("Type[Transform]", get_transform_type),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment": EncodeDecodeFieldsMap(
python_only=[
"arms_by_signature",
"arms_by_name",
"trial_indices_by_status",
"trials_have_ttl",
]
),
"BatchTrial": EncodeDecodeFieldsMap(
python_only=["experiment"], python_to_encoded={"BaseTrial__status": "status"}
),
"SimpleBenchmarkProblem": EncodeDecodeFieldsMap(encoded_only=["function_name"]),
"GenerationStrategy": EncodeDecodeFieldsMap(
python_only=["uses_registered_models", "seen_trial_indices_by_status"],
encoded_only=["had_initialized_model", "db_id"],
python_to_encoded={"curr": "curr_index"},
),
"GeneratorRun": EncodeDecodeFieldsMap(
encoded_only=["arms", "weights"], python_only=["arm_weight_table"]
),
("SumConstraint", get_sum_constraint1),
("SumConstraint", get_sum_constraint2),
("SyntheticRunner", get_synthetic_runner),
("Type[Transform]", get_transform_type),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment": EncodeDecodeFieldsMap(python_only=["arms_by_signature"]),
"BatchTrial": EncodeDecodeFieldsMap(python_only=["experiment"]),
"SimpleBenchmarkProblem": EncodeDecodeFieldsMap(encoded_only=["function_name"]),
"GenerationStrategy": EncodeDecodeFieldsMap(
python_only=["model", "uses_registered_models"],
encoded_only=["had_initialized_model"],
python_to_encoded={"curr": "curr_index"},
),
"GeneratorRun": EncodeDecodeFieldsMap(
encoded_only=["arms", "weights"], python_only=["arm_weight_table"]
),
"OrderConstraint": EncodeDecodeFieldsMap(
python_only=["bound"],
python_to_encoded={
"lower_parameter": "lower_name",
"upper_parameter": "upper_name",
),
(
"SumConstraint",
get_sum_constraint2,
Encoder.parameter_constraint_to_sqa,
Decoder.parameter_constraint_from_sqa,
),
("Trial", get_trial, Encoder.trial_to_sqa, Decoder.trial_from_sqa),
]
# This map records discrepancies between Python and SQA representations,
# so that we can validate that the SQA representation is complete
ENCODE_DECODE_FIELD_MAPS = {
"AbandonedArm":
EncodeDecodeFieldsMap(python_to_encoded={
"reason": "abandoned_reason",
"time": "time_abandoned"
}),
"Arm":
EncodeDecodeFieldsMap(encoded_only=["weight"],
python_to_encoded={"parameters": "parameters"}),
"BatchTrial":
EncodeDecodeFieldsMap(
python_to_encoded={
"generator_run_structs": "generator_runs",
"abandoned_arms_metadata": "abandoned_arms",
"num_arms_created": "num_arms_created",
},
python_only=["experiment", "status_quo", "status_quo_weight"],
encoded_only=["is_batch", "status_quo_name"],
),
"BraninObjective":
("Type[Transform]", get_transform_type),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment":
EncodeDecodeFieldsMap(python_only=[
"arms_by_signature",
"arms_by_name",
"trial_indices_by_status",
"trials_have_ttl",
]),
"BatchTrial":
EncodeDecodeFieldsMap(python_only=["experiment"],
python_to_encoded={"BaseTrial__status": "status"}),
"SimpleBenchmarkProblem":
EncodeDecodeFieldsMap(encoded_only=["function_name"]),
"GenerationStrategy":
EncodeDecodeFieldsMap(
python_only=["uses_registered_models", "seen_trial_indices_by_status"],
encoded_only=["had_initialized_model", "db_id"],
python_to_encoded={"curr": "curr_index"},
),
"GeneratorRun":
EncodeDecodeFieldsMap(encoded_only=["arms", "weights"],
),
(
"SumConstraint",
get_sum_constraint2,
Encoder.parameter_constraint_to_sqa,
Decoder.parameter_constraint_from_sqa,
),
("Trial", get_trial, Encoder.trial_to_sqa, Decoder.trial_from_sqa),
]
# This map records discrepancies between Python and SQA representations,
# so that we can validate that the SQA representation is complete
ENCODE_DECODE_FIELD_MAPS = {
"Metric":
EncodeDecodeFieldsMap(encoded_only={
"scalarized_objective_children_metrics",
"scalarized_objective_weight",
}),
"AbandonedArm":
EncodeDecodeFieldsMap(python_to_encoded={
"reason": "abandoned_reason",
"time": "time_abandoned"
}),
"Arm":
EncodeDecodeFieldsMap(encoded_only=["weight"],
python_to_encoded={"parameters": "parameters"}),
"BatchTrial":
EncodeDecodeFieldsMap(
python_to_encoded={
"generator_run_structs": "generator_runs",
"abandoned_arms_metadata": "abandoned_arms",
"num_arms_created": "num_arms_created",
("SumConstraint", get_sum_constraint2),
("SyntheticRunner", get_synthetic_runner),
("Type[Transform]", get_transform_type),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment":
EncodeDecodeFieldsMap(python_only=["arms_by_signature"]),
"BatchTrial":
EncodeDecodeFieldsMap(python_only=["experiment"]),
"GenerationStrategy":
EncodeDecodeFieldsMap(
python_only=["model", "uses_registered_models"],
encoded_only=["had_initialized_model"],
python_to_encoded={"curr": "curr_index"},
),
"GeneratorRun":
EncodeDecodeFieldsMap(encoded_only=["arms", "weights"],
python_only=["arm_weight_table"]),
"OrderConstraint":
EncodeDecodeFieldsMap(
python_only=["bound"],
python_to_encoded={
("SumConstraint", get_sum_constraint1),
("SumConstraint", get_sum_constraint2),
("SyntheticRunner", get_synthetic_runner),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment":
EncodeDecodeFieldsMap(python_only=["arms_by_signature"]),
"BatchTrial":
EncodeDecodeFieldsMap(python_only=["experiment"]),
"GeneratorRun":
EncodeDecodeFieldsMap(encoded_only=["arms", "weights"],
python_only=["arm_weight_table"]),
"OrderConstraint":
EncodeDecodeFieldsMap(
python_only=["bound"],
python_to_encoded={
"lower_parameter": "lower_name",
"upper_parameter": "upper_name",
},
),
"SimpleExperiment":
EncodeDecodeFieldsMap(
),
(
"SumConstraint",
get_sum_constraint2,
Encoder.parameter_constraint_to_sqa,
Decoder.parameter_constraint_from_sqa,
),
("Trial", get_trial, Encoder.trial_to_sqa, Decoder.trial_from_sqa),
]
# This map records discrepancies between Python and SQA representations,
# so that we can validate that the SQA representation is complete
ENCODE_DECODE_FIELD_MAPS = {
"AbandonedArm": EncodeDecodeFieldsMap(
python_to_encoded={"reason": "abandoned_reason", "time": "time_abandoned"}
),
"Arm": EncodeDecodeFieldsMap(
encoded_only=["weight"], python_to_encoded={"parameters": "parameters"}
),
"BatchTrial": EncodeDecodeFieldsMap(
python_to_encoded={
"generator_run_structs": "generator_runs",
"abandoned_arms_metadata": "abandoned_arms",
"num_arms_created": "num_arms_created",
},
python_only=["experiment", "status_quo", "status_quo_weight_override"],
encoded_only=["is_batch", "status_quo_name", "deployed_name"],
),
"BraninObjective": EncodeDecodeFieldsMap(
python_only=["metric"],
("SimpleExperiment", get_simple_experiment),
("SumConstraint", get_sum_constraint1),
("SumConstraint", get_sum_constraint2),
("SyntheticRunner", get_synthetic_runner),
("Trial", get_trial),
]
# This map records discrepancies between Python and JSON representations,
# so that we can validate that the JSON representation is complete
# -- Sometimes a field appears in the Python object but not the JSON
# (because it is not strictly necessary to store)
# -- Sometimes a field appears in both places but with different names
# (because the name used by JSON is the name used by the constructor,
# might not be the same used by the attribute)
ENCODE_DECODE_FIELD_MAPS = {
"Experiment": EncodeDecodeFieldsMap(python_only=["arms_by_signature"]),
"BatchTrial": EncodeDecodeFieldsMap(python_only=["experiment"]),
"GeneratorRun": EncodeDecodeFieldsMap(
encoded_only=["arms", "weights"], python_only=["arm_weight_table"]
),
"OrderConstraint": EncodeDecodeFieldsMap(
python_only=["bound"],
python_to_encoded={
"lower_parameter": "lower_name",
"upper_parameter": "upper_name",
},
),
"SimpleExperiment": EncodeDecodeFieldsMap(
python_only=["arms_by_signature", "evaluation_function"]
),
"SumConstraint": EncodeDecodeFieldsMap(