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chore(deps): update dependency kfp to v2 - autoclosed #31

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chore(deps): update dependency kfp to v2 - autoclosed #31

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@renovate renovate bot commented Sep 24, 2023 •
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This PR contains the following updates:

Package Change Age Adoption Passing Confidence
kfp (changelog) ==1.8.22 -> ==2.7.0 age adoption passing confidence

Release Notes

kubeflow/pipelines (kfp)

v2.0.1

Compare Source

v2.0.0

Compare Source

⚠ BREAKING CHANGES
  • SDK: SDK client v2beta1 API integration. Fixes #​8706 (#​9112)
  • sdk: Implement Graph Component (#​8179)
  • sdk: make CLI output consistent, readable, and usable (#​7739)
  • sdk: promote v2 compiler command and deprecate v1 command (#​7508)
  • sdk: Support submitting pipeline IR in yaml format via kfp.client (#​7458)
  • sdk: use yaml for IR package (#​7431)
  • sdk: rename commands, arguments parameters to command, args (#​7391)
  • sdk: throw error for output_component_file (#​7390)
  • sdk: move v2 to main namespace (#​7376)
  • sdk: move v1 to deprecated folder (#​7291)
  • sdk: drop support for python 3.6 (#​7303)
  • Use Argo Emissary Executor instead of Docker by default. Partial #​5718 (#​7137)
  • sdk.v2: Block task dependency referencing tasks inside a sibling condition or loop group. (#​7050)
  • sdk: Deprecate V2 compatible mode in v1 compiler (#​6958)
  • sdk.v2: Merge v2 experimental change back to v2 namespace (#​6890)
Features
  • backend: Add nodeSelector support. Closes #​8959. (#​9132) (276f922)
  • backend: add parameter verification before submitting the workflow (#​9228) (52c4c6f)
  • backend: add schema version check (#​9447) (08494a2)
  • backend: add support for resource requests. Closes #​7047. Closes #​6354. (#​9088) (37dac45)
  • backend: avoid downcast and use ExecutionSpec if possible (#​9232) (6c72d95)
  • backend: Implement aws-go-sdk crendentials to support IRSA for s3 in V2 (#​9502) (8a3215e)
  • backend: support pvc creation, deletion and mount; fixes #​8708 (#​9106) (761a592)
  • backend: support secrets (#​9178) (b8caf81)
  • backend: updates compiler to include kubernetes-specific specs in argo workflow (#​9059) (a3e795a)
  • component: Adds Vertex Pipelines prompt validation component (249f235)
  • components: add a check for model garden models and skip eval import (1782ee2)
  • components: Add a remote runner for pipelines (274ac8b)
  • components: Add force_dircet_runner flag to pipeline options (f167e15)
  • components: Add instructions for formatting BiasConfig input proto using json_format in Model & Data bias component (3a89044)
  • components: Add logic in import_model_evaluation to accept explanations from slices (4397b8c)
  • components: Add machine type and encryption key for Error Analysis Component (0293fe1)
  • components: Add machine type for Feature Extractor component. Deprecate Dataflow-related inputs (4e85352)
  • components: add preview directory to GCPC (b167f87)
  • components: Add slicing_specs input to classification evaluation (6a55449)
  • components: Add utility function for constructing the serverless custom job launcher spec (6fb10f3)
  • components: Allow batch predict component to add missing bq:// schemes (8cc0550)
  • components: Allow importing LLM eval metrics (ecc4ae0)
  • components: Change ResolveVertexModelOp name to GetVertexModelOp (6a916e8)
  • components: Create ResolveVertexModelOp component (595ae8e)
  • components: Define Data Bias component for detecting data bias metrics (7ab5d97)
  • components: Define Model Bias component for detecting model bias metrics (7022007)
  • components: Derive image tag from Eval container version. Align Eval image version for all Eval components in GCPC (63936c0)
  • components: Fix batch prediction job proto bigquery payload sanitization (a7b8fd0)
  • components: Import user slices to the model evaluation importer (8c9b716)
  • components: make GCPC artifacts usable in KFP Python components (6104ff6)
  • components: Move model eval components (48668bc)
  • components: Move model evaluation components to v1 (f2ad300)
  • components: Move model evaluation feature attribution component to preview namespace (dc6f431)
  • components: Provide model evaluation pipelines (9ce827e)
  • components: Release the Seq2Seq and Temporal Fusion Transformer pipelines (377b961)
  • components: Remove experimental evaluation components (69ea826)
  • components: Remove GetVertexModelOp, to add to preview later (85f6969)
  • components: Sagemaker V2 Hosting components and tests (#​9243) (4818e84)
  • components: SageMaker V2 model monitor component and testing (#​9253) (07e67bb)
  • components: SageMaker V2 model monitor component release (#​9368) (29444f9)
  • components: Support Instance Config in kubeflow model_batch_predict component (3166418)
  • components: Support model garden models in GetVertexModelOp (0b32899)
  • components: Update eval component with the latest GCPC container image version (a3418b3)
  • components: Update GCPC image version in two Eval importer components (1f4d943)
  • components: Update import_model_evaluation so models with 100+ labels will not import confusion matrices at every threshold (cb7d9a8)
  • frontend: make container name configurable (#​9433) (bb9dc67)
  • sdk: support compiling components with dsl.PipelineTaskFinalStatus type (#​9082) (7890227)
  • sdk: support extracting input/output descriptions from component/pipeline docstrings (#​9156) (946c51b)
  • sdk: support indexing into top-level artifact metadata in Container Components (#​9131) (5828632)
  • sdk: Support PIPELINE_ROOT_PLACEHOLDER (#​9134) (5e98b3b)
  • sdk: Support setting cpu/memory requests. (#​9121) (a6ef77b)
  • sdk: Support submitting pipeline with platform config. (#​9140) (952e073)
  • sdk: support writing TASK_FINAL_STATUS parameter type (#​9080) (c01288d)
  • SDK: SDK client v2beta1 API integration. Fixes #​8706 (#​9112) (07d6c18)
  • Add cpu_request and memory_request in pipeline_spec. (#​9063) (d2db64b)
  • add TASK_FINAL_STATUS to PipelineSpec ParameterTypeEnum (#​9061) (902e2a9)
  • API: Update IR go package (#​8614) (c30648a)
  • backend: add run support for v2 api (#​8647) (d524464)
  • backend: add support for "finished_at" and others in filter. Fixes #​8654 (#​8662) (6ee7677)
  • backend: Add support for converting v2 recurring run to scheduled workflow in template (#​8521) (7e7e1af)
  • backend: add support for environment variables. Fixes #​8704 (#​8886) (faca1e5)
  • backend: Add support for recurring run v2 api (#​8634) (d0f0ab3)
  • backend: Make cache-server webhook port number configurable (#​8401) (3824c5b)
  • backend: Refactor apiserver, add Pipeline and other v2beta services (#​8633) (135dc64)
  • backend: support optional and default parameters. Fixes #​8716 (#​8765) (89bdac9)
  • backend: support yaml with platform-specific specs (#​8983) (a9ead5a)
  • component: add evaluation_importer_gcp_resources to evaluated annotation importer component (d17916f)
  • component: change Error Analysis component to use CustomJob launcher (fd67277)
  • component: change Feature Extractor component to use CustomJob launcher (a725192)
  • component: Create component definition for GetVertexDataset (2d29137)
  • component: Create YAML definition for Feature Extractor Error Analysis component (e7c1a16)
  • component: define ImportEvaluatedAnnotation component (8c9fdee)
  • component: init container backend for evaluated annotation importer (74b86dc)
  • component: Merge annotation and error analysis in evaluated annotation importer (10e7c55)
  • component: Update input args in dataset preprocessor and evaluated annotation (9a32f76)
  • components: Add data-filter-split feature back to the ImageTrainingJOb component which was removed previously (4a4a968)
  • components: Add components for natural language: training TFHub model and preprocessing component for batch prediction (60b2d5f)
  • components: Add logs to Batch Prediction creation process (b3de27a)
  • components: Create GCPC v2 beta (834d966)
  • components: Create new component YAML definition for computing error analysis annotations (b7d03cb)
  • components: Create new component YAML definition for computing evaluated annotations (fe38716)
  • components: Create new component YAML definition for Evaluation Dataset Preprocessor Error Analysis (6800d21)
  • components: Dataflow Flex Template component (6101ff1)
  • components: Delete tfp_anomaly_detection (f2537d4)
  • components: Import model evaluation slices 50 at a time (39e4c36)
  • components: Propagate cost labels of GCP resources (7466803)
  • components: Update evaluation components to v0.9 and add input for quantile forecasting (74237dc)
  • components: update EvaluationDatasetPreprocessorOp to use KFP v2 Python definition (deed177)
  • sdk: add experiment_id parameter to create run methods (#​9004) (3e1f3c6)
  • add kubernetes platform-specific protos, generated Go code, and Python package (#​8888) (a4abf27)
  • add NodeSelector message to kfp-kubernetes proto (#​8981) (cd15b7a)
  • add platform-specific configuration protos to kfp-pipeline-spec package (#​8896) (643f421)
  • implement kfp-kubernetes library (#​8950) (0c11cce)
  • support nodeSelector in kfp-kubernetes (#​8982) (c8cb5b5)
  • backend: Add ExecutionClient to access ExecutionSpec (#​8050) (e8abec2)
  • backend: Add v2 api for experiments (#​8480) (6e364d3)
  • backend: authorize readArtifacts and ReportMetrics endpoints (#​7819) (1caa8e0)
  • backend: Expand ExecutionSpec Interface (#​7766) (06c9310)
  • backend: fix partner_id in GCP Marketplace application (#​8426) (3fca792)
  • backend: Implement RuntimeConfig in backend (#​8085) (2b556ec)
  • backend: Implement RuntimeConfig in backend for jobs(RecurringRun) (#​8152) (f25127f)
  • backend: Include namespace in Pipeline API model. Part of #​4197 (#​8375) (7c114a0)
  • backend: update minio-go to support irsa (#​7946) (7923ba3)
  • backend: Upload namespaced pipeline definitions. Part of #​4197 (#​8511) (931c14a)
  • cloud: Update JSON templates for evaluation (88a2b80)
  • components: Add DataprocBatch resource to gcp_resources output parameter (6e95e89)
  • components: Add display name to import model evaluation component (9b12f6e)
  • components: Add evaluation forecasting default of 0.5 for quantiles (21b8479)
  • components: Add Infra Validation remote runner (a06a4e6)
  • components: add KServe component flag to disable storing CRD status into output parameters (#​8393) (24f8651)
  • components: Add metadata field for pipeline resource name (82bf1ec)
  • components: Add model input to vertex ai model evaluation component (35b13b3)
  • components: add namespace to pvc creation (#​8147) (031a7d9)
  • components: Add nargs to allow for empty string input by component (555447f)
  • components: Add special case in json_util.py where explanation_spec metadata outputs can have empty values (b8b77fd)
  • components: Add text classification data processing component and training component (9675870)
  • components: Add vertex_notification_email component on v1 folder (3b1bd08)
  • components: Added BigQuery input support to evaluation components (bfa2dc6)
  • components: Allow dataset paths list (5d06871)
  • components: Create new tensorboard experiment creator component (a3c7c38)
  • components: Give evaluation preprocessing components unique dataflow job names (c052bf8)
  • components: Import model evaluation slices when available in the metrics (0d304c6)
  • components: Internal change (bf21b7b)
  • components: Introducing AWS SageMaker TrainingJob component v2 in Preview (#​8158) (f162b24)
  • components: Model Evaluation, rename EvaluationDataSplitterOp to TargetFieldDataRemoverOp, rename ground_truth_column to target_field, rename class_names to class_labels, and remove key_columns input (71c8e77)
  • components: New sagemaker training job parameters (#​8538) (6a6cfdb)
  • components: propagates vertex system labels to the downstream resources (batch prediction job) (4410bf2)
  • components: propagates vertex system labels to the downstream resources (bigquery job) (a506da6)
  • components: propagates vertex system labels to the downstream resources (custom job) (69e1e4b)
  • components: propagates vertex system labels to the downstream resources (dataflow python job) (4c2797e)
  • components: propagates vertex system labels to the downstream resources (dataproc) (7fe4319)
  • components: propagates vertex system labels to the downstream resources (Vertex AI Datasets) (9d9a8bb)
  • components: propagates vertex system labels to the downstream resources (Vertex AI Endpoints) (f37086b)
  • components: propagates vertex system labels to the downstream resources (Vertex AI HyperParameter Tuning Job) (cdd0626)
  • components: propagates vertex system labels to the downstream resources (Vertex AI Model Registry) (56edebb)
  • components: release Structured Data team's updated components and pipelines (b9a0499)
  • components: release Structured Data team's updated components and pipelines (bd1538d)
  • components: Release Structured Data team's updated components and pipelines (73034a9)
  • components: Separate feature attribution from evaluation component to its own component (f9cf42a)
  • components: Split evaluation component into classification, forecasting, and regression evaluation & create artifact types for google.__Metrics (8c74612)
  • components: Support serving default in bq export model job op (582576f)
  • components: Support uploading for model versions for ModelUploadOp (94bdce8)
  • components: Sync gcpc staging code to prod (01c9ed9)
  • components: Sync GCPC staging to prod to include AutoML model comparison (06761b9)
  • components: Update AutoML Tables components to have latest SDK features (49fdac6)
  • components: Update dataset_preprocessor component inputs (399b7be)
  • components: Update evaluation container to v0.5 for data sampler and splitter preprocessing components (37ff321)
  • components: Update evaluation container to v0.8.1 image (8d87bec)
  • components: Update import_model_evaluation component to accept new google.___Metrics artifact types (8eb61ad)
  • components: Update regression and forecasting to contain ground truth input fields (6ec9b71)
  • components: Updated components and pipelines (e358dee)
  • components: Updated components and pipelines (d1f1ee9)
  • docs: use new sdk reference docs theme (#​8212) (19cf904)
  • frontend: Add KFPv2 namespace check (#​8036) (9df8343)
  • frontend: Add loading and error states for HTML and Markdown displays (#​7989) (6cbc10b)
  • frontend: Add parent labels to the Compare Table (#​8024) (4be213a)
  • frontend: Add pre-check for pipeline and pipeline version name at the UI (#​8113) (58f3a60)
  • frontend: Add refresh and run re-selection functionality (#​8118) (d02857f)
  • frontend: Add ROC Curve filter table and functionality (#​8073) (23d549f)
  • frontend: Add run parameters (#​8105) (f96d3e9)
  • frontend: Complete Sub-DAG implementation in KFPv2. (#​8326) (21cf640)
  • frontend: Create two-level dropdown (#​7933) (832858b)
  • frontend: Creating run from various entry points (#​8190) (7d5985b)
  • frontend: Display HTML and Markdown files (#​7981) (cfe3278)
  • frontend: Display metrics loading and error states (#​8029) (4cb8562)
  • frontend: Display multi-level dropdown on KFPv2 Run Comparison page (#​7943) (53d8f7e)
  • frontend: Display ROC curve (#​8046) (cc3bd8b)
  • frontend: Display scalar metrics table (#​8026) (d3fe514)
  • frontend: Display two-panel layout and confusion matrices (#​7966) (617ad83)
  • frontend: Implement aws-js-sdk crendentials to support IRSA for s3 (#​8651) (9b9b3ac)
  • frontend: Show error message for invalid input or missing parameters. (#​8003) (303267f)
  • frontend: Show pipeline details (DAG) for an existing run without pipeline / pipeline version. (#​8116) (448b4ca)
  • frontend: Support Clone Run with RuntimeConfig (#​8093) (1257a35)
  • frontend: Support cloning recurringRun in KFP v2 (#​8652) (80c0dc5)
  • frontend: Support creating recurringRun in KFP v2. (#​8568) (a4a2488)
  • frontend: Support namespaced pipelines from the UI. Closes #​5084 (#​8831) (6996947)
  • frontend: v2 Dynamic Sub-DAG (I) (#​8278) (440f4e1)
  • google-cloud: add explanation_metadata_artifact input arg to custom Batch Prediction component. (ad364d9)
  • google-cloud: Add ground_truth_column input argument to data splitter component. (17d62e6)
  • google-cloud: Change evaluation preprocessing component output type. (059afb0)
  • google-cloud: Modify GCPC evaluation templates. (176d3ff)
  • google-cloud: Release eval changes with v0.3 (d2fd41b)
  • google-cloud: Release notes for 1.0.12 and 1.0.13 (e42d9d2)
  • google-cloud: Update eval container version for eval components (065f732)
  • IR: add is_optional field for input artifacts (#​8571) (998f52d)
  • IR: change is_list_of_artifacts proto field to is_artifact_list (#​8522) (041f446)
  • samples: Full Kubeflow E2E sample using KFPv2. (#​8303) (91fe29f)
  • sdk: Accepts higher PyYAML versions (#​8665) (6040334)
  • sdk: add --build-image option to 'kfp components build' to allow users to skip docker build. Fixes #​8382 for 2.0 (#​8387) (5b75d75)
  • sdk: Add comments to IR YAML file (#​8467) (49db63c)
  • sdk: add compilation logic for google artifact types (support custom artifact types pt. 2) (#​8232) (e371fa3)
  • sdk: Add default registry context (#​7948) (aab7fda)
  • sdk: add is_list_of_artifacts field to PipelineSpec [lists of artifacts support pt. 2] (#​8466) (6cd7cbc)
  • sdk: add pipeline job placholders for scheduled runs (#​8447) (e97fe8e)
  • sdk: add retry policy support to kfp v2 (#​7867) (850a750)
  • sdk: add runtime logic for custom artifact types (support for custom artifact types pt. 3) (#​8233) (166d6bb)
  • sdk: add support for lists of artifacts in Python components [support lists of artifacts pt. 3] (#​8465) (08b2408)
  • sdk: add support for metadata placeholders (#​8151) (88a1b31)
  • sdk: add workaround for google artifact (support custom artifact types pt. 4) (#​8279) (8ab690f)
  • sdk: Allow artifact inputs in pipeline definition. (#​8044) (1dd06cd)
  • sdk: deprecate .add_node_selector_constraint in favor of .set_accelerator_type (#​8980) (e96754c)
  • sdk: deprecate .set_gpu_limit in favor of .set_accelerator_limit (#​8836) (e7ad073)
  • sdk: enable dynamic importer metadata (#​7660) (c353245)
  • sdk: enable use of primitive placeholders in f-string (#​8494) (b829e4a)
  • sdk: expose IfPresentPlaceholder and ConcatPlaceholder to kfp.dsl (#​8145) (c7a90a3)
  • sdk: expose new ContainerSpec API (#​8144) (35fccb1)
  • sdk: Ignore upstream failure (#​8838) (5684bfc)
  • sdk: Implement Graph Component (#​8179) (5ce4954)
  • sdk: migrate v1 auth to v2 (#​7789) (e14a784)
  • sdk: rename kfp artifact attributes (support custom artifact types pt. 1) (#​8191) (72c1d10)
  • sdk: support compiling platform specific features (#​8940) (a38d747)
  • sdk: support for fan-in from dsl.ParallelFor (#​8631) (b575950)
  • sdk: support list of artifacts annotations [list of artifacts support pt. 1] (#​8464) (e7c82c0)
  • sdk: Support loading pipeline from yaml (#​8209) (410e99c)
  • sdk: support more than one exit handler per pipeline (#​8088) (bdff332)
  • sdk: support optional artifact inputs (#​8623) (151e8a3)
  • sdk: Support Parallelism in ParallelFor in KFP SDK V2 (#​8146) (51bea09)
  • sdk: Support pipeline outputs (#​8204) (48574dc)
  • sdk: Support using pipeline in exit handlers (#​8220) (d883582)
  • sdk: supporting bring your own container for arbitrary input and outputs (#​8066) (04c827f)
  • Upgrade argo-workflow to v3.3.8 (#​8009) (8bee292)
  • api: add runtime_config.parameter_values with string typed values (#​7734) (5b64733)
  • api: adds task name to PipelineTaskFinalStatus message (#​7452) (541f2ac)
  • api: Update IR with RetryPolicy (#​7581) (27d5404)
  • backend: Add ExecutionSpec Interface (#​7531) (8cf022c)
  • backend: add new endpoint that get pipeline by name (#​7004) (81438f3)
  • backend: Forbid unarchive runs that belog to archived experiment (#​7147) (96a6a3b)
  • backend: support IR YAML format in API (#​7499) (4f398dc)
  • backend: Upgrade go client for MLMD to 1.5.0. Partial #​7029 (#​7101) (ba59a64)
  • backend: use cert-manager for cache server cert (#​7843) (784f9fa)
  • chore: add labels and error to the gcp_resources.proto (bc56df6)
  • component: add BQ export model component (28c666f)
  • component: adding bq evaluate model component (27d2ab5)
  • component: Adds Vertex Pipelines notification email component. (e2687ce)
  • component: remove training_filter_split, validation_filter_split, test_filter_split as they are not working (ff99a98)
  • component: Support BigQuery drop model job components (affbc09)
  • component: Support BigQuery ML advanced weights job component (f6b560a)
  • component: Support BigQuery ML centroids job components (45cfb91)
  • component: Support BigQuery ML reconstruction loss and trial info job components (d2f33c8)
  • component: Support BigQuery ML weights job component (4183344)
  • components: Add a KServe component (#​6881) (72185ff)
  • components: Add AutoML Tables default pipeline with evaluation (1265649)
  • components: Add GetWorkerPoolSpecsOp and update sample notebook to include training new model from tuning results (30308ea)
  • components: Add IsMetricBeyondThresholdOp util function for HP tuning job; add tests for all util components (37b3397)
  • components: add nfs mount support for create_custom_training_job_op_from_component (0e316b6)
  • components: Add util components for getting best trial/hyperparameters; delete HP Tuning Job lightweight python version to avoid potential confusion (a62bdbe)
  • components: add utility library for google artifacts, and use the library for FPCs. Also fix BQML export model output param error. (a17e1d3)
  • components: cleanup the deprecated fields in v1 model upload component. (9738726)
  • components: create gcpc v1. (5baa487)
  • components: Create new import model evaluation component (00eb97c)
  • components: Expose reserved_ip_ranges to custom job component (89c741d)
  • components: Implement cancellation propagation (61d9210)
  • components: Implement delete_endpoint (1d3eaf7)
  • components: Implement delete_model (284b46e)
  • components: Implement undeploy_model component (3bc17be)
  • components: Improve AutoML Tables default pipeline with evaluation component (b98a2ab)
  • components: Outputting system.artifact and google.BQTable as a replacement for the google.VertexBatchPredictionJob artifact. (18b3ab8)
  • components: Take problem type as input rather than schema URI (d1c0c75)
  • components: Tests for import model evaluation (cdddaef)
  • components: Update batch prediction component to use artifact.uri instead of artifact.metadata['artifactUri'] (7d5690a)
  • components: update model upload component to accept the unmanaged model artifact (f341b67)
  • components/google-cloud: Accept UnmanagedContainerModel artifact in Batch Prediction component (e39eed1)
  • components/google-cloud: Add support for env variables in Custom_Job component. (5080288)
  • components/google-cloud: Support parametrized input for reserved_ip_range and other Vertex Training parameters in custom job utility. (be682e4)
  • conformance: adapt pipeline API tests to KF environment (#​7647) (694a274)
  • conformance: adapt pipelin

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@renovate renovate bot changed the title chore(deps): update dependency kfp to v2 chore(deps): update dependency kfp to v2 - autoclosed Feb 17, 2024
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