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MetricsTab.tsx
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MetricsTab.tsx
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/*
* Copyright 2021 The Kubeflow Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
import * as React from 'react';
import { useQuery } from 'react-query';
import { ErrorBoundary } from 'src/atoms/ErrorBoundary';
import { commonCss, padding } from 'src/Css';
import {
getArtifactTypes,
getOutputLinkedArtifactsInExecution,
LinkedArtifact,
} from 'src/mlmd/MlmdUtils';
import { ArtifactType, Execution } from 'src/third_party/mlmd';
import Banner from '../Banner';
import { MetricsVisualizations } from '../viewers/MetricsVisualizations';
import { ExecutionTitle } from './ExecutionTitle';
type MetricsTabProps = {
execution: Execution;
namespace: string | undefined;
};
/**
* Metrics tab renders metrics for the artifact of given execution.
* Some system metrics are: Confusion Matrix, ROC Curve, Scalar, etc.
* Detail can be found in https://github.com/kubeflow/pipelines/blob/master/sdk/python/kfp/dsl/io_types.py
* Note that these metrics are only available on KFP v2 mode.
*/
export function MetricsTab({ execution, namespace }: MetricsTabProps) {
let executionCompleted = false;
const executionState = execution.getLastKnownState();
if (
!(
executionState === Execution.State.NEW ||
executionState === Execution.State.UNKNOWN ||
executionState === Execution.State.RUNNING
)
) {
executionCompleted = true;
}
const executionId = execution.getId();
// Retrieving a list of artifacts associated with this execution,
// so we can find the artifact for system metrics from there.
const {
isLoading: isLoadingArtifacts,
isSuccess: isSuccessArtifacts,
error: errorArtifacts,
data: artifacts,
} = useQuery<LinkedArtifact[], Error>(
['execution_output_artifact', { id: executionId, state: executionState }],
() => getOutputLinkedArtifactsInExecution(execution),
{ enabled: executionCompleted, staleTime: Infinity },
);
// artifactTypes allows us to map from artifactIds to artifactTypeNames,
// so we can identify metrics artifact provided by system.
const {
isLoading: isLoadingArtifactTypes,
isSuccess: isSuccessArtifactTypes,
error: errorArtifactTypes,
data: artifactTypes,
} = useQuery<ArtifactType[], Error>(
['artifact_types', { id: executionId, state: executionState }],
() => getArtifactTypes(),
{
enabled: executionCompleted,
staleTime: Infinity,
},
);
let executionStateUnknown = executionState === Execution.State.UNKNOWN;
// This react element produces banner message if query to MLMD is pending or has error.
// Once query is completed, it shows actual content of metrics visualization in MetricsSwitcher.
return (
<ErrorBoundary>
<div className={commonCss.page}>
<div className={padding(20)}>
<ExecutionTitle execution={execution} />
{executionStateUnknown && <Banner message='Task is in unknown state.' mode='info' />}
{!executionStateUnknown && !executionCompleted && (
<Banner message='Task has not completed.' mode='info' />
)}
{(isLoadingArtifactTypes || isLoadingArtifacts) && (
<Banner message='Metrics is loading.' mode='info' />
)}
{errorArtifacts && (
<Banner
message='Error in retrieving metrics information.'
mode='error'
additionalInfo={errorArtifacts.message}
/>
)}
{!errorArtifacts && errorArtifactTypes && (
<Banner
message='Error in retrieving artifact types information.'
mode='error'
additionalInfo={errorArtifactTypes.message}
/>
)}
{isSuccessArtifacts && isSuccessArtifactTypes && artifacts && artifactTypes && (
<MetricsVisualizations
linkedArtifacts={artifacts}
artifactTypes={artifactTypes}
execution={execution}
namespace={namespace}
></MetricsVisualizations>
)}
</div>
</div>
</ErrorBoundary>
);
}