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from caffe2.python import core, workspace
from caffe2.python.core import CreatePythonOperator
import caffe2.python.hypothesis_test_util as hu
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
import unittest
class PythonOpTest(hu.HypothesisTestCase):
@given(x=hu.tensor(),
n=st.integers(min_value=1, max_value=20),
w=st.integers(min_value=1, max_value=20))
@settings(deadline=10000)
def test_simple_python_op(self, x, n, w):
def g(input_, output):
output[...] = input_
def f(inputs, outputs):
outputs[0].reshape(inputs[0].shape)
g(inputs[0].data, outputs[0].data)
ops = [CreatePythonOperator(f, ["x"], [str(i)]) for i in range(n)]
net = core.Net("net")
net.Proto().op.extend(ops)
net.Proto().type = "dag"
net.Proto().num_workers = w
iters = 100
plan = core.Plan("plan")
plan.AddStep(core.ExecutionStep("test-step", net, iters))
workspace.FeedBlob("x", x)
workspace.RunPlan(plan.Proto().SerializeToString())
for i in range(n):
y = workspace.FetchBlob(str(i))
np.testing.assert_almost_equal(x, y)
if __name__ == "__main__":
import unittest
unittest.main()
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