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https://github.com/zebrajr/pytorch.git
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d072701547
Summary: data_workers.py provides a really nice, easy way to run background threads for data input. Unfortunately, it's restrictive, the output of the fetcher function has to be a numpy array. I pulled out that core nice thread management into parallel_workers, and updated the classes data_workers to extend those classes. The main change was refactoring out most of the queue handling logic into QueueManager. This way parallel_workers can be used to manage background threads without having to use the queue for output. Reviewed By: akyrola Differential Revision: D5538626 fbshipit-source-id: f382cc43f800ff90840582a378dc9b86ac05b613
91 lines
2.4 KiB
Python
91 lines
2.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import unittest
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from caffe2.python import workspace, core
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import caffe2.python.parallel_workers as parallel_workers
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def create_queue():
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queue = 'queue'
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workspace.RunOperatorOnce(
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core.CreateOperator(
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"CreateBlobsQueue", [], [queue], num_blobs=1, capacity=1000
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)
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)
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return queue
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def create_worker(queue, get_blob_data):
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def dummy_worker(worker_id):
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blob = 'blob_' + str(worker_id)
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workspace.FeedBlob(blob, get_blob_data(worker_id))
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workspace.RunOperatorOnce(
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core.CreateOperator(
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'SafeEnqueueBlobs', [queue, blob], [blob, 'status_blob']
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)
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)
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return dummy_worker
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def dequeue_value(queue):
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dequeue_blob = 'dequeue_blob'
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workspace.RunOperatorOnce(
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core.CreateOperator(
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"SafeDequeueBlobs", [queue], [dequeue_blob, 'status_blob']
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)
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)
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return workspace.FetchBlob(dequeue_blob)
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class ParallelWorkersTest(unittest.TestCase):
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def testParallelWorkers(self):
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workspace.ResetWorkspace()
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queue = create_queue()
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dummy_worker = create_worker(queue, lambda worker_id: str(worker_id))
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worker_coordinator = parallel_workers.init_workers(dummy_worker)
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worker_coordinator.start()
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for _ in range(10):
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value = dequeue_value(queue)
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self.assertTrue(
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value in [b'0', b'1'], 'Got unexpected value ' + str(value)
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)
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self.assertTrue(worker_coordinator.stop())
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def testParallelWorkersInitFun(self):
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workspace.ResetWorkspace()
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queue = create_queue()
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dummy_worker = create_worker(
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queue, lambda worker_id: workspace.FetchBlob('data')
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)
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workspace.FeedBlob('data', 'not initialized')
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def init_fun(worker_coordinator, global_coordinator):
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workspace.FeedBlob('data', 'initialized')
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worker_coordinator = parallel_workers.init_workers(
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dummy_worker, init_fun=init_fun
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)
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worker_coordinator.start()
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for _ in range(10):
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value = dequeue_value(queue)
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self.assertEqual(
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value, b'initialized', 'Got unexpected value ' + str(value)
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)
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self.assertTrue(worker_coordinator.stop())
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