def test_reader_with_limit(self):
ws = workspace.C.Workspace()
session = LocalSession(ws)
""" 1. feed full dataset """
src_init = core.Net('src_init')
src_values = Struct(('label', np.array(range(100))))
src_blobs = NewRecord(src_init, src_values)
src_ds = Dataset(src_blobs)
FeedRecord(src_blobs, src_values, ws)
ws.run(src_init)
""" 2. Read with limit smaller than size of dataset """
dst_init = core.Net('dst_init')
dst_ds = Dataset(src_values.clone_schema())
dst_ds.init_empty(dst_init)
ws.run(dst_init)
with TaskGroup() as tg:
reader = ReaderWithLimit(src_ds.reader(), num_iter=10)
pipe(reader, dst_ds.writer(), num_threads=8)
session.run(tg)
self.assertFalse(ws.blobs[str(reader.data_finished())].fetch())
self.assertEquals(
sorted(ws.blobs[str(dst_ds.content().label())].fetch()), range(10))
""" 3. Read with limit larger than size of dataset """
ws.run(dst_init)
with TaskGroup() as tg:
reader = ReaderWithLimit(src_ds.reader(), num_iter=110)
pipe(reader, dst_ds.writer(), num_threads=8)
session.run(tg)
self.assertEquals(
sorted(ws.blobs[str(dst_ds.content().label())].fetch()),
range(100))
self.assertTrue(ws.blobs[str(reader.data_finished())].fetch())
def test_reader_with_limit(self):
ws = workspace.C.Workspace()
session = LocalSession(ws)
""" 1. feed full dataset """
src_init = core.Net('src_init')
src_values = Struct(('label', np.array(range(100))))
src_blobs = NewRecord(src_init, src_values)
src_ds = Dataset(src_blobs)
FeedRecord(src_blobs, src_values, ws)
ws.run(src_init)
""" 2. Read with limit smaller than size of dataset """
dst_init = core.Net('dst_init')
dst_ds = Dataset(src_values.clone_schema())
dst_ds.init_empty(dst_init)
ws.run(dst_init)
with TaskGroup() as tg:
reader = ReaderWithLimit(src_ds.reader(), num_iter=10)
pipe(reader, dst_ds.writer(), num_threads=8)
session.run(tg)
self.assertFalse(ws.blobs[str(reader.data_finished())].fetch())
self.assertEquals(
sorted(ws.blobs[str(dst_ds.content().label())].fetch()), range(10))
""" 3. Read with limit larger than size of dataset """
ws.run(dst_init)
with TaskGroup() as tg:
reader = ReaderWithLimit(src_ds.reader(), num_iter=110)
pipe(reader, dst_ds.writer(), num_threads=8)
session.run(tg)
self.assertEquals(
sorted(ws.blobs[str(dst_ds.content().label())].fetch()), range(100))
self.assertTrue(ws.blobs[str(reader.data_finished())].fetch())
def test_dequeue_many(self):
init_net = core.Net('init')
N = 17
NUM_DEQUEUE_RECORDS = 3
src_values = Struct(
('uid', np.array(range(N))),
('value', 0.1 * np.array(range(N))))
expected_dst = Struct(
('uid', 2 * np.array(range(N))),
('value', np.array(N * [0.0])))
with core.NameScope('init'):
src_blobs = NewRecord(init_net, src_values)
dst_blobs = InitEmptyRecord(init_net, src_values.clone_schema())
counter = init_net.Const(0)
ONE = init_net.Const(1)
def proc1(rec):
with core.NameScope('proc1'):
out = NewRecord(ops, rec)
ops.Add([rec.uid(), rec.uid()], [out.uid()])
out.value.set(blob=rec.value(), unsafe=True)
return out
def proc2(rec):
with core.NameScope('proc2'):
out = NewRecord(ops, rec)
out.uid.set(blob=rec.uid(), unsafe=True)
ops.Sub([rec.value(), rec.value()], [out.value()])
ops.Add([counter, ONE], [counter])
return out
src_ds = Dataset(src_blobs)
dst_ds = Dataset(dst_blobs)
with TaskGroup() as tg:
out1 = pipe(
src_ds.reader(),
output=Queue(
capacity=11, num_dequeue_records=NUM_DEQUEUE_RECORDS),
processor=proc1)
out2 = pipe(out1, processor=proc2)
pipe(out2, dst_ds.writer())
ws = workspace.C.Workspace()
FeedRecord(src_blobs, src_values, ws)
session = LocalSession(ws)
session.run(init_net)
session.run(tg)
output = FetchRecord(dst_blobs, ws=ws)
num_dequeues = ws.blobs[str(counter)].fetch()
self.assertEquals(
num_dequeues, int(math.ceil(float(N) / NUM_DEQUEUE_RECORDS)))
for a, b in zip(output.field_blobs(), expected_dst.field_blobs()):
np.testing.assert_array_equal(a, b)
def test_dequeue_many(self):
init_net = core.Net('init')
N = 17
NUM_DEQUEUE_RECORDS = 3
src_values = Struct(
('uid', np.array(range(N))),
('value', 0.1 * np.array(range(N))))
expected_dst = Struct(
('uid', 2 * np.array(range(N))),
('value', np.array(N * [0.0])))
with core.NameScope('init'):
src_blobs = NewRecord(init_net, src_values)
dst_blobs = InitEmptyRecord(init_net, src_values.clone_schema())
counter = init_net.Const(0)
ONE = init_net.Const(1)
def proc1(rec):
with core.NameScope('proc1'):
out = NewRecord(ops, rec)
ops.Add([rec.uid(), rec.uid()], [out.uid()])
out.value.set(blob=rec.value(), unsafe=True)
return out
def proc2(rec):
with core.NameScope('proc2'):
out = NewRecord(ops, rec)
out.uid.set(blob=rec.uid(), unsafe=True)
ops.Sub([rec.value(), rec.value()], [out.value()])
ops.Add([counter, ONE], [counter])
return out
src_ds = Dataset(src_blobs)
dst_ds = Dataset(dst_blobs)
with TaskGroup() as tg:
out1 = pipe(
src_ds.reader(),
output=Queue(
capacity=11, num_dequeue_records=NUM_DEQUEUE_RECORDS),
processor=proc1)
out2 = pipe(out1, processor=proc2)
pipe(out2, dst_ds.writer())
ws = workspace.C.Workspace()
FeedRecord(src_blobs, src_values, ws)
session = LocalSession(ws)
session.run(init_net)
session.run(tg)
output = FetchRecord(dst_blobs, ws=ws)
num_dequeues = ws.blobs[str(counter)].fetch()
self.assertEquals(
num_dequeues, int(math.ceil(float(N) / NUM_DEQUEUE_RECORDS)))
for a, b in zip(output.field_blobs(), expected_dst.field_blobs()):
np.testing.assert_array_equal(a, b)
def test_local_session(self):
init_net = core.Net('init')
src_values = Struct(
('uid', np.array([1, 2, 6])),
('value', np.array([1.4, 1.6, 1.7])))
expected_dst = Struct(
('uid', np.array([2, 4, 12])),
('value', np.array([0.0, 0.0, 0.0])))
with core.NameScope('init'):
src_blobs = NewRecord(init_net, src_values)
dst_blobs = InitEmptyRecord(init_net, src_values.clone_schema())
def proc1(rec):
net = core.Net('proc1')
with core.NameScope('proc1'):
out = NewRecord(net, rec)
net.Add([rec.uid(), rec.uid()], [out.uid()])
out.value.set(blob=rec.value(), unsafe=True)
return [net], out
def proc2(rec):
net = core.Net('proc2')
with core.NameScope('proc2'):
out = NewRecord(net, rec)
out.uid.set(blob=rec.uid(), unsafe=True)
net.Sub([rec.value(), rec.value()], [out.value()])
return [net], out
src_ds = Dataset(src_blobs)
dst_ds = Dataset(dst_blobs)
with TaskGroup() as tg:
out1 = pipe(src_ds.reader(), processor=proc1)
out2 = pipe(out1, processor=proc2)
pipe(out2, dst_ds.writer())
ws = workspace.C.Workspace()
FeedRecord(src_blobs, src_values, ws)
session = LocalSession(ws)
session.run(init_net)
session.run(tg)
output = FetchRecord(dst_blobs, ws=ws)
for a, b in zip(output.field_blobs(), expected_dst.field_blobs()):
np.testing.assert_array_equal(a, b)
def test_local_session(self):
init_net = core.Net('init')
src_values = Struct(
('uid', np.array([1, 2, 6])),
('value', np.array([1.4, 1.6, 1.7])))
expected_dst = Struct(
('uid', np.array([2, 4, 12])),
('value', np.array([0.0, 0.0, 0.0])))
with core.NameScope('init'):
src_blobs = NewRecord(init_net, src_values)
dst_blobs = InitEmptyRecord(init_net, src_values.clone_schema())
def proc1(rec):
net = core.Net('proc1')
with core.NameScope('proc1'):
out = NewRecord(net, rec)
net.Add([rec.uid(), rec.uid()], [out.uid()])
out.value.set(blob=rec.value(), unsafe=True)
return [net], out
def proc2(rec):
net = core.Net('proc2')
with core.NameScope('proc2'):
out = NewRecord(net, rec)
out.uid.set(blob=rec.uid(), unsafe=True)
net.Sub([rec.value(), rec.value()], [out.value()])
return [net], out
src_ds = Dataset(src_blobs)
dst_ds = Dataset(dst_blobs)
with TaskGroup() as tg:
out1 = pipe(src_ds.reader(), processor=proc1)
out2 = pipe(out1, processor=proc2)
pipe(out2, dst_ds.writer())
ws = workspace.C.Workspace()
FeedRecord(src_blobs, src_values, ws)
session = LocalSession(ws)
session.run(init_net)
session.run(tg)
output = FetchRecord(dst_blobs, ws=ws)
for a, b in zip(output.field_blobs(), expected_dst.field_blobs()):
np.testing.assert_array_equal(a, b)
