mirror of
https://github.com/saymrwulf/pytorch.git
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46 lines
1.5 KiB
Python
46 lines
1.5 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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from caffe2.python import core, workspace
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from caffe2.python.core import CreatePythonOperator
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import caffe2.python.hypothesis_test_util as hu
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from hypothesis import given
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import hypothesis.strategies as st
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import numpy as np
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import unittest
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try:
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import numba
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HAS_NUMBA = True
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except ImportError:
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HAS_NUMBA = False
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class PythonOpTest(hu.HypothesisTestCase):
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@unittest.skipIf(not HAS_NUMBA, "")
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@given(x=hu.tensor(),
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n=st.integers(min_value=1, max_value=20),
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w=st.integers(min_value=1, max_value=20))
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def test_multithreaded_evaluation_numba_nogil(self, x, n, w):
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@numba.jit(nopython=True, nogil=True)
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def g(input_, output):
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output[...] = input_
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def f(inputs, outputs):
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outputs[0].reshape(inputs[0].shape)
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g(inputs[0].data, outputs[0].data)
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ops = [CreatePythonOperator(f, ["x"], [str(i)]) for i in range(n)]
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net = core.Net("net")
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net.Proto().op.extend(ops)
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net.Proto().type = "dag"
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net.Proto().num_workers = w
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iters = 100
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plan = core.Plan("plan")
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plan.AddStep(core.ExecutionStep("test-step", net, iters))
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workspace.FeedBlob("x", x)
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workspace.RunPlan(plan.Proto().SerializeToString())
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for i in range(n):
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y = workspace.FetchBlob(str(i))
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np.testing.assert_almost_equal(x, y)
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