Add Super pipeline for code transforms.

.make.versions

@@ -16,7 +16,7 @@ FILTER_VERSION=0.3.0
 NOOP_VERSION=0.8.0
 RESIZE_VERSION=0.3.0
 LANG_ID_VERSION=0.3.0
-TOKENIZER_VERSION=0.3.0
+TOKENIZATION_VERSION=0.3.0
 MALWARE_VERSION=0.4.0
 PROGLANG_SELECT_VERSION=0.3.0
 CODE_QUALITY_VERSION=0.3.0

kfp/doc/multi_transform_pipeline.md

@@ -23,13 +23,30 @@ In the list of its input parameters, we also see `data_s3_config`. Now, we have
 
 ![param list](param_list2.png)
 
+### Examples
 
-**Note** An example super pipeline that combines several transforms, `doc_id`, `ededup`, and `fdedup`, can be found in [superworkflow_dedups_sample_wf.py](../superworkflows/v1/superworkflow_dedups_sample_wf.py).
+The sections that follow display two super pipelines as examples:
+
+1) [dedups super pipeline](#dedups)
+1) [programming languages super pipeline](#code)
+
+### Dedups super pipeline <a name = "dedups"></a>
+
+This pipeline combines several transforms, `doc_id`, `ededup`, and `fdedup`, can be found in [superworkflow_dedups_sample_wf.py](../superworkflows/ray/kfp_v1/superworkflow_dedups_sample_wf.py).
 
 ![super pipeline](super_pipeline.png)
 
+The input parameters of the super pipelines are described in this [section](#super-pipeline-Input-Parameters).
+
+### Programming languages super pipeline <a name = "code"></a>
+
+This pipeline combines transforms for programming languages data preprocessing: `ededup`, `doc_id`, `fdedup`, `proglang_select`, `code_quality`,  `malware` and `tokenization`. It can be found in [superworkflow_code_wf.py](../superworkflows/ray/kfp_v1/superworkflow_code_sample_wf.py).
+
+![super pipeline](super-code-pipeline.png)
+
+The input parameters of the super pipelines are described in this [section](#Super-pipeline-Input-Parameters).
 
-The input parameters of the super pipelines:
+### Super Pipeline Input Parameters
 
 There are several `groups` of input parameters for super pipelines, each group of parameters has a prefix of "p<x>_" string, where <x> is an order number.
 

kfp/kfp_ray_components/src/execute_ray_job_multi_s3.py

@@ -62,7 +62,7 @@
     # Execute Ray jobs
     execute_ray_jobs(
         name=cluster_name,
-        additional_params=KFPUtils.load_from_json(args.additional_params),
+        additional_params=KFPUtils.load_from_json(args.additional_params.replace("'", '"')),
         e_params=exec_params,
         exec_script_name=args.exec_script_name,
         server_url=args.server_url,

kfp/superworkflows/Makefile

@@ -2,27 +2,22 @@ REPOROOT=../../
 # Use make help, to see the available rules
 include ${REPOROOT}/.make.defaults
 
-clean::
-	@# Help: Recursively make $@ all subdirs 
-	$(MAKE) RULE=$@ .recurse
+.PHONY: workflow-venv
+workflow-venv:
+	$(MAKE) -C ray/kfp_v1 workflow-venv
 
-workflow-venv::
-	@# Help: Recursively make $@ in subdirs
-	$(MAKE) RULE=$@ .recurse	
+.PHONY: workflow-build
+workflow-build:
+	$(MAKE) -C ray/kfp_v1 workflow-build
 
-workflow-build::
-	@# Help: Recursively make $@ in subdirs
-	$(MAKE) RULE=$@ .recurse
+.PHONY: workflow-test
+workflow-test:
+	$(MAKE) -C ray/kfp_v1 workflow-test
 
-workflow-test::
-	@# Help: Recursively make $@ in subdirs
-	$(MAKE) RULE=$@ .recurse
-
-workflow-upload::
-	@# Help: Recursively make $@ in subdirs
-	$(MAKE) RULE=$@ .recurse
-
-workflow-reconcile-requirements::
-	@# Help: Recursively make $@ in all subdirs
-	@$(MAKE) RULE=$@ .recurse
+.PHONY: workflow-upload
+workflow-upload:
+	$(MAKE) -C ray/kfp_v1 workflow-upload
 
+.PHONY: workflow-reconcile-requirements
+workflow-reconcile-requirements:
+	$(MAKE) -C ray/kfp_v1 workflow-reconcile-requirements

kfp/superworkflows/v1/Makefile → kfp/superworkflows/ray/kfp_v1/Makefile

@@ -1,8 +1,8 @@
-REPOROOT=${CURDIR}/../../..
+REPOROOT=${CURDIR}/../../../..
 WORKFLOW_VENV_ACTIVATE=${REPOROOT}/transforms/venv/bin/activate
 include $(REPOROOT)/transforms/.make.transforms_workflows
 
-PYTHON_WF := $(shell find ./ -name *_wf.py)
+PYTHON_WF := $(shell find ./ -name "*_wf.py")
 YAML_WF=$(patsubst %.py, %.yaml, ${PYTHON_WF})
 
 workflow-venv:: .check_python_version ${WORKFLOW_VENV_ACTIVATE}

kfp/superworkflows/ray/kfp_v1/superworkflow_code_sample_wf.py

@@ -0,0 +1,237 @@
+import kfp.compiler as compiler
+import kfp.components as comp
+import kfp.dsl as dsl
+from kfp_support.workflow_support.utils import ONE_WEEK_SEC
+
+
+# Components
+# For every sub workflow we need a separate components, that knows about this subworkflow.
+component_spec_path = "../../../kfp_ray_components/"
+run_code_quality_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_malware_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_proglang_select_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_doc_id_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_exact_dedup_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_fuzzy_dedup_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+run_tokenization_op = comp.load_component_from_file(component_spec_path + "executeSubWorkflowComponent.yaml")
+
+proglang_select_image = "quay.io/dataprep1/data-prep-kit/proglang_select:0.3.0"
+code_quality_image = "quay.io/dataprep1/data-prep-kit/code_quality:0.3.0"
+malware_image = "quay.io/dataprep1/data-prep-kit/malware:0.4.0"
+doc_id_image = "quay.io/dataprep1/data-prep-kit/doc_id:0.3.1"
+ededup_image = "quay.io/dataprep1/data-prep-kit/ededup:0.3.0"
+fdedup_image = "quay.io/dataprep1/data-prep-kit/fdedup:0.3.0"
+tokenizer_image = "quay.io/dataprep1/data-prep-kit/tokenization:0.3.0"
+
+
+# Pipeline to invoke execution on remote resource
+@dsl.pipeline(
+    name="super-kubeflow-pipeline-code",
+    description="Super pipeline for programming languages data preprocessing",
+)
+def sample_code_ray_orchestrator(
+    # the super pipeline parameters
+    p1_orch_code_quality_name: str = "code_quality_wf",
+    p1_orch_malware_name: str = "malware_wf",
+    p1_orch_proglang_select_name: str = "proglang_select_wf",
+    p1_orch_doc_id_name: str = "doc_id_wf",
+    p1_orch_exact_dedup_name: str = "ededup_wf",
+    p1_orch_fuzzy_dedup_name: str = "fdedup_wf",
+    p1_orch_tokenization_wf_name: str = "tokenization_wf",
+    p2_pipeline_runtime_pipeline_id: str = "pipeline_id",
+    p2_pipeline_ray_head_options: str = '{"cpu": 1, "memory": 4, "image_pull_secret": ""}',
+    p2_pipeline_ray_worker_options: str = '{"replicas": 2, "max_replicas": 2, "min_replicas": 2, "cpu": 2, "memory": 4, "image_pull_secret": ""}',
+    p2_pipeline_server_url: str = "http://kuberay-apiserver-service.kuberay.svc.cluster.local:8888",
+    p2_pipeline_input_parent_path: str = "test/ingest2parquet/output/",
+    p2_pipeline_output_parent_path: str = "test/super/output/",
+    p2_pipeline_parent_path_suffix: str = "",
+    p2_pipeline_additional_params: str = '{"wait_interval": 2, "wait_cluster_ready_tmout": 400, "wait_cluster_up_tmout": 300, "wait_job_ready_tmout": 400, "wait_print_tmout": 30, "http_retries": 5}',
+    p2_pipeline_data_s3_access_secret: str = "s3-secret",
+    p2_pipeline_runtime_code_location: str = '{"github": "github", "commit_hash": "12345", "path": "path"}',
+    p2_pipeline_runtime_actor_options: str = '{"num_cpus": 0.8}',
+    p2_pipeline_data_max_files: int = -1,
+    p2_pipeline_data_num_samples: int = -1,
+    # Exact dedup step parameters
+    p3_name: str = "ededup",
+    p3_skip: bool = False,
+    p3_ededup_doc_column: str = "contents",
+    p3_ededup_hash_cpu: float = 0.5,
+    # data sampling
+    p3_ededup_n_samples: int = 10,
+    # overriding parameters
+    p3_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + ededup_image
+    + '"}, "ray_head_options": {"image": "'
+    + ededup_image
+    + '"}}',
+    # Document ID step parameters
+    p4_name: str = "doc_id",
+    p4_skip: bool = False,
+    # doc id parameters
+    p4_doc_id_doc_column: str = "contents",
+    p4_doc_id_hash_column: str = "hash_column",
+    p4_doc_id_int_column: str = "int_id_column",
+    # overriding parameters
+    p4_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + doc_id_image
+    + '"}, "ray_head_options": {"image": "'
+    + doc_id_image
+    + '"}}',
+    # Fuzzy dedup step parameters
+    p5_name: str = "fdedup",
+    p5_skip: bool = False,
+    # columns used
+    p5_fdedup_doc_column: str = "contents",
+    p5_fdedup_id_column: str = "int_id_column",
+    p5_fdedup_cluster_column: str = "cluster",
+    # orchestrator
+    # infrastructure
+    p5_fdedup_bucket_cpu: float = 0.5,
+    p5_fdedup_doc_cpu: float = 0.5,
+    p5_fdedup_mhash_cpu: float = 0.5,
+    # fuzzy parameters
+    p5_fdedup_num_permutations: int = 64,
+    p5_fdedup_threshold: float = 0.8,
+    p5_fdedup_shingles_size: int = 5,
+    p5_fdedup_delimiters: str = " ",
+    # random delay between reads
+    p5_fdedup_random_delay_limit: int = 5,
+    # snapshotting
+    p5_fdedup_snapshot_delay: int = 1,
+    p5_fdedup_use_doc_snapshot: bool = False,
+    p5_fdedup_use_bucket_snapshot: bool = False,
+    # data sampling
+    p5_fdedup_n_samples: int = 10,
+    # overriding parameters
+    p5_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + fdedup_image
+    + '"}, "ray_head_options": {"image": "'
+    + fdedup_image
+    + '"}}',
+    # proglang_select step parameters
+    p6_name: str = "proglang_select",
+    p6_skip: bool = False,
+    p6_proglang_select_allowed_langs_file: str = "test/proglang_select/languages/allowed-code-languages.txt",
+    p6_proglang_select_language_column: str = "programming_language",
+    p6_proglang_select_s3_access_secret: str = "s3-secret",
+    # overriding parameters
+    p6_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + proglang_select_image
+    + '"}, "ray_head_options": {"image": "'
+    + proglang_select_image
+    + '"}}',
+    # Code quality step parameters
+    p7_name: str = "code_quality",
+    p7_skip: bool = False,
+    p7_cq_contents_column_name: str = "contents",
+    p7_cq_language_column_name: str = "programming_language",
+    p7_cq_tokenizer: str = "codeparrot/codeparrot",
+    p7_cq_hf_token: str = "None",
+    # orchestrator
+    # overriding parameters
+    p7_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + code_quality_image
+    + '"}, "ray_head_options": {"image": "'
+    + code_quality_image
+    + '"}}',
+    # malware step parameters
+    p8_name: str = "malware",
+    p8_skip: bool = False,
+    p8_malware_input_column: str = "contents",
+    p8_malware_output_column: str = "virus_detection",
+    # orchestrator
+    # overriding parameters
+    p8_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + malware_image
+    + '"}, "ray_head_options": {"image": "'
+    + malware_image
+    + '"}}',
+    # tokenization parameters
+    p9_name: str = "tokenization",
+    p9_skip: bool = False,
+    p9_tkn_tokenizer: str = "hf-internal-testing/llama-tokenizer",
+    p9_tkn_doc_id_column: str = "document_id",
+    p9_tkn_doc_content_column: str = "contents",
+    p9_tkn_text_lang: str = "en",
+    p9_tkn_tokenizer_args: str = "cache_dir=/tmp/hf",
+    p9_tkn_chunk_size: int = 0,
+    p9_overriding_params: str = '{"ray_worker_options": {"image": "'
+    + tokenizer_image
+    + '"}, "ray_head_options": {"image": "'
+    + tokenizer_image
+    + '"}}',
+):
+
+    # get all arguments
+    args = locals()
+    orch_host = "http://ml-pipeline:8888"
+
+    def _set_component(op: dsl.BaseOp, displaied_name: str, prev_op: dsl.BaseOp = None):
+        # set the sub component UI name
+        op.set_display_name(displaied_name)
+
+        # Add pod labels
+        op.add_pod_label("app", "ml-pipeline").add_pod_label("component", "code-pipelines")
+        # No cashing
+        op.execution_options.caching_strategy.max_cache_staleness = "P0D"
+        # image pull policy
+        op.set_image_pull_policy("Always")
+        # Set the timeout for each task to one week (in seconds)
+        op.set_timeout(ONE_WEEK_SEC)
+        if prev_op is not None:
+            op.after(prev_op)
+
+    # exact deduplication
+    exact_dedup = run_exact_dedup_op(
+        name=p1_orch_exact_dedup_name,
+        prefix="p3_",
+        params=args,
+        host=orch_host,
+        input_folder=p2_pipeline_input_parent_path,
+    )
+    _set_component(exact_dedup, "exact dedup")
+    # document ID
+    doc_id = run_doc_id_op(
+        name=p1_orch_doc_id_name, prefix="p4_", params=args, host=orch_host, input_folder=exact_dedup.output
+    )
+    _set_component(doc_id, "doc ID", exact_dedup)
+    # fuzzy deduplication
+    fuzzy_dedup = run_fuzzy_dedup_op(
+        name=p1_orch_fuzzy_dedup_name, prefix="p5_", params=args, host=orch_host, input_folder=doc_id.output
+    )
+    _set_component(fuzzy_dedup, "fuzzy dedup", doc_id)
+
+    # proglang_select
+    proglang_select = run_proglang_select_op(
+        name=p1_orch_proglang_select_name,
+        prefix="p6_",
+        params=args,
+        host=orch_host,
+        input_folder=fuzzy_dedup.output,
+    )
+    _set_component(proglang_select, "proglang_select", fuzzy_dedup)
+
+    # code_quality
+    code_quality = run_code_quality_op(
+        name=p1_orch_code_quality_name, prefix="p7_", params=args, host=orch_host, input_folder=proglang_select.output
+    )
+    _set_component(code_quality, "code_quality", proglang_select)
+
+    # malware
+    malware = run_malware_op(
+        name=p1_orch_malware_name, prefix="p8_", params=args, host=orch_host, input_folder=code_quality.output
+    )
+    _set_component(malware, "malware", code_quality)
+    # malware
+    tokenization = run_tokenization_op(
+        name=p1_orch_tokenization_wf_name, prefix="p9_", params=args, host=orch_host, input_folder=malware.output
+    )
+    _set_component(tokenization, "tokenization", malware)
+
+    # Configure the pipeline level to one week (in seconds)
+    dsl.get_pipeline_conf().set_timeout(ONE_WEEK_SEC)
+
+
+if __name__ == "__main__":
+    # Compiling the pipeline
+    compiler.Compiler().compile(sample_code_ray_orchestrator, __file__.replace(".py", ".yaml"))