def test_extra_fields_invalid_deployment_schema(self):
# Undefined fields should be forbidden in the schema
deployment_schema = self.get_minimal_deployment_schema()
# Schema should be createable with valid fields
DeploymentSchema.parse_obj(deployment_schema)
# Schema should raise error when a nonspecified field is included
deployment_schema["fake_field"] = None
with pytest.raises(ValidationError):
DeploymentSchema.parse_obj(deployment_schema)
def deployment_to_schema(d: Deployment) -> DeploymentSchema:
"""Converts a live deployment object to a corresponding structured schema.
If the deployment has a class or function, it will be attemptetd to be
converted to a valid corresponding import path.
init_args and init_kwargs must also be JSON-serializable or this call will
fail.
"""
if d.ray_actor_options is not None:
ray_actor_options_schema = RayActorOptionsSchema.parse_obj(
d.ray_actor_options)
else:
ray_actor_options_schema = None
return DeploymentSchema(
name=d.name,
# TODO(Sihan) DeploymentConfig num_replicas and auto_config can be set together
# because internally we use these two field for autoscale and deploy.
# We can improve the code after we separate the user faced deployment config and
# internal deployment config.
num_replicas=None if d._config.autoscaling_config else d.num_replicas,
route_prefix=d.route_prefix,
max_concurrent_queries=d.max_concurrent_queries,
user_config=d.user_config,
autoscaling_config=d._config.autoscaling_config,
graceful_shutdown_wait_loop_s=d._config.graceful_shutdown_wait_loop_s,
graceful_shutdown_timeout_s=d._config.graceful_shutdown_timeout_s,
health_check_period_s=d._config.health_check_period_s,
health_check_timeout_s=d._config.health_check_timeout_s,
ray_actor_options=ray_actor_options_schema,
)
def test_ge_zero_deployment_schema(self):
# Ensure ValidationError is raised when any fields that must be greater
# than or equal to zero is set to -1.
deployment_schema = self.get_minimal_deployment_schema()
ge_zero_fields = [
"graceful_shutdown_wait_loop_s",
"graceful_shutdown_timeout_s",
]
for field in ge_zero_fields:
deployment_schema[field] = -1
with pytest.raises(ValidationError):
DeploymentSchema.parse_obj(deployment_schema)
deployment_schema[field] = None
def deployment_to_schema(d: Deployment) -> DeploymentSchema:
"""Converts a live deployment object to a corresponding structured schema.
If the deployment has a class or function, it will be attemptetd to be
converted to a valid corresponding import path.
init_args and init_kwargs must also be JSON-serializable or this call will
fail.
"""
if d.ray_actor_options is not None:
ray_actor_options_schema = RayActorOptionsSchema.parse_obj(
d.ray_actor_options)
else:
ray_actor_options_schema = None
return DeploymentSchema(
name=d.name,
import_path=get_deployment_import_path(d,
enforce_importable=True,
replace_main=True),
init_args=(),
init_kwargs={},
num_replicas=d.num_replicas,
route_prefix=d.route_prefix,
max_concurrent_queries=d.max_concurrent_queries,
user_config=d.user_config,
autoscaling_config=d._config.autoscaling_config,
graceful_shutdown_wait_loop_s=d._config.graceful_shutdown_wait_loop_s,
graceful_shutdown_timeout_s=d._config.graceful_shutdown_timeout_s,
health_check_period_s=d._config.health_check_period_s,
health_check_timeout_s=d._config.health_check_timeout_s,
ray_actor_options=ray_actor_options_schema,
)
def test_gt_zero_deployment_schema(self):
# Ensure ValidationError is raised when any fields that must be greater
# than zero is set to zero.
deployment_schema = self.get_minimal_deployment_schema()
gt_zero_fields = [
"num_replicas",
"max_concurrent_queries",
"health_check_period_s",
"health_check_timeout_s",
]
for field in gt_zero_fields:
deployment_schema[field] = 0
with pytest.raises(ValidationError):
DeploymentSchema.parse_obj(deployment_schema)
deployment_schema[field] = None
def test_invalid_python_attributes(self):
# Test setting invalid attributes for Python to ensure a validation or
# value error is raised.
# Python requires an import path
deployment_schema = self.get_minimal_deployment_schema()
# DeploymentSchema should be generated with valid import_paths
for path in get_valid_import_paths():
deployment_schema["import_path"] = path
DeploymentSchema.parse_obj(deployment_schema)
# Invalid import_path syntax should raise a ValidationError
for path in get_invalid_import_paths():
deployment_schema["import_path"] = path
with pytest.raises(ValidationError):
DeploymentSchema.parse_obj(deployment_schema)
def test_valid_deployment_schema(self):
# Ensure a valid DeploymentSchema can be generated
deployment_schema = {
"name": "shallow",
"init_args": [4, "glue"],
"init_kwargs": {
"fuel": "diesel"
},
"import_path": "test_env.shallow_import.ShallowClass",
"num_replicas": 2,
"route_prefix": "/shallow",
"max_concurrent_queries": 32,
"user_config": {
"threshold": 0.2,
"pattern": "rainbow"
},
"autoscaling_config": None,
"graceful_shutdown_wait_loop_s": 17,
"graceful_shutdown_timeout_s": 49,
"health_check_period_s": 11,
"health_check_timeout_s": 11,
"ray_actor_options": {
"runtime_env": {
"working_dir": ("https://github.com/shrekris-anyscale/"
"test_module/archive/HEAD.zip"),
"py_modules": [
("https://github.com/shrekris-anyscale/"
"test_deploy_group/archive/HEAD.zip"),
],
},
"num_cpus": 3,
"num_gpus": 4.2,
"memory": 5,
"object_store_memory": 3,
"resources": {
"custom_asic": 8
},
"accelerator_type": NVIDIA_TESLA_P4,
},
}
DeploymentSchema.parse_obj(deployment_schema)
def dagnode_from_json(input_json: Any) -> Union[DAGNode, RayServeHandle, Any]:
"""
Decode a DAGNode from given input json dictionary. JSON serialization is
only used and enforced in ray serve from ray core API authored DAGNode(s).
Covers both RayServeHandle and DAGNode types.
Assumptions:
- User object's JSON dict does not have keys that collide with our
reserved DAGNODE_TYPE_KEY
- RayServeHandle and Deployment can be re-constructed without losing
states needed for their functionality or correctness.
- DAGNode type can be re-constructed with new stable_uuid upon each
deserialization without effective correctness of execution.
- Only exception is ClassNode used as parent of ClassMethodNode
that we perserve the same parent node.
- .options() does not contain any DAGNode type
"""
node_type_to_cls = {
# Ray DAG Inputs
InputNode.__name__: InputNode,
InputAttributeNode.__name__: InputAttributeNode,
# Deployment graph execution nodes
DeploymentExecutorNode.__name__: DeploymentExecutorNode,
DeploymentMethodExecutorNode.__name__: DeploymentMethodExecutorNode,
DeploymentFunctionExecutorNode.__name__:
DeploymentFunctionExecutorNode,
}
# Deserialize RayServeHandle type
if SERVE_HANDLE_JSON_KEY in input_json:
return serve_handle_from_json_dict(input_json)
# Base case for plain objects
elif DAGNODE_TYPE_KEY not in input_json:
return input_json
elif input_json[DAGNODE_TYPE_KEY] == RayServeDAGHandle.__name__:
return RayServeDAGHandle(input_json["dag_node_json"])
elif input_json[DAGNODE_TYPE_KEY] == "DeploymentSchema":
return DeploymentSchema.parse_obj(input_json["schema"])
elif input_json[DAGNODE_TYPE_KEY] == RayServeLazySyncHandle.__name__:
return RayServeLazySyncHandle(
input_json["deployment_name"],
HandleOptions(input_json["handle_options_method_name"]),
)
# Deserialize DAGNode type
elif input_json[DAGNODE_TYPE_KEY] in node_type_to_cls:
return node_type_to_cls[input_json[DAGNODE_TYPE_KEY]].from_json(
input_json)
else:
# Class and Function nodes require original module as body.
module_name, attr_name = parse_import_path(input_json["import_path"])
module = getattr(import_module(module_name), attr_name)
if input_json[DAGNODE_TYPE_KEY] == FunctionNode.__name__:
return FunctionNode.from_json(input_json, module)
elif input_json[DAGNODE_TYPE_KEY] == ClassNode.__name__:
return ClassNode.from_json(input_json, module)
def test_mutually_exclusive_num_replicas_and_autoscaling_config(self):
# num_replicas and autoscaling_config cannot be set at the same time
deployment_schema = self.get_minimal_deployment_schema()
deployment_schema["num_replicas"] = 5
deployment_schema["autoscaling_config"] = None
DeploymentSchema.parse_obj(deployment_schema)
deployment_schema["num_replicas"] = None
deployment_schema["autoscaling_config"] = AutoscalingConfig().dict()
DeploymentSchema.parse_obj(deployment_schema)
deployment_schema["num_replicas"] = 5
deployment_schema["autoscaling_config"] = AutoscalingConfig().dict()
with pytest.raises(ValueError):
DeploymentSchema.parse_obj(deployment_schema)
def test_invalid_python_attributes(self):
# Test setting invalid attributes for Python to ensure a validation or
# value error is raised.
# Python requires an import path
deployment_schema = self.get_minimal_deployment_schema()
deployment_schema["init_args"] = [1, 2]
deployment_schema["init_kwargs"] = {"threshold": 0.5}
del deployment_schema["import_path"]
with pytest.raises(ValueError, match="must be specified"):
DeploymentSchema.parse_obj(deployment_schema)
# DeploymentSchema should be generated once import_path is set
deployment_schema["import_path"] = "my_module.MyClass"
DeploymentSchema.parse_obj(deployment_schema)
# Invalid import_path syntax should raise a ValidationError
invalid_paths = ["", "MyClass", ".", "hello,world"]
for path in invalid_paths:
deployment_schema["import_path"] = path
with pytest.raises(ValidationError):
DeploymentSchema.parse_obj(deployment_schema)
def test_route_prefix(self):
# Ensure that route_prefix is validated
deployment_schema = self.get_minimal_deployment_schema()
# route_prefix must start with a "/"
deployment_schema["route_prefix"] = "hello/world"
with pytest.raises(ValueError):
DeploymentSchema.parse_obj(deployment_schema)
# route_prefix must end with a "/"
deployment_schema["route_prefix"] = "/hello/world/"
with pytest.raises(ValueError):
DeploymentSchema.parse_obj(deployment_schema)
# route_prefix cannot contain wildcards, meaning it can't have
# "{" or "}"
deployment_schema["route_prefix"] = "/hello/{adjective}/world/"
with pytest.raises(ValueError):
DeploymentSchema.parse_obj(deployment_schema)
# Ensure a valid route_prefix works
deployment_schema["route_prefix"] = "/hello/wonderful/world"
DeploymentSchema.parse_obj(deployment_schema)
# Ensure route_prefix of "/" works
deployment_schema["route_prefix"] = "/"
DeploymentSchema.parse_obj(deployment_schema)
# Ensure route_prefix of None works
deployment_schema["route_prefix"] = None
DeploymentSchema.parse_obj(deployment_schema)
