def test_search_registered_models(mock_store):
mock_store.search_registered_models.return_value = PagedList(
[RegisteredModel("Model 1"), RegisteredModel("Model 2")], ""
)
result = newModelRegistryClient().search_registered_models(filter_string="test filter")
mock_store.search_registered_models.assert_called_with("test filter", 100, None, None)
assert len(result) == 2
assert result.token == ""
result = newModelRegistryClient().search_registered_models(
filter_string="another filter",
max_results=12,
order_by=["A", "B DESC"],
page_token="next one",
)
mock_store.search_registered_models.assert_called_with(
"another filter", 12, ["A", "B DESC"], "next one"
)
assert len(result) == 2
assert result.token == ""
mock_store.search_registered_models.return_value = PagedList(
[RegisteredModel("model A"), RegisteredModel("Model zz"), RegisteredModel("Model b")],
"page 2 token",
)
result = newModelRegistryClient().search_registered_models(max_results=5)
mock_store.search_registered_models.assert_called_with(None, 5, None, None)
assert [rm.name for rm in result] == ["model A", "Model zz", "Model b"]
assert result.token == "page 2 token"
def test_list_run_infos():
experiment_id = mock.Mock()
view_type = mock.Mock()
run_infos = [mock.Mock(), mock.Mock()]
runs = [mock.Mock(info=info) for info in run_infos]
token = "adfoiweroh12334kj129318934u"
with mock.patch.object(
AbstractStoreTestImpl, "search_runs", return_value=PagedList(runs, token)
):
store = AbstractStoreTestImpl()
result = store.list_run_infos(experiment_id, view_type)
for i in range(len(result)):
assert result[i] == run_infos[i]
assert result.token == token
store.search_runs.assert_called_once_with(
[experiment_id], None, view_type, SEARCH_MAX_RESULTS_DEFAULT, None, None
)
run_infos = [mock.Mock()]
runs = [mock.Mock(info=info) for info in run_infos]
with mock.patch.object(
AbstractStoreTestImpl, "search_runs", return_value=PagedList(runs, None)
):
store = AbstractStoreTestImpl()
result = store.list_run_infos(experiment_id, view_type, page_token=token)
for i in range(len(result)):
assert result[i] == run_infos[i]
assert result.token is None
store.search_runs.assert_called_once_with(
[experiment_id], None, view_type, SEARCH_MAX_RESULTS_DEFAULT, None, token
)
def test_search_registered_models(mock_get_request_message, mock_model_registry_store):
rmds = [
RegisteredModel(
name="model_1",
creation_timestamp=111,
last_updated_timestamp=222,
description="Test model",
latest_versions=[],
),
RegisteredModel(
name="model_2",
creation_timestamp=111,
last_updated_timestamp=333,
description="Another model",
latest_versions=[],
),
]
mock_get_request_message.return_value = SearchRegisteredModels()
mock_model_registry_store.search_registered_models.return_value = PagedList(rmds, None)
resp = _search_registered_models()
_, args = mock_model_registry_store.search_registered_models.call_args
assert args == {"filter_string": "", "max_results": 100, "order_by": [], "page_token": ""}
assert json.loads(resp.get_data()) == {"registered_models": jsonify(rmds)}
mock_get_request_message.return_value = SearchRegisteredModels(filter="hello")
mock_model_registry_store.search_registered_models.return_value = PagedList(rmds[:1], "tok")
resp = _search_registered_models()
_, args = mock_model_registry_store.search_registered_models.call_args
assert args == {"filter_string": "hello", "max_results": 100, "order_by": [], "page_token": ""}
assert json.loads(resp.get_data()) == {
"registered_models": jsonify(rmds[:1]),
"next_page_token": "tok",
}
mock_get_request_message.return_value = SearchRegisteredModels(filter="hi", max_results=5)
mock_model_registry_store.search_registered_models.return_value = PagedList([rmds[0]], "tik")
resp = _search_registered_models()
_, args = mock_model_registry_store.search_registered_models.call_args
assert args == {"filter_string": "hi", "max_results": 5, "order_by": [], "page_token": ""}
assert json.loads(resp.get_data()) == {
"registered_models": jsonify([rmds[0]]),
"next_page_token": "tik",
}
mock_get_request_message.return_value = SearchRegisteredModels(
filter="hey", max_results=500, order_by=["a", "B desc"], page_token="prev"
)
mock_model_registry_store.search_registered_models.return_value = PagedList(rmds, "DONE")
resp = _search_registered_models()
_, args = mock_model_registry_store.search_registered_models.call_args
assert args == {
"filter_string": "hey",
"max_results": 500,
"order_by": ["a", "B desc"],
"page_token": "prev",
}
assert json.loads(resp.get_data()) == {
"registered_models": jsonify(rmds),
"next_page_token": "DONE",
}
def _list_experiments(
self,
ids=None,
names=None,
view_type=ViewType.ACTIVE_ONLY,
max_results=None,
page_token=None,
eager=False,
):
"""
:param eager: If ``True``, eagerly loads each experiments's tags. If ``False``, these tags
are not eagerly loaded and will be loaded if/when their corresponding
object properties are accessed from a resulting ``SqlExperiment`` object.
"""
stages = LifecycleStage.view_type_to_stages(view_type)
conditions = [SqlExperiment.lifecycle_stage.in_(stages)]
if ids and len(ids) > 0:
int_ids = [int(eid) for eid in ids]
conditions.append(SqlExperiment.experiment_id.in_(int_ids))
if names and len(names) > 0:
conditions.append(SqlExperiment.name.in_(names))
max_results_for_query = None
if max_results is not None:
max_results_for_query = max_results + 1
def compute_next_token(current_size):
next_token = None
if max_results_for_query == current_size:
final_offset = offset + max_results
next_token = SearchUtils.create_page_token(final_offset)
return next_token
with self.ManagedSessionMaker() as session:
query_options = self._get_eager_experiment_query_options(
) if eager else []
if max_results is not None:
offset = SearchUtils.parse_start_offset_from_page_token(
page_token)
queried_experiments = (session.query(SqlExperiment).options(
*query_options).order_by(
SqlExperiment.experiment_id).filter(
*conditions).offset(offset).limit(
max_results_for_query).all())
else:
queried_experiments = (session.query(SqlExperiment).options(
*query_options).filter(*conditions).all())
experiments = [
exp.to_mlflow_entity() for exp in queried_experiments
]
if max_results is not None:
return PagedList(experiments[:max_results],
compute_next_token(len(experiments)))
else:
return PagedList(experiments, None)
def test_paginate_lt_maxresults_multipage():
"""
Number of runs is less than max_results, but multiple pages are necessary to get all runs
"""
tokenized_runs = PagedList([create_run() for _ in range(10)], "token")
no_token_runs = PagedList([create_run()], "")
max_results = 50
max_per_page = 10
mocked_lambda = mock.Mock(side_effect=[tokenized_runs, tokenized_runs, no_token_runs])
TOTAL_RUNS = 21
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
assert len(paginated_runs) == TOTAL_RUNS
def test_get_paginated_runs_lt_maxresults_multipage():
"""
Number of runs is less than max_results, but multiple pages are necessary to get all runs
"""
tokenized_runs = PagedList([create_run() for i in range(10)], "token")
no_token_runs = PagedList([create_run()], "")
max_results = 50
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 10):
with mock.patch.object(MlflowClient, "search_runs"):
MlflowClient.search_runs.side_effect = [tokenized_runs, tokenized_runs, no_token_runs]
TOTAL_RUNS = 21
paginated_runs = _get_paginated_runs([], "", ViewType.ACTIVE_ONLY, max_results, None)
assert len(paginated_runs) == TOTAL_RUNS
def list_experiments(
self,
view_type=ViewType.ACTIVE_ONLY,
max_results=None,
page_token=None,
):
"""
:param view_type: Qualify requested type of experiments.
:param max_results: If passed, specifies the maximum number of experiments desired. If not
passed, all experiments will be returned.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``list_experiments`` call.
:return: A :py:class:`PagedList <mlflow.store.entities.PagedList>` of
:py:class:`Experiment <mlflow.entities.Experiment>` objects. The pagination token
for the next page can be obtained via the ``token`` attribute of the object.
"""
from mlflow.utils.search_utils import SearchUtils
from mlflow.store.entities.paged_list import PagedList
_validate_list_experiments_max_results(max_results)
self._check_root_dir()
rsl = []
if view_type == ViewType.ACTIVE_ONLY or view_type == ViewType.ALL:
rsl += self._get_active_experiments(full_path=False)
if view_type == ViewType.DELETED_ONLY or view_type == ViewType.ALL:
rsl += self._get_deleted_experiments(full_path=False)
experiments = []
for exp_id in rsl:
try:
# trap and warn known issues, will raise unexpected exceptions to caller
experiment = self._get_experiment(exp_id, view_type)
if experiment:
experiments.append(experiment)
except MissingConfigException as rnfe:
# Trap malformed experiments and log warnings.
logging.warning(
"Malformed experiment '%s'. Detailed error %s",
str(exp_id),
str(rnfe),
exc_info=True,
)
if max_results is not None:
experiments, next_page_token = SearchUtils.paginate(
experiments, page_token, max_results
)
return PagedList(experiments, next_page_token)
else:
return PagedList(experiments, None)
def list_run_infos(
self,
experiment_id,
run_view_type,
max_results=SEARCH_MAX_RESULTS_DEFAULT,
order_by=None,
page_token=None,
):
"""
Return run information for runs which belong to the experiment_id.
:param experiment_id: The experiment id which to search
:param run_view_type: ACTIVE_ONLY, DELETED_ONLY, or ALL runs
:param max_results: Maximum number of results desired.
:param order_by: List of order_by clauses.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``list_run_infos`` call.
:return: A list of :py:class:`mlflow.entities.RunInfo` objects that satisfy the
search expressions. The pagination token for the next page can be obtained via the
``token`` attribute of the object; however, some store implementations may not support
pagination and thus the returned token would not be meaningful in such cases.
"""
search_result = self.search_runs([experiment_id], None, run_view_type,
max_results, order_by, page_token)
return PagedList([run.info for run in search_result],
search_result.token)
def search_runs(
self,
experiment_ids,
filter_string,
run_view_type,
max_results=SEARCH_MAX_RESULTS_DEFAULT,
order_by=None,
page_token=None,
):
"""
Return runs that match the given list of search expressions within the experiments.
:param experiment_ids: List of experiment ids to scope the search
:param filter_string: A search filter string.
:param run_view_type: ACTIVE_ONLY, DELETED_ONLY, or ALL runs
:param max_results: Maximum number of runs desired.
:param order_by: List of order_by clauses.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``search_runs`` call.
:return: A list of :py:class:`mlflow.entities.Run` objects that satisfy the search
expressions. The pagination token for the next page can be obtained via the ``token``
attribute of the object; however, some store implementations may not support pagination
and thus the returned token would not be meaningful in such cases.
"""
runs, token = self._search_runs(experiment_ids, filter_string,
run_view_type, max_results, order_by,
page_token)
return PagedList(runs, token)
def test_list_registered_models(mock_get_request_message,
mock_model_registry_store):
mock_get_request_message.return_value = ListRegisteredModels(
max_results=50)
rmds = PagedList(
[
RegisteredModel(
name="model_1",
creation_timestamp=111,
last_updated_timestamp=222,
description="Test model",
latest_versions=[],
),
RegisteredModel(
name="model_2",
creation_timestamp=111,
last_updated_timestamp=333,
description="Another model",
latest_versions=[],
),
],
"next_pt",
)
mock_model_registry_store.list_registered_models.return_value = rmds
resp = _list_registered_models()
args, _ = mock_model_registry_store.list_registered_models.call_args
assert args == (50, "")
assert json.loads(resp.get_data()) == {
"next_page_token": "next_pt",
"registered_models": jsonify(rmds),
}
def search_registered_models(self,
filter_string=None,
max_results=None,
order_by=None,
page_token=None):
"""
Search for registered models in backend that satisfy the filter criteria.
:param filter_string: Filter query string, defaults to searching all registered models.
:param max_results: Maximum number of registered models desired.
:param order_by: List of column names with ASC|DESC annotation, to be used for ordering
matching search results.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``search_registered_models`` call.
:return: A PagedList of :py:class:`mlflow.entities.model_registry.RegisteredModel` objects
that satisfy the search expressions. The pagination token for the next page can be
obtained via the ``token`` attribute of the object.
"""
req_body = message_to_json(
SearchRegisteredModels(filter=filter_string,
max_results=max_results,
order_by=order_by,
page_token=page_token))
response_proto = self._call_endpoint(SearchRegisteredModels, req_body)
registered_models = [
RegisteredModel.from_proto(registered_model)
for registered_model in response_proto.registered_models
]
return PagedList(registered_models, response_proto.next_page_token)
def test_list_registered_models(mock_store):
mock_store.list_registered_models.return_value = PagedList(
[RegisteredModel("Model 1"), RegisteredModel("Model 2")], ""
)
result = newModelRegistryClient().list_registered_models()
mock_store.list_registered_models.assert_called_once()
assert len(result) == 2
def list_experiments(
self,
view_type=ViewType.ACTIVE_ONLY,
max_results=None,
page_token=None,
):
"""
:param view_type: Qualify requested type of experiments.
:param max_results: If passed, specifies the maximum number of experiments desired. If not
passed, the server will pick a maximum number of results to return.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``list_experiments`` call.
:return: A :py:class:`PagedList <mlflow.store.entities.PagedList>` of
:py:class:`Experiment <mlflow.entities.Experiment>` objects. The pagination token
for the next page can be obtained via the ``token`` attribute of the object.
"""
req_body = message_to_json(
ListExperiments(view_type=view_type,
max_results=max_results,
page_token=page_token))
response_proto = self._call_endpoint(ListExperiments, req_body)
experiments = [
Experiment.from_proto(x) for x in response_proto.experiments
]
# If the response doesn't contain `next_page_token`, `response_proto.next_page_token`
# returns an empty string (default value for a string proto field).
token = (response_proto.next_page_token
if response_proto.HasField("next_page_token") else None)
return PagedList(experiments, token)
def test_paginate_gt_maxresults_multipage():
"""
Number of runs that fit search criteria is greater than max_results. Multiple pages expected.
Expected to only get max_results number of results back.
"""
# should ask for and return the correct number of max_results
full_page_runs = PagedList([create_run() for _ in range(8)], "abc")
partial_page = PagedList([create_run() for _ in range(4)], "def")
max_results = 20
max_per_page = 8
mocked_lambda = mock.Mock(side_effect=[full_page_runs, full_page_runs, partial_page])
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
calls = [mock.call(8, None), mock.call(8, "abc"), mock.call(20 % 8, "abc")]
mocked_lambda.assert_has_calls(calls)
assert len(paginated_runs) == 20
def test_get_paginated_runs_eq_maxresults_token():
"""
Runs returned are equal to max_results which are equal to a full number of pages.
The server might send a token back, or they might not (depending on if they know if
more runs exist). In this example, a toke IS sent back.
Expected behavior is to NOT query for more pages.
"""
runs = [create_run() for i in range(10)]
tokenized_runs = PagedList(runs, "abc")
blank_runs = PagedList([], "")
max_results = 10
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 10):
with mock.patch.object(MlflowClient, "search_runs"):
MlflowClient.search_runs.side_effect = [tokenized_runs, blank_runs]
paginated_runs = _get_paginated_runs([], "", ViewType.ACTIVE_ONLY, max_results, None)
MlflowClient.search_runs.assert_called_once()
assert len(paginated_runs) == 10
def test_paginate_eq_maxresults_token():
"""
Runs returned are equal to max_results which are equal to a full number of pages.
The server might send a token back, or they might not (depending on if they know if
more runs exist). In this example, a token IS sent back.
Expected behavior is to NOT query for more pages.
"""
runs = [create_run() for _ in range(10)]
tokenized_runs = PagedList(runs, "abc")
blank_runs = PagedList([], "")
max_results = 10
max_per_page = 10
mocked_lambda = mock.Mock(side_effect=[tokenized_runs, blank_runs])
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
mocked_lambda.assert_called_once()
assert len(paginated_runs) == 10
def test_get_paginated_runs_gt_maxresults_multipage():
"""
Number of runs that fit search criteria is greater than max_results. Multiple pages expected.
Expected to only get max_results number of results back.
"""
# should ask for and return the correct number of max_results
full_page_runs = PagedList([create_run() for i in range(8)], "abc")
partial_page = PagedList([create_run() for i in range(4)], "def")
max_results = 20
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 8):
with mock.patch.object(MlflowClient, "search_runs"):
MlflowClient.search_runs.side_effect = [full_page_runs, full_page_runs, partial_page]
paginated_runs = _get_paginated_runs([12], "", ViewType.ACTIVE_ONLY, max_results, None)
calls = [mock.call([12], "", ViewType.ACTIVE_ONLY, 8, None, None),
mock.call([12], "", ViewType.ACTIVE_ONLY, 8, None, "abc"),
mock.call([12], "", ViewType.ACTIVE_ONLY, 20 % 8, None, "abc")]
MlflowClient.search_runs.assert_has_calls(calls)
assert len(paginated_runs) == 20
def test_search_runs_default_view_type(mock_get_request_message, mock_tracking_store):
"""
Search Runs default view type is filled in as ViewType.ACTIVE_ONLY
"""
mock_get_request_message.return_value = SearchRuns(experiment_ids=["0"])
mock_tracking_store.search_runs.return_value = PagedList([], None)
_search_runs()
args, _ = mock_tracking_store.search_runs.call_args
assert args[2] == ViewType.ACTIVE_ONLY
def test_get_paginated_runs_lt_maxresults_onepage_nonetoken():
"""
Number of runs is less than max_results and fits on one page.
The token passed back on the last page is None, not the emptystring
"""
runs = [create_run() for i in range(5)]
tokenized_runs = PagedList(runs, None)
max_results = 50
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 10):
with mock.patch.object(MlflowClient, "search_runs", return_value=tokenized_runs):
paginated_runs = _get_paginated_runs([], "", ViewType.ACTIVE_ONLY, max_results, None)
MlflowClient.search_runs.assert_called_once()
assert len(paginated_runs) == 5
def test_paginate_gt_maxresults_onepage():
""""
Number of runs that fit search criteria is greater than max_results. Only one page expected.
Expected to only get max_results number of results back.
"""
runs = [create_run() for _ in range(10)]
tokenized_runs = PagedList(runs, "abc")
max_results = 10
max_per_page = 20
mocked_lambda = mock.Mock(return_value=tokenized_runs)
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
mocked_lambda.assert_called_once_with(max_results, None)
assert len(paginated_runs) == 10
def test_paginate_lt_maxresults_onepage_nonetoken():
"""
Number of runs is less than max_results and fits on one page.
The token passed back on the last page is None, not the emptystring
"""
runs = [create_run() for _ in range(5)]
tokenized_runs = PagedList(runs, None)
max_results = 50
max_per_page = 10
mocked_lambda = mock.Mock(return_value=tokenized_runs)
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
mocked_lambda.assert_called_once()
assert len(paginated_runs) == 5
def test_paginate_lt_maxresults_onepage():
"""
Number of runs is less than max_results and fits on one page,
so we only need to fetch one page.
"""
runs = [create_run() for _ in range(5)]
tokenized_runs = PagedList(runs, "")
max_results = 50
max_per_page = 10
mocked_lambda = mock.Mock(return_value=tokenized_runs)
paginated_runs = _paginate(mocked_lambda, max_per_page, max_results)
mocked_lambda.assert_called_once()
assert len(paginated_runs) == 5
def search_model_versions(self, filter_string):
"""
Search for model versions in backend that satisfy the filter criteria.
:param filter_string: A filter string expression. Currently supports a single filter
condition either name of model like ``name = 'model_name'`` or
``run_id = '...'``.
:return: PagedList of :py:class:`mlflow.entities.model_registry.ModelVersion`
objects.
"""
parsed_filter = SearchUtils.parse_filter_for_model_versions(
filter_string)
if len(parsed_filter) == 0:
conditions = []
elif len(parsed_filter) == 1:
filter_dict = parsed_filter[0]
if filter_dict["comparator"] != "=":
raise MlflowException(
"Model Registry search filter only supports equality(=) "
"comparator. Input filter string: %s" % filter_string,
error_code=INVALID_PARAMETER_VALUE,
)
if filter_dict["key"] == "name":
conditions = [SqlModelVersion.name == filter_dict["value"]]
elif filter_dict["key"] == "source_path":
conditions = [SqlModelVersion.source == filter_dict["value"]]
elif filter_dict["key"] == "run_id":
conditions = [SqlModelVersion.run_id == filter_dict["value"]]
else:
raise MlflowException("Invalid filter string: %s" %
filter_string,
error_code=INVALID_PARAMETER_VALUE)
else:
raise MlflowException(
"Model Registry expects filter to be one of "
"\"name = '<model_name>'\" or "
"\"source_path = '<source_path>'\" or \"run_id = '<run_id>'."
"Input filter string: %s. " % filter_string,
error_code=INVALID_PARAMETER_VALUE,
)
with self.ManagedSessionMaker() as session:
conditions.append(
SqlModelVersion.current_stage != STAGE_DELETED_INTERNAL)
sql_model_version = session.query(SqlModelVersion).filter(
*conditions).all()
model_versions = [
mv.to_mlflow_entity() for mv in sql_model_version
]
return PagedList(model_versions, None)
def test_get_paginated_runs_gt_maxresults_onepage():
""""
Number of runs that fit search criteria is greater than max_results. Only one page expected.
Expected to only get max_results number of results back.
"""
runs = [create_run() for i in range(10)]
tokenized_runs = PagedList(runs, "abc")
max_results = 10
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 20):
with mock.patch.object(MlflowClient, "search_runs", return_value=tokenized_runs):
paginated_runs = _get_paginated_runs([123], "", ViewType.ACTIVE_ONLY, max_results, None)
MlflowClient.search_runs.assert_called_once_with(
[123], "", ViewType.ACTIVE_ONLY, max_results, None, None)
assert len(paginated_runs) == 10
def search_model_versions(self, filter_string):
"""
Search for model versions in backend that satisfy the filter criteria.
:param filter_string: A filter string expression. Currently supports a single filter
condition either name of model like ``name = 'model_name'`` or
``run_id = '...'``.
:return: PagedList of :py:class:`mlflow.entities.model_registry.ModelVersion`
objects.
"""
req_body = message_to_json(SearchModelVersions(filter=filter_string))
response_proto = self._call_endpoint(SearchModelVersions, req_body)
model_versions = [ModelVersion.from_proto(mvd)
for mvd in response_proto.model_versions]
return PagedList(model_versions, response_proto.next_page_token)
def test_get_paginated_runs_lt_maxresults_onepage():
"""
Number of runs is less than max_results and fits on one page,
so we only need to fetch one page.
"""
runs = [create_run() for _ in range(5)]
tokenized_runs = PagedList(runs, "")
max_results = 50
with mock.patch("mlflow.tracking.fluent.NUM_RUNS_PER_PAGE_PANDAS", 10):
with mock.patch.object(MlflowClient,
"search_runs",
return_value=tokenized_runs):
paginated_runs = _get_paginated_runs([], "", ViewType.ACTIVE_ONLY,
max_results, None)
MlflowClient.search_runs.assert_called_once()
assert len(paginated_runs) == 5
def list_registered_models(self, max_results, page_token):
"""
List of all registered models.
:param max_results: Maximum number of registered models desired.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``list_registered_models`` call.
:return: PagedList of :py:class:`mlflow.entities.model_registry.RegisteredModel` objects.
"""
req_body = message_to_json(
ListRegisteredModels(page_token=page_token,
max_results=max_results))
response_proto = self._call_endpoint(ListRegisteredModels, req_body)
return PagedList([
RegisteredModel.from_proto(registered_model)
for registered_model in response_proto.registered_models
], response_proto.next_page_token)
def search_registered_models(
self,
filter_string=None,
max_results=SEARCH_REGISTERED_MODEL_MAX_RESULTS_DEFAULT,
order_by=None,
page_token=None,
):
"""
Search for registered models in backend that satisfy the filter criteria.
:param filter_string: Filter query string, defaults to searching all registered models.
:param max_results: Maximum number of registered models desired.
:param order_by: List of column names with ASC|DESC annotation, to be used for ordering
matching search results.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``search_registered_models`` call.
:return: A PagedList of :py:class:`mlflow.entities.model_registry.RegisteredModel` objects
that satisfy the search expressions. The pagination token for the next page can be
obtained via the ``token`` attribute of the object.
"""
if max_results > SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD:
raise MlflowException(
"Invalid value for request parameter max_results. "
"It must be at most {}, but got value {}".format(
SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD,
max_results),
INVALID_PARAMETER_VALUE,
)
parsed_filter = SearchUtils.parse_filter_for_registered_models(
filter_string)
parsed_orderby = self._parse_search_registered_models_order_by(
order_by)
offset = SearchUtils.parse_start_offset_from_page_token(page_token)
# we query for max_results + 1 items to check whether there is another page to return.
# this remediates having to make another query which returns no items.
max_results_for_query = max_results + 1
def compute_next_token(current_size):
next_token = None
if max_results_for_query == current_size:
final_offset = offset + max_results
next_token = SearchUtils.create_page_token(final_offset)
return next_token
if len(parsed_filter) == 0:
conditions = []
elif len(parsed_filter) == 1:
filter_dict = parsed_filter[0]
comparator = filter_dict["comparator"].upper()
if comparator not in SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS:
raise MlflowException(
"Search registered models filter expression only "
"supports the equality(=) comparator, case-sensitive"
"partial match (LIKE), and case-insensitive partial "
"match (ILIKE). Input filter string: %s" % filter_string,
error_code=INVALID_PARAMETER_VALUE,
)
if comparator == SearchUtils.LIKE_OPERATOR:
conditions = [
SqlRegisteredModel.name.like(filter_dict["value"])
]
elif comparator == SearchUtils.ILIKE_OPERATOR:
conditions = [
SqlRegisteredModel.name.ilike(filter_dict["value"])
]
else:
conditions = [SqlRegisteredModel.name == filter_dict["value"]]
else:
supported_ops = "".join([
"(" + op + ")"
for op in SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS
])
sample_query = 'name {} "<model_name>"'.format(supported_ops)
raise MlflowException(
"Invalid filter string: {}".format(filter_string) +
"Search registered models supports filter expressions like:" +
sample_query,
error_code=INVALID_PARAMETER_VALUE,
)
with self.ManagedSessionMaker() as session:
query = (session.query(SqlRegisteredModel).filter(
*conditions).order_by(
*parsed_orderby).limit(max_results_for_query))
if page_token:
query = query.offset(offset)
sql_registered_models = query.all()
next_page_token = compute_next_token(len(sql_registered_models))
rm_entities = [
rm.to_mlflow_entity() for rm in sql_registered_models
][:max_results]
return PagedList(rm_entities, next_page_token)
def search_registered_models(
self,
filter_string=None,
max_results=SEARCH_REGISTERED_MODEL_MAX_RESULTS_DEFAULT,
order_by=None,
page_token=None):
"""
Search for registered models in backend that satisfy the filter criteria.
:param filter_string: Filter query string, defaults to searching all registered models.
Currently supports a single filter condition based on
the name of the model like ``name = 'model_name'``
:param max_results: Maximum number of registered models desired.
:param order_by: List of column names with ASC|DESC annotation, to be used for ordering
matching search results.
Note:: This field is currently not supported.
:param page_token: Token specifying the next page of results. It should be obtained from
a ``search_registered_models`` call.
:return: A PagedList of :py:class:`mlflow.entities.model_registry.RegisteredModel` objects
that satisfy the search expressions. The pagination token for the next page can be
obtained via the ``token`` attribute of the object.
"""
if order_by:
raise NotImplementedError(
"Order by is not implemented for search registered models.")
if max_results > SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD:
raise MlflowException(
"Invalid value for request parameter max_results."
"It must be at most {}, but got value {}".format(
SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD,
max_results), INVALID_PARAMETER_VALUE)
parsed_filter = SearchUtils.parse_filter_for_registered_models(
filter_string)
offset = SearchUtils.parse_start_offset_from_page_token(page_token)
# we query for max_results + 1 items to check whether there is another page to return.
# this remediates having to make another query which returns no items.
max_results_for_query = max_results + 1
def compute_next_token(current_size):
next_token = None
if max_results_for_query == current_size:
final_offset = offset + max_results
next_token = SearchUtils.create_page_token(final_offset)
return next_token
if len(parsed_filter) == 0:
conditions = []
elif len(parsed_filter) == 1:
filter_dict = parsed_filter[0]
comparator = filter_dict['comparator'].upper()
if comparator not in \
SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS:
raise MlflowException(
'Search registered models filter expression only '
'supports the equality(=) comparator, case-sensitive'
'partial match (LIKE), and case-insensitive partial '
'match (ILIKE). Input filter string: %s' % filter_string,
error_code=INVALID_PARAMETER_VALUE)
if comparator == SearchUtils.LIKE_OPERATOR:
conditions = [
SqlRegisteredModel.name.like(filter_dict["value"])
]
elif comparator == SearchUtils.ILIKE_OPERATOR:
conditions = [
SqlRegisteredModel.name.ilike(filter_dict["value"])
]
else:
conditions = [SqlRegisteredModel.name == filter_dict["value"]]
else:
supported_ops = ''.join([
'(' + op + ')'
for op in SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS
])
sample_query = f'name {supported_ops} "<model_name>"'
raise MlflowException(
f'Invalid filter string: {filter_string}'
'Search registered models supports filter expressions like:' +
sample_query,
error_code=INVALID_PARAMETER_VALUE)
with self.ManagedSessionMaker() as session:
if self.db_type == SQLITE:
session.execute("PRAGMA case_sensitive_like = true;")
query = session\
.query(SqlRegisteredModel)\
.filter(*conditions)\
.order_by(SqlRegisteredModel.name.asc())\
.limit(max_results_for_query)
if page_token:
query = query.offset(offset)
sql_registered_models = query.all()
next_page_token = compute_next_token(len(sql_registered_models))
rm_entities = [
rm.to_mlflow_entity() for rm in sql_registered_models
][:max_results]
return PagedList(rm_entities, next_page_token)
def search_registered_models(self,
filter_string,
page_token=None,
max_results=SEARCH_REGISTERED_MODEL_MAX_RESULTS_DEFAULT):
"""
Search for registered models in backend that satisfy the filter criteria.
:param filter_string: A filter string expression. Currently supports a single filter
condition either name of model like ``name = 'model_name'``
:param page_token: Token specifying the next page of results. It should be obtained from
a ``search_registered_models`` call.
:param max_results: Maximum number of registered models desired.
:return: A PagedList of :py:class:`mlflow.entities.model_registry.RegisteredModel` objects
that satisfy the search expressions. The pagination token for the next page can be
obtained via the ``token`` attribute of the object.
"""
if max_results > SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD:
raise MlflowException("Invalid value for request parameter max_results."
"It must be at most {}, but got value {}"
.format(SEARCH_REGISTERED_MODEL_MAX_RESULTS_THRESHOLD,
max_results),
INVALID_PARAMETER_VALUE)
parsed_filter = SearchUtils.parse_filter_for_model_registry(filter_string)
offset = SearchUtils.parse_start_offset_from_page_token(page_token)
def compute_next_token(current_size):
next_token = None
if max_results == current_size:
final_offset = offset + max_results
next_token = SearchUtils.create_page_token(final_offset)
return next_token
if len(parsed_filter) == 0:
conditions = []
elif len(parsed_filter) == 1:
filter_dict = parsed_filter[0]
if filter_dict["comparator"] not in \
SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS:
raise MlflowException('Search registered models filter expression only '
'supports the equality(=) comparator, case-sensitive'
'partial match (LIKE), and case-insensitive partial '
'match (ILIKE). Input filter string: %s' % filter_string,
error_code=INVALID_PARAMETER_VALUE)
if filter_dict["key"] == "name":
if filter_dict["comparator"] == "LIKE":
conditions = [SqlRegisteredModel.name.like(filter_dict["value"])]
elif filter_dict["comparator"] == "ILIKE":
conditions = [SqlRegisteredModel.name.ilike(filter_dict["value"])]
else:
conditions = [SqlRegisteredModel.name == filter_dict["value"]]
else:
raise MlflowException('Invalid filter string: %s' % filter_string,
error_code=INVALID_PARAMETER_VALUE)
else:
supported_ops = ''.join(['(' + op + ')' for op in
SearchUtils.VALID_REGISTERED_MODEL_SEARCH_COMPARATORS])
sample_query = f'name {supported_ops} "<model_name>"'
raise MlflowException(f'Invalid filter string: {filter_string}'
'Search registered models supports filter expressions like:' +
sample_query, error_code=INVALID_PARAMETER_VALUE)
with self.ManagedSessionMaker() as session:
if self.db_type == SQLITE:
session.execute("PRAGMA case_sensitive_like = true;")
query = session\
.query(SqlRegisteredModel)\
.filter(*conditions)\
.order_by(SqlRegisteredModel.name.asc())\
.limit(max_results)
if page_token:
query = query.offset(offset)
sql_registered_models = query.all()
registered_models = [rm.to_mlflow_entity() for rm in sql_registered_models]
next_page_token = compute_next_token(len(registered_models))
return PagedList(registered_models, next_page_token)
