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calculation-pipeline.yaml
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calculation-pipeline.yaml
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# Copyright 2021 The MLX Contributors
#
# SPDX-License-Identifier: Apache-2.0
apiVersion: tekton.dev/v1beta1
kind: PipelineRun
metadata:
name: calculation-pipeline
annotations:
tekton.dev/output_artifacts: '{"add": [{"key": "artifacts/$PIPELINERUN/add/Output.tgz",
"name": "add-Output", "path": "/tmp/outputs/Output/data"}], "add-2": [{"key":
"artifacts/$PIPELINERUN/add-2/Output.tgz", "name": "add-2-Output", "path": "/tmp/outputs/Output/data"}],
"my-divmod": [{"key": "artifacts/$PIPELINERUN/my-divmod/mlpipeline-ui-metadata.tgz",
"name": "mlpipeline-ui-metadata", "path": "/tmp/outputs/mlpipeline_ui_metadata/data"},
{"key": "artifacts/$PIPELINERUN/my-divmod/mlpipeline-metrics.tgz", "name": "mlpipeline-metrics",
"path": "/tmp/outputs/mlpipeline_metrics/data"}, {"key": "artifacts/$PIPELINERUN/my-divmod/quotient.tgz",
"name": "my-divmod-quotient", "path": "/tmp/outputs/quotient/data"}, {"key":
"artifacts/$PIPELINERUN/my-divmod/remainder.tgz", "name": "my-divmod-remainder",
"path": "/tmp/outputs/remainder/data"}]}'
tekton.dev/input_artifacts: '{"add-2": [{"name": "my-divmod-quotient", "parent_task":
"my-divmod"}], "my-divmod": [{"name": "add-Output", "parent_task": "add"}]}'
tekton.dev/artifact_bucket: mlpipeline
tekton.dev/artifact_endpoint: minio-service.kubeflow:9000
tekton.dev/artifact_endpoint_scheme: http://
tekton.dev/artifact_items: '{"add": [["Output", "$(results.output.path)"]], "add-2":
[["Output", "$(results.output.path)"]], "my-divmod": [["mlpipeline-ui-metadata",
"/tmp/outputs/mlpipeline_ui_metadata/data"], ["mlpipeline-metrics", "/tmp/outputs/mlpipeline_metrics/data"],
["quotient", "$(results.quotient.path)"], ["remainder", "$(results.remainder.path)"]]}'
sidecar.istio.io/inject: "false"
pipelines.kubeflow.org/big_data_passing_format: $(workspaces.$TASK_NAME.path)/artifacts/$ORIG_PR_NAME/$TASKRUN_NAME/$TASK_PARAM_NAME
pipelines.kubeflow.org/pipeline_spec: '{"description": "A toy pipeline that performs
arithmetic calculations.", "inputs": [{"default": "7.0", "name": "a", "optional":
true, "type": "Float"}, {"default": "8.0", "name": "b", "optional": true, "type":
"Float"}, {"default": "17.0", "name": "c", "optional": true, "type": "Float"}],
"name": "Calculation Pipeline"}'
spec:
params:
- name: a
value: '7.0'
- name: b
value: '8.0'
- name: c
value: '17.0'
pipelineSpec:
params:
- name: a
default: '7.0'
- name: b
default: '8.0'
- name: c
default: '17.0'
tasks:
- name: add
params:
- name: a
value: $(params.a)
taskSpec:
steps:
- name: main
args:
- --a
- $(inputs.params.a)
- --b
- '4'
- '----output-paths'
- $(results.output.path)
command:
- sh
- -ec
- |
program_path=$(mktemp)
printf "%s" "$0" > "$program_path"
python3 -u "$program_path" "$@"
- |
def add(a, b):
"""Calculates sum of two arguments"""
return a + b
def _serialize_float(float_value: float) -> str:
if isinstance(float_value, str):
return float_value
if not isinstance(float_value, (float, int)):
raise TypeError('Value "{}" has type "{}" instead of float.'.format(str(float_value), str(type(float_value))))
return str(float_value)
import argparse
_parser = argparse.ArgumentParser(prog='Add', description='Calculates sum of two arguments')
_parser.add_argument("--a", dest="a", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("--b", dest="b", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=1)
_parsed_args = vars(_parser.parse_args())
_output_files = _parsed_args.pop("_output_paths", [])
_outputs = add(**_parsed_args)
_outputs = [_outputs]
_output_serializers = [
_serialize_float,
]
import os
for idx, output_file in enumerate(_output_files):
try:
os.makedirs(os.path.dirname(output_file))
except OSError:
pass
with open(output_file, 'w') as f:
f.write(_output_serializers[idx](_outputs[idx]))
image: python:3.7
params:
- name: a
results:
- name: output
description: /tmp/outputs/Output/data
metadata:
labels:
pipelines.kubeflow.org/pipelinename: ''
pipelines.kubeflow.org/generation: ''
pipelines.kubeflow.org/cache_enabled: "true"
annotations:
pipelines.kubeflow.org/component_spec_digest: '{"name": "Add", "outputs":
[{"name": "Output", "type": "Float"}], "version": "Add@sha256=6747051c897943c73ef931bf243a7a5ea738f7981a2208ab6daf11bcdf6744c4"}'
tekton.dev/template: ''
timeout: 525600m
- name: my-divmod
params:
- name: add-Output
value: $(tasks.add.results.output)
- name: b
value: $(params.b)
taskSpec:
steps:
- name: main
args:
- --dividend
- $(inputs.params.add-Output)
- --divisor
- $(inputs.params.b)
- '----output-paths'
- $(results.quotient.path)
- $(results.remainder.path)
- /tmp/outputs/mlpipeline_ui_metadata/data
- /tmp/outputs/mlpipeline_metrics/data
command:
- sh
- -ec
- |
program_path=$(mktemp)
printf "%s" "$0" > "$program_path"
python3 -u "$program_path" "$@"
- |
def my_divmod(dividend, divisor):
"""Divides two numbers and calculate the quotient and remainder"""
#Pip installs inside a component function.
#NOTE: installs should be placed right at the beginning to avoid upgrading a package
# after it has already been imported and cached by python
import sys, subprocess;
subprocess.run([sys.executable, '-m', 'pip', 'install', 'tensorflow==1.8.0'])
#Imports inside a component function:
import numpy as np
#This function demonstrates how to use nested functions inside a component function:
def divmod_helper(dividend, divisor):
return np.divmod(dividend, divisor)
(quotient, remainder) = divmod_helper(dividend, divisor)
from tensorflow.python.lib.io import file_io
import json
# Exports a sample tensorboard:
metadata = {
'outputs' : [{
'type': 'tensorboard',
'source': 'gs://ml-pipeline-dataset/tensorboard-train',
}]
}
# Exports two sample metrics:
metrics = {
'metrics': [{
'name': 'quotient',
'numberValue': float(quotient),
},{
'name': 'remainder',
'numberValue': float(remainder),
}]}
from collections import namedtuple
divmod_output = namedtuple('MyDivmodOutput', ['quotient', 'remainder', 'mlpipeline_ui_metadata', 'mlpipeline_metrics'])
return divmod_output(quotient, remainder, json.dumps(metadata), json.dumps(metrics))
def _serialize_float(float_value: float) -> str:
if isinstance(float_value, str):
return float_value
if not isinstance(float_value, (float, int)):
raise TypeError('Value "{}" has type "{}" instead of float.'.format(str(float_value), str(type(float_value))))
return str(float_value)
import argparse
_parser = argparse.ArgumentParser(prog='My divmod', description='Divides two numbers and calculate the quotient and remainder')
_parser.add_argument("--dividend", dest="dividend", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("--divisor", dest="divisor", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=4)
_parsed_args = vars(_parser.parse_args())
_output_files = _parsed_args.pop("_output_paths", [])
_outputs = my_divmod(**_parsed_args)
_output_serializers = [
_serialize_float,
_serialize_float,
str,
str,
]
import os
for idx, output_file in enumerate(_output_files):
try:
os.makedirs(os.path.dirname(output_file))
except OSError:
pass
with open(output_file, 'w') as f:
f.write(_output_serializers[idx](_outputs[idx]))
image: tensorflow/tensorflow:1.11.0-py3
params:
- name: add-Output
- name: b
results:
- name: quotient
description: /tmp/outputs/quotient/data
- name: remainder
description: /tmp/outputs/remainder/data
stepTemplate:
volumeMounts:
- name: mlpipeline-ui-metadata
mountPath: /tmp/outputs/mlpipeline_ui_metadata
- name: mlpipeline-metrics
mountPath: /tmp/outputs/mlpipeline_metrics
volumes:
- name: mlpipeline-ui-metadata
emptyDir: {}
- name: mlpipeline-metrics
emptyDir: {}
metadata:
labels:
pipelines.kubeflow.org/pipelinename: ''
pipelines.kubeflow.org/generation: ''
pipelines.kubeflow.org/cache_enabled: "true"
annotations:
pipelines.kubeflow.org/component_spec_digest: '{"name": "My divmod", "outputs":
[{"name": "quotient", "type": "Float"}, {"name": "remainder", "type":
"Float"}, {"name": "mlpipeline_ui_metadata", "type": "UI_metadata"},
{"name": "mlpipeline_metrics", "type": "Metrics"}], "version": "My divmod@sha256=4c899614d703dce761021d181331942f218ad9dceb0c389dff06e39841d9b067"}'
tekton.dev/template: ''
timeout: 525600m
- name: add-2
params:
- name: c
value: $(params.c)
- name: my-divmod-quotient
value: $(tasks.my-divmod.results.quotient)
taskSpec:
steps:
- name: main
args:
- --a
- $(inputs.params.my-divmod-quotient)
- --b
- $(inputs.params.c)
- '----output-paths'
- $(results.output.path)
command:
- sh
- -ec
- |
program_path=$(mktemp)
printf "%s" "$0" > "$program_path"
python3 -u "$program_path" "$@"
- |
def add(a, b):
"""Calculates sum of two arguments"""
return a + b
def _serialize_float(float_value: float) -> str:
if isinstance(float_value, str):
return float_value
if not isinstance(float_value, (float, int)):
raise TypeError('Value "{}" has type "{}" instead of float.'.format(str(float_value), str(type(float_value))))
return str(float_value)
import argparse
_parser = argparse.ArgumentParser(prog='Add', description='Calculates sum of two arguments')
_parser.add_argument("--a", dest="a", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("--b", dest="b", type=float, required=True, default=argparse.SUPPRESS)
_parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=1)
_parsed_args = vars(_parser.parse_args())
_output_files = _parsed_args.pop("_output_paths", [])
_outputs = add(**_parsed_args)
_outputs = [_outputs]
_output_serializers = [
_serialize_float,
]
import os
for idx, output_file in enumerate(_output_files):
try:
os.makedirs(os.path.dirname(output_file))
except OSError:
pass
with open(output_file, 'w') as f:
f.write(_output_serializers[idx](_outputs[idx]))
image: python:3.7
params:
- name: c
- name: my-divmod-quotient
results:
- name: output
description: /tmp/outputs/Output/data
metadata:
labels:
pipelines.kubeflow.org/pipelinename: ''
pipelines.kubeflow.org/generation: ''
pipelines.kubeflow.org/cache_enabled: "true"
annotations:
pipelines.kubeflow.org/component_spec_digest: '{"name": "Add", "outputs":
[{"name": "Output", "type": "Float"}], "version": "Add@sha256=6747051c897943c73ef931bf243a7a5ea738f7981a2208ab6daf11bcdf6744c4"}'
tekton.dev/template: ''
timeout: 525600m
timeout: 525600m