- MISMATCH = {'status_code': 1, 'status_desc': 'lock_id does not match current device lock_id'}
- BUSY = {'status_code': 2, 'status_desc': 'Lock currently in use unable to perform operation'}
- class eqc_direct.utils.JobCodes[source]
Bases:
object
Job codes for errors paired with their descriptions
- NORMAL = {'err_code': 0, 'err_desc': 'Success'}
- INDEX_OUT_OF_RANGE = {'err_code': 1, 'err_desc': 'Index in submitted data is out of range for specified number of variables'}
- COEF_INDEX_MISMATCH = {'err_code': 2, 'err_desc': 'Polynomial indices do not match required length for specified coefficient length'}
- DEVICE_BUSY = {'err_code': 3, 'err_desc': 'Device currently processing other request'}
- LOCK_MISMATCH = {'err_code': 4, 'err_desc': "lock_id doesn't match current device lock"}
- HARDWARE_FAILURE = {'err_code': 5, 'err_desc': 'Device failed during execution'}
- INVALID_SUM_CONSTRAINT = {'err_code': 6, 'err_desc': 'Sum constraint must be greater than or equal to 1 and less than or equal to 10000'}
- INVALID_RELAXATION_SCHEDULE = {'err_code': 7, 'err_desc': 'Parameter relaxation_schedule must be in set {1,2,3,4}'}
- USER_INTERRUPT = {'err_code': 8, 'err_desc': 'User sent stop signal before result was returned'}
- EXCEEDS_MAX_SIZE = {'err_code': 9, 'err_desc': 'Exceeds max problem size for device'}
- DECREASING_INDEX = {'err_code': 10, 'err_desc': 'One of specified polynomial indices is not specified in non-decreasing order'}
- INVALID_PRECISION = {'err_code': 11, 'err_desc': 'The input precision exceeds maximum allowed precision for device'}
- DUPLICATE_INDEX = {'err_code': 12, 'err_desc': 'A duplicate polynomial index set was specified for the input polynomial'}
- PRECISION_CONSTRAINT_MISMATCH = {'err_code': 13, 'err_desc': 'Sum constraint must be divisible by solution_precision'}
- PRECISION_NONNEGATIVE = {'err_code': 14, 'err_desc': 'Input solution precision cannot be negative'}
- DEGREE_POSITIVE = {'err_code': 15, 'err_desc': 'Input degree must be greater than 0'}
- NUM_VARIABLES_POSITIVE = {'err_code': 16, 'err_desc': 'Input num_variables must be greater than 0'}
- eqc_direct.utils.message_to_dict(grpc_message) dict [source]
Convert a gRPC message to a dictionary.
- eqc_direct.utils.convert_hamiltonian_to_poly_format(linear_terms: ndarray, quadratic_terms: ndarray) Tuple[List[List[int]], List[float]] [source]
Converts linear terms and quadratic terms of Hamiltonian to polynomial index formatting for Dirac device
- Parameters:
linear_terms – the linear terms for the Hamiltonian 1D length n array
quadratic_terms – the quadratic coefficients of the Hamiltonian (n by n)
- Returns:
a tuple with the following members:
poly_indices: List[List[int]] - polynomial indices in non-decreasing sparse format
poly_coefficients: List[float] - polynomial coefficients in sparse format