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jobs.py
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jobs.py
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import time
import logging
import asyncio
import tornado.web
from libertem.analysis import (
DiskMaskAnalysis, RingMaskAnalysis, PointMaskAnalysis,
FEMAnalysis, COMAnalysis, SumAnalysis, PickFrameAnalysis,
PickFFTFrameAnalysis, SumfftAnalysis,
RadialFourierAnalysis, ApplyFFTMask
)
from .base import CORSMixin, run_blocking, log_message, result_images
from .messages import Message
from libertem.executor.base import JobCancelledError
from libertem.udf.base import UDFRunner
log = logging.getLogger(__name__)
class JobDetailHandler(CORSMixin, tornado.web.RequestHandler):
def initialize(self, data, event_registry):
self.data = data
self.event_registry = event_registry
def get_analysis_by_type(self, type_):
analysis_by_type = {
"APPLY_DISK_MASK": DiskMaskAnalysis,
"APPLY_RING_MASK": RingMaskAnalysis,
"FFTSUM_FRAMES": SumfftAnalysis,
"APPLY_POINT_SELECTOR": PointMaskAnalysis,
"CENTER_OF_MASS": COMAnalysis,
"RADIAL_FOURIER": RadialFourierAnalysis,
"SUM_FRAMES": SumAnalysis,
"PICK_FRAME": PickFrameAnalysis,
"FEM": FEMAnalysis,
"PICK_FFT_FRAME": PickFFTFrameAnalysis,
"APPLY_FFT_MASK": ApplyFFTMask,
}
return analysis_by_type[type_]
async def put(self, uuid):
request_data = tornado.escape.json_decode(self.request.body)
params = request_data['job']
ds = self.data.get_dataset(params['dataset'])
analysis = self.get_analysis_by_type(params['analysis']['type'])(
dataset=ds,
parameters=params['analysis']['parameters']
)
try:
if analysis.TYPE == 'UDF':
return await self.run_udf(uuid, ds, analysis)
else:
return await self.run_job(uuid, ds, analysis)
except JobCancelledError:
msg = Message(self.data).cancel_done(uuid)
log_message(msg)
await self.event_registry.broadcast_event(msg)
return
except Exception as e:
log.exception("error running job, params=%r", params)
msg = Message(self.data).job_error(uuid, "error running job: %s" % str(e))
self.event_registry.broadcast_event(msg)
await self.data.remove_job(uuid)
async def delete(self, uuid):
result = await self.data.remove_job(uuid)
if result:
msg = Message(self.data).cancel_job(uuid)
log_message(msg)
self.event_registry.broadcast_event(msg)
self.write(msg)
else:
log.warning("tried to remove unknown job %s", uuid)
msg = Message(self.data).cancel_failed(uuid)
log_message(msg)
self.event_registry.broadcast_event(msg)
self.write(msg)
async def run_udf(self, uuid, ds, analysis):
udf = analysis.get_udf()
roi = analysis.get_roi()
# FIXME: register_job for UDFs?
self.data.register_job(uuid=uuid, job=udf, dataset=ds)
# FIXME: code duplication
executor = self.data.get_executor()
msg = Message(self.data).start_job(
job_id=uuid,
)
log_message(msg)
self.write(msg)
self.finish()
self.event_registry.broadcast_event(msg)
t = time.time()
post_t = time.time()
window = 0.3
result_iter = UDFRunner(udf).run_for_dataset_async(
ds, executor, roi=roi, cancel_id=uuid
)
async for udf_results in result_iter:
window = min(max(window, 2*(t - post_t)), 5)
if time.time() - t < window:
continue
results = await run_blocking(
analysis.get_udf_results,
udf_results=udf_results,
)
post_t = time.time()
await self.send_results(results, uuid)
# The broadcast might have taken quite some time due to
# backpressure from the network
t = time.time()
if self.data.job_is_cancelled(uuid):
raise JobCancelledError()
results = await run_blocking(
analysis.get_udf_results,
udf_results=udf_results,
)
await self.send_results(results, uuid, finished=True)
async def run_job(self, uuid, ds, analysis):
job = analysis.get_job()
full_result = job.get_result_buffer()
self.data.register_job(uuid=uuid, job=job, dataset=job.dataset)
executor = self.data.get_executor()
msg = Message(self.data).start_job(
job_id=uuid,
)
log_message(msg)
self.write(msg)
self.finish()
self.event_registry.broadcast_event(msg)
t = time.time()
post_t = time.time()
window = 0.3
async for result in executor.run_job(job, cancel_id=uuid):
for tile in result:
tile.reduce_into_result(full_result)
window = min(max(window, 2*(t - post_t)), 5)
if time.time() - t < window:
continue
post_t = time.time()
results = await run_blocking(
analysis.get_results,
job_results=full_result,
)
await self.send_results(results, uuid)
# The broadcast might have taken quite some time due to
# backpressure from the network
t = time.time()
if self.data.job_is_cancelled(uuid):
raise JobCancelledError()
results = await run_blocking(
analysis.get_results,
job_results=full_result,
)
await self.send_results(results, uuid, finished=True)
async def send_results(self, results, uuid, finished=False):
if self.data.job_is_cancelled(uuid):
raise JobCancelledError()
images = await result_images(results)
if self.data.job_is_cancelled(uuid):
raise JobCancelledError()
if finished:
msg = Message(self.data).finish_job(
job_id=uuid,
num_images=len(results),
image_descriptions=[
{"title": result.title, "desc": result.desc}
for result in results
],
)
else:
msg = Message(self.data).task_result(
job_id=uuid,
num_images=len(results),
image_descriptions=[
{"title": result.title, "desc": result.desc}
for result in results
],
)
log_message(msg)
# NOTE: make sure the following broadcast_event messages are sent atomically!
# (that is: keep the code below synchronous, and only send the messages
# once the images have finished encoding, and then send all at once)
futures = []
futures.append(
self.event_registry.broadcast_event(msg)
)
for image in images:
raw_bytes = image.read()
futures.append(
self.event_registry.broadcast_event(raw_bytes, binary=True)
)
await asyncio.gather(*futures)