Editing files to add resource requests and limits (elyra-ai#3202)

Signed-off-by: Author Name [email protected]
Signed-off-by: Paloma Rebuelta <[email protected]>

docs/source/getting_started/changelog.md

@@ -2,8 +2,11 @@
 
 A summary of new feature highlights is located on the [GitHub release page](https://github.com/elyra-ai/elyra/releases).
 
-## Release 3.15.0 - 03/28/2023
+## Release 4.0.0
+
+- Add functionality to select resource limits from the GUI [#3202](https://github.com/elyra-ai/elyra/pull/3202)
 
+## Release 3.15.0 - 03/28/2023
 
 ## Release 3.15.0rc0 - 03/28/2023
 

elyra/pipeline/airflow/processor_airflow.py

@@ -342,6 +342,8 @@ def _cc_pipeline(self, pipeline: Pipeline, pipeline_name: str, pipeline_instance
                     "image_pull_policy": image_pull_policy,
                     "cpu_request": operation.cpu,
                     "mem_request": operation.memory,
+                    "cpu_limit": operation.cpu_limit,
+                    "memory_limit": operation.memory_limit,
                     "gpu_limit": operation.gpu,
                     "operator_source": operation.filename,
                 }

elyra/pipeline/kfp/processor_kfp.py

@@ -843,6 +843,11 @@ def _generate_workflow_tasks(
                     "size": operation.memory,
                     "units": "G",
                 }
+                workflow_task["task_modifiers"]["cpu_limit"] = operation.cpu_limit
+                workflow_task["task_modifiers"]["memory_limit"] = {
+                    "size": operation.memory_limit,
+                    "units": "G",
+                }
                 gpu_vendor = "nvidia.com/gpu"
                 if operation.gpu_vendor:
                     gpu_vendor = operation.gpu_vendor

elyra/pipeline/pipeline.py

@@ -246,6 +246,8 @@ def __init__(
                 outputs: List of files produced by this operation to be included in a child operation(s)
                 cpu: number of cpus requested to run the operation
                 memory: amount of memory requested to run the operation (in Gi)
+                cpu_limit: limit of number of cpus to run the operation
+                memory_limit: limit of amount of memory to run the operation (in Gi)
                 gpu: number of gpus requested to run the operation
                 parameters: a list of names of pipeline parameters that should be passed to this operation
                 gpu_vendor: gpu resource type, eg. nvidia.com/gpu, amd.com/gpu etc.
@@ -261,19 +263,39 @@ def __init__(
         if not component_props.get("runtime_image"):
             raise ValueError("Invalid pipeline operation: Missing field 'operation runtime image'.")
         if component_props.get("cpu") and not self._validate_range(component_props.get("cpu"), min_value=1):
-            raise ValueError("Invalid pipeline operation: CPU must be a positive value or None")
+            raise ValueError("Invalid pipeline operation: CPU request must be a positive value or None")
+        if component_props.get("cpu_limit") and not self._validate_range(component_props.get("cpu_limit"), min_value=1):
+            raise ValueError("Invalid pipeline operation: CPU limit must be a positive value or None")
         if component_props.get("gpu") and not self._validate_range(component_props.get("gpu"), min_value=0):
             raise ValueError("Invalid pipeline operation: GPU must be a positive value or None")
         if component_props.get("memory") and not self._validate_range(component_props.get("memory"), min_value=1):
-            raise ValueError("Invalid pipeline operation: Memory must be a positive value or None")
+            raise ValueError("Invalid pipeline operation: Memory request must be a positive value or None")
+        if component_props.get("memory_limit") and not self._validate_range(
+            component_props.get("memory_limit"), min_value=1
+        ):
+            raise ValueError("Invalid pipeline operation: Memory limit must be a positive value or None")
+        if (
+            component_props.get("memory_limit")
+            and component_props.get("memory")
+            and component_props.get("memory_limit") < component_props.get("memory")
+        ):
+            raise ValueError("Invalid pipeline operation: Memory limit must be equal or larger than memory request")
+        if (
+            component_props.get("cpu_limit")
+            and component_props.get("cpu")
+            and component_props.get("cpu_limit") < component_props.get("cpu")
+        ):
+            raise ValueError("Invalid pipeline operation: CPU limit must be equal or larger than CPU request")
 
         # Re-build object to include default values
         self._component_props["filename"] = component_props.get("filename")
         self._component_props["runtime_image"] = component_props.get("runtime_image")
         self._component_props["dependencies"] = Operation._scrub_list(component_props.get("dependencies", []))
         self._component_props["include_subdirectories"] = component_props.get("include_subdirectories", False)
         self._component_props["cpu"] = component_props.get("cpu")
+        self._component_props["cpu_limit"] = component_props.get("cpu_limit")
         self._component_props["memory"] = component_props.get("memory")
+        self._component_props["memory_limit"] = component_props.get("memory_limit")
         self._component_props["gpu"] = component_props.get("gpu")
         self._component_props["gpu_vendor"] = component_props.get("gpu_vendor")
         self._component_props["parameters"] = component_props.get(PIPELINE_PARAMETERS, [])
@@ -316,10 +338,18 @@ def env_vars(self) -> ElyraPropertyList[EnvironmentVariable]:
     def cpu(self) -> Optional[str]:
         return self._component_props.get("cpu")
 
+    @property
+    def cpu_limit(self) -> Optional[str]:
+        return self._component_props.get("cpu_limit")
+
     @property
     def memory(self) -> Optional[str]:
         return self._component_props.get("memory")
 
+    @property
+    def memory_limit(self) -> Optional[str]:
+        return self._component_props.get("memory_limit")
+
     @property
     def gpu(self) -> Optional[str]:
         return self._component_props.get("gpu")

elyra/pipeline/validation.py

@@ -431,7 +431,13 @@ async def _validate_generic_node_properties(
         # If not running locally, we check resource and image name
         if pipeline_runtime != "local":
             self._validate_container_image_name(node.id, node_label, image_name, response=response)
-            for resource_name in ["cpu", "gpu", "memory"]:
+            for resource_name in [
+                "cpu",
+                "gpu",
+                "memory",
+                "cpu_limit",
+                "memory_limit",
+            ]:
                 resource_value = node.get_component_parameter(resource_name)
                 if resource_value:
                     self._validate_resource_value(
@@ -638,7 +644,7 @@ def _validate_resource_value(
         Validates the value for hardware resources requested
         :param node_id: the unique ID of the node
         :param node_label: the given node name or user customized name/label of the node
-        :param resource_name: the name of the resource e.g. cpu, gpu. memory
+        :param resource_name: the name of the resource e.g. cpu, cpu_limit, gpu, memory, memory_limit
         :param resource_value: the value of the resource
         :param response: ValidationResponse containing the issue list to be updated
         """

elyra/templates/airflow/airflow_template.jinja2

@@ -47,14 +47,20 @@ op_{{ operation.id|regex_replace }} = KubernetesPodOperator(name='{{ operation.n
                                                             arguments=["{{ operation.argument_list }}"],
                                                             task_id='{{ operation.notebook|regex_replace }}',
                                                             env_vars={{ operation.pipeline_envs }},
-        {% if operation.cpu_request or operation.mem_request or operation.gpu_limit %}
+        {% if operation.cpu_request or operation.mem_request or operation.cpu_limit or operation.memory_limit or operation.gpu_limit %}
                                                             resources = {
             {% if operation.cpu_request %}
                                                                        'request_cpu': '{{ operation.cpu_request }}',
             {% endif %}
             {% if operation.mem_request %}
                                                                        'request_memory': '{{ operation.mem_request }}G',
             {% endif %}
+            {% if operation.cpu_limit %}
+                                                                       'limit_cpu': '{{ operation.cpu_limit }}',
+            {% endif %}
+            {% if operation.memory_limit %}
+                                                                       'limit_memory': '{{ operation.memory_limit }}G',
+            {% endif %}
             {% if operation.gpu_limit %}
                                                                        'limit_gpu': '{{ operation.gpu_limit }}',
             {% endif %}

elyra/templates/components/generic_properties_template.jinja2

@@ -37,14 +37,26 @@
         },
         "cpu": {
           "type": "integer",
-          "title": "CPU",
-          "description": "For CPU-intensive workloads, you can choose more than 1 CPU (e.g. 1.5).",
+          "title": "CPU request",
+          "description": "For CPU-intensive workloads, you can request more than 1 CPU (e.g. 1.5, this is optional).",
+          "minimum": 0
+        },
+        "cpu_limit": {
+          "type": "integer",
+          "title": "CPU limit",
+          "description": "The maximum CPU that can be allocated to this node. This should be equal or higher than the request",
           "minimum": 0
         },
         "memory": {
           "type": "integer",
-          "title": "RAM(GB)",
-          "description": "The total amount of RAM specified.",
+          "title": "RAM request (GB)",
+          "description": "The total amount of RAM requested (optional).",
+          "minimum": 0
+        },
+        "memory_limit": {
+          "type": "integer",
+          "title": "RAM limit (GB)",
+          "description": "The maximum amount of RAM allowed. This should be equal or higher than the request",
           "minimum": 0
         },
         "gpu": {

elyra/templates/kubeflow/v1/python_dsl_template.jinja2

@@ -66,6 +66,12 @@ def generated_pipeline(
 {%  if workflow_task.task_modifiers.mem_request and workflow_task.task_modifiers.mem_request.size %}
     {{ task_name }}.container.set_memory_request(memory="{{ workflow_task.task_modifiers.mem_request.size }}{{ workflow_task.task_modifiers.mem_request.units }}")
 {%  endif %}
+{%  if workflow_task.task_modifiers.cpu_limit %}
+    {{ task_name }}.container.set_cpu_limit(cpu="{{ workflow_task.task_modifiers.cpu_limit }}")
+{%  endif %}
+{%  if workflow_task.task_modifiers.memory_limit and workflow_task.task_modifiers.memory_limit.size %}
+    {{ task_name }}.container.set_memory_limit(memory="{{ workflow_task.task_modifiers.memory_limit.size }}{{ workflow_task.task_modifiers.memory_limit.units }}")
+{%  endif %}
 {%  if workflow_task.task_modifiers.gpu_limit and workflow_task.task_modifiers.gpu_limit.size %}
     {{ task_name }}.container.add_resource_limit(resource_name="{{ workflow_task.task_modifiers.gpu_limit.vendor }}", value="{{ workflow_task.task_modifiers.gpu_limit.size }}")
 {%  endif %}

elyra/tests/pipeline/kfp/conftest.py

@@ -177,7 +177,14 @@ def metadata_dependencies(metadata_managers, request):
     # Create a Pipeline object from the pipeline file, applying the customization
     # options
     customization_options = {}
-    for supported_option in ["with_cos_object_prefix", "resources_cpu", "resources_gpu", "resources_memory"]:
+    for supported_option in [
+        "with_cos_object_prefix",
+        "resources_cpu",
+        "resources_cpu_limit",
+        "resources_gpu",
+        "resources_memory",
+        "resources_memory_limit",
+    ]:
         customization_options[supported_option] = request.param.get(supported_option)
     pipeline_object = get_pipeline_object(
         pipeline_filename=request.param["pipeline_file"],
@@ -361,6 +368,8 @@ def get_pipeline_object(
       - "resources_cpu" (number, applied to all generic nodes)
       - "resources_gpu" (number, applied to all generic nodes)
       - "resources_memory" (number, applied to all generic nodes)
+      - "resources_cpu_limit" (number, applied to all generic nodes)
+      - "resources_memory_limit" (number, applied to all generic nodes)
     """
     assert pipeline_filename is not None, "A pipeline filename is required."
 
@@ -409,6 +418,10 @@ def get_pipeline_object(
                     node["app_data"]["component_parameters"]["cpu"] = customization_options["resources_cpu"]
                 else:
                     node["app_data"]["component_parameters"].pop("cpu", None)
+                if customization_options.get("resources_cpu_limit") is not None:
+                    node["app_data"]["component_parameters"]["cpu_limit"] = customization_options["resources_cpu_limit"]
+                else:
+                    node["app_data"]["component_parameters"].pop("cpu_limit", None)
                 if customization_options.get("resources_gpu") is not None:
                     node["app_data"]["component_parameters"]["gpu"] = customization_options["resources_gpu"]
                 else:
@@ -417,6 +430,12 @@ def get_pipeline_object(
                     node["app_data"]["component_parameters"]["memory"] = customization_options["resources_memory"]
                 else:
                     node["app_data"]["component_parameters"].pop("memory", None)
+                if customization_options.get("resources_memory_limit") is not None:
+                    node["app_data"]["component_parameters"]["memory_limit"] = customization_options[
+                        "resources_memory_limit"
+                    ]
+                else:
+                    node["app_data"]["component_parameters"].pop("memory_limit", None)
 
     # Parse JSON and return Pipeline instance
     return PipelineParser().parse(pipeline_json=pipeline_json)

elyra/tests/pipeline/kfp/test_processor_kfp.py

@@ -943,14 +943,18 @@ def test_generate_pipeline_dsl_compile_pipeline_dsl_one_generic_node_pipeline_te
 
     op = list(pipeline.operations.values())[0]
 
-    if op.gpu or op.cpu or op.memory:
+    if op.gpu or op.cpu or op.memory or op.cpu_limit or op.memory_limit:
         assert node_template["container"].get("resources") is not None
         if op.gpu:
             assert node_template["container"]["resources"]["limits"]["nvidia.com/gpu"] == str(op.gpu)
         if op.cpu:
             assert node_template["container"]["resources"]["requests"]["cpu"] == str(op.cpu)
         if op.memory:
             assert node_template["container"]["resources"]["requests"]["memory"] == f"{op.memory}G"
+        if op.cpu_limit:
+            assert node_template["container"]["resources"]["limits"]["cpu"] == str(op.cpu_limit)
+        if op.memory_limit:
+            assert node_template["container"]["resources"]["limits"]["memory"] == f"{op.memory_limit}G"
 
 
 @pytest.fixture(autouse=False)

elyra/tests/pipeline/test_pipeline_constructor.py

@@ -494,6 +494,40 @@ def test_fail_creating_operation_with_negative_cpu_resources():
         )
 
 
+def test_fail_creating_operation_with_more_requests_than_limit_cpu():
+    component_parameters = {
+        "filename": "elyra/pipeline/tests/resources/archive/test.ipynb",
+        "cpu": "4",
+        "cpu_limit": "2",
+        "runtime_image": "tensorflow/tensorflow:latest",
+    }
+    with pytest.raises(ValueError):
+        GenericOperation(
+            id="test-id",
+            type="execution-node",
+            classifier="execute-notebook-node",
+            name="test",
+            component_props=component_parameters,
+        )
+
+
+def test_fail_creating_operation_with_more_requests_than_limit_memory():
+    component_parameters = {
+        "filename": "elyra/pipeline/tests/resources/archive/test.ipynb",
+        "memory": "4",
+        "memory_limit": "2",
+        "runtime_image": "tensorflow/tensorflow:latest",
+    }
+    with pytest.raises(ValueError):
+        GenericOperation(
+            id="test-id",
+            type="execution-node",
+            classifier="execute-notebook-node",
+            name="test",
+            component_props=component_parameters,
+        )
+
+
 def test_fail_creating_operation_with_0_memory_resources():
     component_parameters = {
         "filename": "elyra/pipeline/tests/resources/archive/test.ipynb",

packages/pipeline-editor/src/FileSubmissionDialog.tsx

@@ -86,13 +86,24 @@ export const FileSubmissionDialog: React.FC<IProps> = ({
       <br />
       <div className="elyra-resourcesWrapper">
         <div className="elyra-resourceInput">
-          <label htmlFor="cpu"> CPU:</label>
+          <label htmlFor="cpu"> CPU request:</label>
           <div className="elyra-resourceInputDescription" id="cpu-description">
-            For CPU-intensive workloads, you can choose more than 1 CPU (e.g.
-            1.5).
+            For CPU-intensive workloads, you can request more than 1 CPU (e.g.
+            1.5, this is optional).
           </div>
           <input id="cpu" type="number" name="cpu" />
         </div>
+        <div className="elyra-resourceInput">
+          <label htmlFor="cpu_limit"> CPU limit:</label>
+          <div
+            className="elyra-resourceInputDescription"
+            id="cpu-limit-description"
+          >
+            The maximum CPU that can be allocated to this node. This should be
+            equal or higher than the request
+          </div>
+          <input id="cpu_limit" type="number" name="cpu_limit" />
+        </div>
         <div className="elyra-resourceInput">
           <label htmlFor="gpu"> GPU:</label>
           <div className="elyra-resourceInputDescription" id="gpu-description">
@@ -102,15 +113,26 @@ export const FileSubmissionDialog: React.FC<IProps> = ({
           <input id="gpu" type="number" name="gpu" />
         </div>
         <div className="elyra-resourceInput">
-          <label htmlFor="memory"> RAM (GB):</label>
+          <label htmlFor="memory"> RAM request (GB):</label>
           <div
             className="elyra-resourceInputDescription"
             id="memory-description"
           >
-            The total amount of RAM specified.
+            The total amount of RAM requested (optional).
           </div>
           <input id="memory" type="number" name="memory" />
         </div>
+        <div className="elyra-resourceInput">
+          <label htmlFor="memory_limit"> RAM limit (GB):</label>
+          <div
+            className="elyra-resourceInputDescription"
+            id="memory-limit-description"
+          >
+            The maximum amount of RAM allowed. This should be equal or higher
+            than the request
+          </div>
+          <input id="memory_limit" type="number" name="memory_limit" />
+        </div>
       </div>
       <br />
       <input

packages/pipeline-editor/src/PipelineEditorWidget.tsx

@@ -777,9 +777,15 @@ const PipelineWrapper: React.FC<IProps> = ({
         if (node.app_data.component_parameters.cpu === null) {
           delete node.app_data.component_parameters.cpu;
         }
+        if (node.app_data.component_parameters.cpu_limit === null) {
+          delete node.app_data.component_parameters.cpu_limit;
+        }
         if (node.app_data.component_parameters.memory === null) {
           delete node.app_data.component_parameters.memory;
         }
+        if (node.app_data.component_parameters.memory_limit === null) {
+          delete node.app_data.component_parameters.memory_limit;
+        }
         if (node.app_data.component_parameters.gpu === null) {
           delete node.app_data.component_parameters.gpu;
         }

packages/pipeline-editor/src/SubmitFileButtonExtension.tsx

@@ -128,8 +128,10 @@ export class SubmitFileButtonExtension<
       runtime_config,
       framework,
       cpu,
+      cpu_limit,
       gpu,
       memory,
+      memory_limit,
       dependency_include,
       dependencies,
       ...envObject
@@ -145,8 +147,10 @@ export class SubmitFileButtonExtension<
       dependency_include ? dependencies.split(',') : undefined,
       envObject,
       cpu,
+      cpu_limit,
       gpu,
-      memory
+      memory,
+      memory_limit
     );
 
     PipelineService.submitPipeline(