Source code for braket.tasks.photonic_model_quantum_task_result

# Copyright Amazon.com Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
#     http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.

from __future__ import annotations

from dataclasses import dataclass

import numpy as np

from braket.task_result import AdditionalMetadata, PhotonicModelTaskResult, TaskMetadata


[docs] @dataclass class PhotonicModelQuantumTaskResult: task_metadata: TaskMetadata additional_metadata: AdditionalMetadata measurements: np.ndarray = None def __eq__(self, other: PhotonicModelQuantumTaskResult) -> bool: if isinstance(other, PhotonicModelQuantumTaskResult): return self.task_metadata.id == other.task_metadata.id return NotImplemented
[docs] @staticmethod def from_object(result: PhotonicModelTaskResult) -> PhotonicModelQuantumTaskResult: """Create PhotonicModelQuantumTaskResult from PhotonicModelTaskResult object. Args: result (PhotonicModelTaskResult): PhotonicModelTaskResult object Returns: PhotonicModelQuantumTaskResult: A PhotonicModelQuantumTaskResult based on the given dict Raises: ValueError: If "measurements" is not a key in the result dict """ return PhotonicModelQuantumTaskResult._from_object_internal(result)
[docs] @staticmethod def from_string(result: str) -> PhotonicModelQuantumTaskResult: return PhotonicModelQuantumTaskResult._from_object_internal( PhotonicModelTaskResult.parse_raw(result) )
@classmethod def _from_object_internal( cls, result: PhotonicModelTaskResult ) -> PhotonicModelQuantumTaskResult: task_metadata = result.taskMetadata additional_metadata = result.additionalMetadata if result.measurements is not None: measurements = np.asarray(result.measurements, dtype=int) else: measurements = None return cls( task_metadata=task_metadata, additional_metadata=additional_metadata, measurements=measurements, )