def test_incomplete_params(self):
config_dict = {
"inputs": [
{"name": "param1", "type": types.INT},
{"name": "param2", "type": types.INT},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": 1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
config_dict = {
"outputs": [
{"name": "param1", "type": types.INT, "value": 12, "isOptional": True},
{"name": "param2", "type": types.INT},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
ops_params.validate_params(
params={"param1": {"value": 1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
def test_extra_params(self):
# inputs
config_dict = {
"inputs": [{"name": "param1", "type": types.INT}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": 1}, "param2": {"value": 2}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# outputs
config_dict = {
"outputs": [{"name": "param1", "type": types.INT}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": 1}, "param2": {"value": 2}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
def test_job_refs_params(self):
config_dict = {
"inputs": [
{
"name": "param1",
"type": types.INT
},
{
"name": "param9",
"type": types.FLOAT
},
],
"run": {
"kind": V1RunKind.JOB,
"container": {
"image": "test"
}
},
}
params = {
"param1": {
"ref": "job.A",
"value": "outputs.foo"
},
"param9": {
"value": 13.1
},
}
config = V1CompiledOperation.from_dict(config_dict)
# Validation outside the context of a pipeline
with self.assertRaises(ValidationError):
ops_params.validate_params(params=params,
inputs=config.inputs,
outputs=None,
is_template=False)
def test_param_validation_with_outputs(self):
config_dict = {
"outputs": [
{"name": "param1", "type": types.STR},
{"name": "param2", "type": types.INT},
{"name": "param3", "type": types.FLOAT},
{"name": "param4", "type": types.BOOL},
{"name": "param5", "type": types.DICT},
{"name": "param6", "type": types.LIST},
{"name": "param7", "type": types.GCS},
{"name": "param8", "type": types.S3},
{"name": "param9", "type": types.WASB},
{"name": "param10", "type": types.PATH},
{"name": "param11", "type": types.METRIC},
{"name": "param12", "type": types.METADATA},
{"name": "param13", "type": types.METADATA},
{"name": "param14", "type": types.METADATA},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
op = V1CompiledOperation.from_dict(config_dict)
params = {
"param1": {"value": "text"},
"param2": {"value": 12},
"param3": {"value": 13.3},
"param4": {"value": False},
"param5": {"value": {"foo": "bar"}},
"param6": {"value": [1, 3, 45, 5]},
"param7": {"value": "gs://bucket/path/to/blob/"},
"param8": {"value": "s3://test/this/is/bad/key.txt"},
"param9": {"value": "wasbs://[email protected]/"},
"param10": {"value": "/foo/bar"},
"param11": {"value": 124.4},
"param12": {"value": {"foo": 124.4}},
"param13": {"value": {"foo": "bar"}},
"param14": {"value": {"foo": ["foo", 124.4]}},
}
validated_params = ops_params.validate_params(
params=params, inputs=None, outputs=op.outputs, is_template=False
)
assert params == {p.name: p.param.to_dict() for p in validated_params}
# Passing missing params
params.pop("param1")
params.pop("param2")
validated_params = ops_params.validate_params(
params=params, inputs=None, outputs=op.outputs, is_template=False
)
params["param1"] = {"value": None}
params["param2"] = {"value": None}
assert params == {p.name: p.param.to_dict() for p in validated_params}
def test_experiment_and_job_refs_params(self):
config_dict = {
"inputs": [
{"name": "param1", "type": types.INT},
{"name": "param2", "type": types.FLOAT},
{"name": "param9", "type": types.WASB},
{"name": "param11", "type": types.METRIC},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
op = V1CompiledOperation.from_dict(config_dict)
params = {
"param1": {
"ref": "runs.64332180bfce46eba80a65caf73c5396",
"value": "outputs.foo",
},
"param2": {
"ref": "runs.0de53b5bf8b04a219d12a39c6b92bcce",
"value": "outputs.foo",
},
"param9": {"value": "wasbs://[email protected]/"},
"param11": {
"ref": "runs.fcc462d764104eb698d3cca509f34154",
"value": "outputs.accuracy",
},
}
validated_params = ops_params.validate_params(
params=params, inputs=op.inputs, outputs=None, is_template=False
)
assert {p.name: p.param.to_dict() for p in validated_params} == params
def validate_params(self,
params=None,
context=None,
is_template=True,
check_runs=False) -> List[ParamSpec]:
return ops_params.validate_params(
inputs=self.inputs,
outputs=self.outputs,
params=params,
matrix=self.matrix,
context=context,
is_template=is_template,
check_runs=check_runs,
)
def validate_params(
self,
params: Dict = None,
context: Dict = None,
is_template: bool = True,
check_runs: bool = False,
parse_values: bool = False,
) -> List[ParamSpec]:
return ops_params.validate_params(
inputs=self.inputs,
outputs=self.outputs,
params=params,
matrix=self.matrix,
context=context,
is_template=is_template,
check_runs=check_runs,
parse_values=parse_values,
)
def test_required_input_no_param_only_validated_on_run(self):
# Inputs
config_dict = {
"inputs": [
{"name": "param1", "type": types.STR},
{"name": "param10", "type": types.PATH},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": "text"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# Outputs
config_dict = {
"outputs": [
{"name": "param1", "type": types.STR},
{"name": "param10", "type": types.PATH},
],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
ops_params.validate_params(
params={"param1": {"value": "text"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# IO
config_dict = {
"inputs": [{"name": "param1", "type": types.STR}],
"outputs": [{"name": "param10", "type": types.PATH}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
ops_params.validate_params(
params={"param1": {"value": "text"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
def test_param_validation_with_mismatched_outputs(self):
config_dict = {
"outputs": [{"name": "param1", "type": types.INT}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
# Passing correct param
ops_params.validate_params(
params={"param1": {"value": 1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# Passing wrong type
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": "text"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": 12.1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": {"foo": "bar"}}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param1": {"value": "gs://bucket/path/to/blob/"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
config_dict = {
"outputs": [{"name": "param2", "type": types.STR}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
# Passing correct param
ops_params.validate_params(
params={"param2": {"value": "text"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# Passing wrong type
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param2": {"value": 1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param2": {"value": False}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param2": {"value": {"foo": "bar"}}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param2": {"value": ["gs://bucket/path/to/blob/"]}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
config_dict = {
"outputs": [{"name": "param7", "type": types.WASB}],
"run": {"kind": V1RunKind.JOB, "container": {"image": "test"}},
}
config = V1CompiledOperation.from_dict(config_dict)
# Passing correct param
ops_params.validate_params(
params={
"param7": {"value": "wasbs://[email protected]/"}
},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
# Passing wrong param
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param7": {"value": "gs://bucket/path/to/blob/"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param7": {"value": "s3://test/this/is/bad/key.txt"}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
with self.assertRaises(ValidationError):
ops_params.validate_params(
params={"param7": {"value": 1}},
inputs=config.inputs,
outputs=config.outputs,
is_template=False,
)
def process_components(self, inputs=None):
from polyaxon.polyaxonfile.check import collect_references
inputs = inputs or []
for _input in inputs:
self._context["dag.inputs.{}".format(_input.name)] = _input
if not self.operations:
raise PolyaxonSchemaError(
"Pipeline is not valid, it has no ops to validate components.")
components = self.components or []
for component in components:
component_name = component.name
if component_name in self._components_by_names:
raise PolyaxonSchemaError(
"Pipeline has multiple components with the same name `{}`".
format(component_name))
self._components_by_names[component_name] = component
for op in self.operations:
op_name = op.name
if op.has_url_reference or op.has_path_reference:
try:
op = collect_references(op, self._path_context)
except Exception as e:
raise PolyaxonSchemaError(
"Pipeline op with name `{}` requires a component with ref `{}`, "
"the reference could not be resolved. Error: {}".
format(op_name, op.hub_ref or op.url_ref
or op.path_ref, e))
elif op.has_hub_reference:
continue
if op.has_component_reference:
outputs = op.component.outputs
inputs = op.component.inputs
elif op.has_dag_reference:
component_ref_name = op.dag_ref
if op_name in self._op_component_mapping:
raise PolyaxonSchemaError(
"Pipeline has multiple ops with the same name `{}`".
format(op_name))
if component_ref_name not in self._components_by_names:
raise PolyaxonSchemaError(
"Pipeline op with name `{}` requires a component with name `{}`, "
"which is not defined on this pipeline.".format(
op_name, component_ref_name))
self._op_component_mapping[op_name] = component_ref_name
outputs = self._components_by_names[component_ref_name].outputs
inputs = self._components_by_names[component_ref_name].inputs
else:
raise PolyaxonSchemaError(
"Pipeline op has no template field `{}`".format(op_name))
if outputs:
for output in outputs:
self._context["ops.{}.outputs.{}".format(
op_name, output.name)] = output
if inputs:
for cinput in inputs:
self._context["ops.{}.inputs.{}".format(
op_name, cinput.name)] = cinput
# We allow to resolve name, status, project, all outputs/inputs, iteration
self._context["ops.{}.inputs".format(op_name)] = V1IO(
name="inputs", iotype=types.DICT, value={}, is_optional=True)
self._context["ops.{}.outputs".format(op_name)] = V1IO(
name="outputs", iotype=types.DICT, value={}, is_optional=True)
self._context["ops.{}.status".format(op_name)] = V1IO(
name="status", iotype=types.STR, value="", is_optional=True)
self._context["ops.{}.name".format(op_name)] = V1IO(
name="name", iotype=types.STR, value="", is_optional=True)
self._context["ops.{}.uuid".format(op_name)] = V1IO(
name="uuid", iotype=types.STR, value="", is_optional=True)
self._context["ops.{}.project_name".format(op_name)] = V1IO(
name="project_name",
iotype=types.STR,
value="",
is_optional=True)
self._context["ops.{}.project_uuid".format(op_name)] = V1IO(
name="project_uuid",
iotype=types.STR,
value="",
is_optional=True)
self._context["ops.{}.iteration".format(op_name)] = V1IO(
name="iteration", iotype=types.STR, value="", is_optional=True)
for op in self.operations:
if op.has_hub_reference:
continue
elif op.has_component_reference:
component_ref = op.template.name
outputs = op.template.outputs
inputs = op.template.inputs
elif op.has_dag_reference:
component_ref = op.template.name
outputs = self._components_by_names[component_ref].outputs
inputs = self._components_by_names[component_ref].inputs
else:
raise PolyaxonSchemaError(
"Pipeline op has no template field `{}`".format(op.name))
ops_params.validate_params(
params=op.params,
inputs=inputs,
outputs=outputs,
context=self._context,
parallel=op.parallel,
is_template=False,
check_runs=False,
extra_info="<op {}>.<component {}>".format(
op.name, component_ref),
)
def process_components(self,
inputs=None,
ignore_hub_validation: bool = False):
"""`ignore_hub_validation` is currently used for ignoring validation
during tests with hub_ref.
"""
inputs = inputs or []
self._context["dag.name"] = V1IO(name="name",
type=types.STR,
value="",
is_optional=True)
self._context["dag.uuid"] = V1IO(name="uuid",
type=types.STR,
value="",
is_optional=True)
for _input in inputs:
self._context["dag.inputs.{}".format(_input.name)] = _input
if not self.operations:
raise PolyaxonSchemaError(
"Pipeline is not valid, it has no ops to validate components.")
components = self.components or []
for component in components:
component_name = component.name
if component_name in self._components_by_names:
raise PolyaxonSchemaError(
"Pipeline has multiple components with the same name `{}`".
format(component_name))
self._components_by_names[component_name] = component
for op in self.operations:
op_name = op.name
if op.has_component_reference:
outputs = op.component.outputs
inputs = op.component.inputs
elif op.has_dag_reference:
component_ref_name = op.dag_ref
if op_name in self._op_component_mapping:
raise PolyaxonSchemaError(
"Pipeline has multiple ops with the same name `{}`".
format(op_name))
if component_ref_name not in self._components_by_names:
raise PolyaxonSchemaError(
"Pipeline op with name `{}` requires a component with name `{}`, "
"which is not defined on this pipeline.".format(
op_name, component_ref_name))
self._op_component_mapping[op_name] = component_ref_name
outputs = self._components_by_names[component_ref_name].outputs
inputs = self._components_by_names[component_ref_name].inputs
elif op.has_hub_reference and ignore_hub_validation:
continue
else:
raise PolyaxonSchemaError(
"Pipeline op has no definition field `{}`".format(op_name))
if outputs:
for output in outputs:
self._context["ops.{}.outputs.{}".format(
op_name, output.name)] = output
if output.type == types.ARTIFACTS:
self._context["ops.{}.artifacts.{}".format(
op_name, output.name)] = output
if inputs:
for cinput in inputs:
self._context["ops.{}.inputs.{}".format(
op_name, cinput.name)] = cinput
if cinput.type == types.ARTIFACTS:
self._context["ops.{}.artifacts.{}".format(
op_name, cinput.name)] = cinput
for g_context in contexts_sections.GLOBALS_CONTEXTS:
self._context["ops.{}.globals.{}".format(
op_name, g_context)] = V1IO(name=g_context,
type=types.STR,
value="",
is_optional=True)
# We allow to resolve name, status, project, all outputs/inputs, iteration
self._context["ops.{}.{}".format(
op_name, contexts_sections.INPUTS)] = V1IO(name="inputs",
type=types.DICT,
value={},
is_optional=True)
self._context["ops.{}.{}".format(
op_name, contexts_sections.OUTPUTS)] = V1IO(name="outputs",
type=types.DICT,
value={},
is_optional=True)
self._context["ops.{}.{}".format(
op_name, contexts_sections.GLOBALS)] = V1IO(name="globals",
type=types.STR,
value="",
is_optional=True)
self._context["ops.{}.{}".format(
op_name, contexts_sections.ARTIFACTS)] = V1IO(name="artifacts",
type=types.STR,
value="",
is_optional=True)
self._context["ops.{}.{}".format(
op_name,
contexts_sections.INPUTS_OUTPUTS)] = V1IO(name="io",
type=types.STR,
value={},
is_optional=True)
for op in self.operations:
if op.has_component_reference:
component_ref = op.definition.name
outputs = op.definition.outputs
inputs = op.definition.inputs
elif op.has_dag_reference:
component_ref = op.definition.name
outputs = self._components_by_names[component_ref].outputs
inputs = self._components_by_names[component_ref].inputs
elif op.has_hub_reference and ignore_hub_validation:
continue
else:
raise PolyaxonSchemaError(
"Pipeline op has no definition field `{}`".format(op.name))
ops_params.validate_params(
params=op.params,
inputs=inputs,
outputs=outputs,
context=self._context,
matrix=op.matrix,
joins=op.joins,
is_template=False,
check_runs=False,
extra_info="<op {}>.<component {}>".format(
op.name, component_ref),
)
