def test_dask_local_hyper():
task = NewRun().with_hyper_params({'p1': [5, 2, 3]}, 'max.accuracy')
spec = tag_test(task, 'test_dask_local_hyper')
run = new_function(command='dask://').run(spec, handler=my_func)
verify_state(run)
assert len(run.status.iterations) == 3 + 1, 'hyper parameters test failed'
pprint(run.to_dict())
tag_test, verify_state)
from mlrun import new_function, NewRun, RunObject, get_run_db
from mlrun.utils import run_keys, update_in
def my_func(context, p1=1, p2='a-string'):
print(f'Run: {context.name} (uid={context.uid})')
print(f'Params: p1={p1}, p2={p2}\n')
print('file\n{}\n'.format(context.get_input('infile.txt').get()))
context.log_result('accuracy', p1 * 2)
context.log_metric('loss', 7)
context.log_artifact('chart', body='abc')
base_spec = NewRun(params={'p1': 8}, out_path=out_path)
base_spec.spec.inputs = {'infile.txt': 'infile.txt'}
s3_spec = base_spec.copy().with_secrets('file', 'secrets.txt')
s3_spec.spec.inputs = {'infile.txt': 's3://yarons-tests/infile.txt'}
def test_noparams():
result = new_function().run(handler=my_func)
assert result.output('accuracy') == 2, 'failed to run'
assert result.status.artifacts[0].get('key') == 'chart', 'failed to run'
def test_with_params():
spec = tag_test(base_spec, 'test_with_params')
import json
from os import listdir
from tempfile import mktemp
import pytest
import yaml
from conftest import has_secrets, out_path, rundb_path
from mlrun.artifacts import ChartArtifact, TableArtifact
from mlrun import NewRun, new_function
from mlrun.utils import run_keys
run_spec = NewRun(params={
'p1': 5
},
out_path=out_path,
outputs=['model.txt',
'chart.html']).set_label('tests', 'kfp')
def my_job(context, p1=1, p2='a-string'):
# access input metadata, values, files, and secrets (passwords)
print(f'Run: {context.name} (uid={context.uid})')
print(f'Params: p1={p1}, p2={p2}')
print('accesskey = {}'.format(context.get_secret('ACCESS_KEY')))
print('file\n{}\n'.format(context.get_input('infile.txt').get()))
# RUN some useful code e.g. ML training, data prep, etc.
# log scalar result values (job result metrics)
import json
from copy import deepcopy
from os import listdir
from tempfile import mktemp
import pytest
import yaml
from conftest import has_secrets, out_path, rundb_path
from mlrun.artifacts import ChartArtifact, TableArtifact
from mlrun import NewRun, run_start
from mlrun.utils import run_keys
run_spec = NewRun(params={'p1': 5}, out_path=out_path).set_label('tests', 'kfp')
def my_job(context, p1=1, p2='a-string'):
# access input metadata, values, files, and secrets (passwords)
print(f'Run: {context.name} (uid={context.uid})')
print(f'Params: p1={p1}, p2={p2}')
print('accesskey = {}'.format(context.get_secret('ACCESS_KEY')))
print('file\n{}\n'.format(context.get_object('infile.txt').get()))
# RUN some useful code e.g. ML training, data prep, etc.
# log scalar result values (job result metrics)
context.log_result('accuracy', p1 * 2)
context.log_result('loss', p1 * 3)
time.sleep(1)
# log scalar values (KFP metrics)
ctx.log_result('accuracy', p1 * 2)
ctx.log_result('latency', p1 * 3)
# log various types of artifacts (and set UI viewers)
ctx.log_artifact('test.txt', body=b'abc is 123')
ctx.log_artifact('test.html', body=b'<b> Some HTML <b>', viewer='web-app')
context.logger.info('run complete!')
return ctx.to_json()
base_spec = NewRun(params={'p1': 8}, out_path=out_path)
base_spec.spec.inputs = {'infile.txt': 'infile.txt'}
def verify_state(result: RunObject):
state = result.status.state
assert state == 'completed', 'wrong state ({}) {}'.format(
state, result.status.error)
def test_simple_function():
#Thread(target=create_function, args=(myfunction, 4444)).start()
_thread.start_new_thread(create_function, (myfunction, 4444))
time.sleep(2)
spec = tag_test(base_spec, 'simple_function')
def test_dask_local():
spec = tag_test(NewRun(params={'p1': 3, 'p2': 'vv'}), 'test_dask_local')
run = new_function(command='dask://',
rundb=rundb_path).run(spec, handler=my_func)
verify_state(run)
pprint(run.to_dict())