def result(
self,
poll_timeout_seconds: float = QuantumJob.DEFAULT_RESULTS_POLL_TIMEOUT,
poll_interval_seconds: float = QuantumJob.
DEFAULT_RESULTS_POLL_INTERVAL,
) -> Dict[str, Any]:
"""Retrieves the job result persisted using save_job_result() function.
Args:
poll_timeout_seconds (float): The polling timeout, in seconds, for `result()`.
Default: 10 days.
poll_interval_seconds (float): The polling interval, in seconds, for `result()`.
Default: 5 seconds.
Returns:
Dict[str, Any]: Dict specifying the job results.
"""
try:
with open(os.path.join(self.name, "results.json"), "r") as f:
persisted_data = PersistedJobData.parse_raw(f.read())
deserialized_data = deserialize_values(
persisted_data.dataDictionary, persisted_data.dataFormat)
return deserialized_data
except FileNotFoundError:
raise ValueError(
f"Unable to find results in the local job directory {self.name}."
)
def _read_and_deserialize_results(temp_dir, job_name):
try:
with open(
f"{temp_dir}/{job_name}/{AwsQuantumJob.RESULTS_FILENAME}",
"r") as f:
persisted_data = PersistedJobData.parse_raw(f.read())
deserialized_data = deserialize_values(
persisted_data.dataDictionary, persisted_data.dataFormat)
return deserialized_data
except FileNotFoundError:
return {}
def load_job_checkpoint(job_name: str,
checkpoint_file_suffix: str = "") -> Dict[str, Any]:
"""
Loads the job checkpoint data stored for the job named 'job_name', with the checkpoint
file that ends with the `checkpoint_file_suffix`. The `job_name` can refer to any job whose
checkpoint data you expect to be available in the file path specified by the `CHECKPOINT_DIR`
container environment variable.
Note: This function for loading job checkpoints is only for use inside the job container
as it writes data to directories and references env variables set in the containers.
Args:
job_name (str): str that specifies the name of the job whose checkpoints
are to be loaded.
checkpoint_file_suffix (str): str specifying the file suffix that is used to
locate the checkpoint file to load. The resulting file name
`f"{job_name}(_{checkpoint_file_suffix}).json"` is used to locate the
checkpoint file. Default: ""
Returns:
Dict[str, Any]: Dict that contains the checkpoint data persisted in the checkpoint file.
Raises:
FileNotFoundError: If the file `f"{job_name}(_{checkpoint_file_suffix})"` could not be found
in the directory specified by the container environment variable `CHECKPOINT_DIR`.
ValueError: If the data stored in the checkpoint file can't be deserialized (possibly due to
corruption).
"""
checkpoint_directory = os.environ["AMZN_BRAKET_CHECKPOINT_DIR"]
checkpoint_file_path = (
f"{checkpoint_directory}/{job_name}_{checkpoint_file_suffix}.json" if
checkpoint_file_suffix else f"{checkpoint_directory}/{job_name}.json")
with open(checkpoint_file_path, "r") as f:
persisted_data = PersistedJobData.parse_raw(f.read())
deserialized_data = deserialize_values(persisted_data.dataDictionary,
persisted_data.dataFormat)
return deserialized_data
def test_job_deserialize_data(data_format, submitted_data,
expected_deserialized_data):
deserialized_data = deserialize_values(submitted_data, data_format)
assert deserialized_data == expected_deserialized_data