nopaque/app/daemon/job_utils.py
2022-11-24 12:24:11 +01:00

235 lines
9.4 KiB
Python

from app import db, docker_client, hashids
from app.models import (
Job,
JobResult,
JobStatus,
TesseractOCRPipelineModel,
SpaCyNLPPipelineModel
)
from datetime import datetime
from flask import current_app
from werkzeug.utils import secure_filename
import docker
import json
import os
import shutil
def check_jobs():
jobs = Job.query.all()
for job in [x for x in jobs if x.status == JobStatus.SUBMITTED]:
_create_job_service(job)
for job in [x for x in jobs if x.status in [JobStatus.QUEUED, JobStatus.RUNNING]]:
_checkout_job_service(job)
for job in [x for x in jobs if x.status == JobStatus.CANCELING]:
_remove_job_service(job)
def _create_job_service(job):
''' # Docker service settings # '''
''' ## Service specific settings ## '''
if job.service == 'file-setup-pipeline':
mem_mb = 512
n_cores = 2
executable = 'file-setup-pipeline'
image = f'{current_app.config["NOPAQUE_DOCKER_IMAGE_PREFIX"]}file-setup-pipeline:v{job.service_version}'
elif job.service == 'tesseract-ocr-pipeline':
mem_mb = 1024
n_cores = 4
executable = 'tesseract-ocr-pipeline'
image = f'{current_app.config["NOPAQUE_DOCKER_IMAGE_PREFIX"]}tesseract-ocr-pipeline:v{job.service_version}'
elif job.service == 'transkribus-htr-pipeline':
mem_mb = 1024
n_cores = 4
executable = 'transkribus-htr-pipeline'
image = f'{current_app.config["NOPAQUE_DOCKER_IMAGE_PREFIX"]}transkribus-htr-pipeline:v{job.service_version}'
elif job.service == 'spacy-nlp-pipeline':
mem_mb = 1024
n_cores = 1
executable = 'spacy-nlp-pipeline'
image = f'{current_app.config["NOPAQUE_DOCKER_IMAGE_PREFIX"]}spacy-nlp-pipeline:v{job.service_version}'
''' ## Command ## '''
command = f'{executable} -i /input -o /output'
command += ' --log-dir /logs'
command += f' --mem-mb {mem_mb}'
command += f' --n-cores {n_cores}'
if job.service == 'spacy-nlp-pipeline':
model_id = hashids.decode(job.service_args['model'])
model = SpaCyNLPPipelineModel.query.get(model_id)
if model is None:
job.status = JobStatus.FAILED
return
command += f' -m {model.pipeline_name}'
if 'encoding_detection' in job.service_args and job.service_args['encoding_detection']:
command += ' --check-encoding'
elif job.service == 'tesseract-ocr-pipeline':
command += f' -m {job.service_args["model"]}'
if 'binarization' in job.service_args and job.service_args['binarization']:
command += ' --binarize'
if 'ocropus_nlbin_threshold' in job.service_args and job.service_args['ocropus_nlbin_threshold']:
value = job.service_args['ocropus_nlbin_threshold']
command += f' --ocropus-nlbin-threshold {value}'
elif job.service == 'transkribus-htr-pipeline':
transkribus_htr_pipeline_model_id = job.service_args['model']
command += f' -m {transkribus_htr_pipeline_model_id}'
readcoop_username = current_app.config.get('NOPAQUE_READCOOP_USERNAME')
command += f' --readcoop-username "{readcoop_username}"'
readcoop_password = current_app.config.get('NOPAQUE_READCOOP_PASSWORD')
command += f' --readcoop-password "{readcoop_password}"'
if 'binarization' in job.service_args and job.service_args['binarization']:
command += ' --binarize'
''' ## Constraints ## '''
constraints = ['node.role==worker']
''' ## Labels ## '''
labels = {
'origin': current_app.config['SERVER_NAME'],
'type': 'job',
'job_id': str(job.id)
}
''' ## Mounts ## '''
mounts = []
''' ### Input mount(s) ### '''
input_mount_target_base = '/input'
if job.service == 'file-setup-pipeline':
input_mount_target_base += f'/{secure_filename(job.title)}'
for job_input in job.inputs:
input_mount_source = job_input.path
input_mount_target = f'{input_mount_target_base}/{job_input.filename}'
input_mount = f'{input_mount_source}:{input_mount_target}:ro'
mounts.append(input_mount)
if job.service == 'tesseract-ocr-pipeline':
if isinstance(job.service_args['model'], str):
model_id = hashids.decode(job.service_args['model'])
elif isinstance(job.service_args['model'], int):
model_id = job.service_args['model']
else:
job.status = JobStatus.FAILED
return
model = TesseractOCRPipelineModel.query.get(model_id)
if model is None:
job.status = JobStatus.FAILED
return
models_mount_source = model.path
models_mount_target = f'/usr/local/share/tessdata/{model.id}.traineddata'
models_mount = f'{models_mount_source}:{models_mount_target}:ro'
mounts.append(models_mount)
elif job.service == 'spacy-nlp-pipeline':
model_id = hashids.decode(job.service_args['model'])
model = SpaCyNLPPipelineModel.query.get(model_id)
if model is None:
job.status = JobStatus.FAILED
return
models_mount_source = model.path
models_mount_target = f'/usr/local/share/spacy/models/{model.filename}'
models_mount = f'{models_mount_source}:{models_mount_target}:ro'
mounts.append(models_mount)
''' ### Output mount ### '''
output_mount_source = os.path.join(job.path, 'results')
output_mount_target = '/output'
output_mount = f'{output_mount_source}:{output_mount_target}:rw'
# Make sure that their is no data in the output directory
shutil.rmtree(output_mount_source, ignore_errors=True)
os.makedirs(output_mount_source)
mounts.append(output_mount)
''' ### Pipeline data mount ### '''
pyflow_data_mount_source = os.path.join(job.path, 'pipeline_data')
pyflow_data_mount_target = '/logs/pyflow.data'
pyflow_data_mount = f'{pyflow_data_mount_source}:{pyflow_data_mount_target}:rw'
# Make sure that their is no data in the output directory
shutil.rmtree(pyflow_data_mount_source, ignore_errors=True)
os.makedirs(pyflow_data_mount_source)
mounts.append(pyflow_data_mount)
''' ## Name ## '''
name = f'job_{job.id}'
''' ## Resources ## '''
resources = docker.types.Resources(
cpu_reservation=n_cores * (10 ** 9),
mem_reservation=mem_mb * (10 ** 6)
)
''' ## Restart policy ## '''
restart_policy = docker.types.RestartPolicy()
try:
docker_client.services.create(
image,
command=command,
constraints=constraints,
labels=labels,
mounts=mounts,
name=name,
resources=resources,
restart_policy=restart_policy,
user='0:0'
)
except docker.errors.DockerException as e:
current_app.logger.error(f'Create service "{name}" failed: {e}')
return
job.status = JobStatus.QUEUED
def _checkout_job_service(job):
service_name = f'job_{job.id}'
try:
service = docker_client.services.get(service_name)
except docker.errors.NotFound as e:
current_app.logger.error(f'Get service "{service_name}" failed: {e}')
job.status = JobStatus.FAILED
return
except docker.errors.DockerException as e:
current_app.logger.error(f'Get service "{service_name}" failed: {e}')
return
service_tasks = service.tasks()
if not service_tasks:
return
task_state = service_tasks[0].get('Status').get('State')
if job.status == JobStatus.QUEUED and task_state != 'pending':
job.status = JobStatus.RUNNING
return
elif job.status == JobStatus.RUNNING and task_state == 'complete':
job.status = JobStatus.COMPLETED
results_dir = os.path.join(job.path, 'results')
with open(os.path.join(results_dir, 'outputs.json')) as f:
outputs = json.load(f)
for output in outputs:
filename = os.path.basename(output['file'])
job_result = JobResult(
filename=filename,
job=job,
mimetype=output['mimetype']
)
if 'description' in output:
job_result.description = output['description']
db.session.add(job_result)
db.session.flush(objects=[job_result])
db.session.refresh(job_result)
os.rename(
os.path.join(results_dir, output['file']),
job_result.path
)
elif job.status == JobStatus.RUNNING and task_state == 'failed':
job.status = JobStatus.FAILED
else:
return
job.end_date = datetime.utcnow()
try:
service.remove()
except docker.errors.DockerException as e:
current_app.logger.error(f'Remove service "{service_name}" failed: {e}')
def _remove_job_service(job):
service_name = f'job_{job.id}'
try:
service = docker_client.services.get(service_name)
except docker.errors.NotFound:
job.status = JobStatus.CANCELED
return
except docker.errors.DockerException as e:
current_app.logger.error(f'Get service "{service_name}" failed: {e}')
return
try:
service.update(mounts=None)
except docker.errors.DockerException as e:
current_app.logger.error(f'Update service "{service_name}" failed: {e}')
return
try:
service.remove()
except docker.errors.DockerException as e:
current_app.logger.error(f'Remove "{service_name}" service failed: {e}')