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import numpy as np
import hypothesis.strategies as st
import unittest
import caffe2.python.hypothesis_test_util as hu
from caffe2.python import core, workspace
from hypothesis import given
import caffe2.python.ideep_test_util as mu
@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class TestWeightedSumOp(hu.HypothesisTestCase):
@given(n=st.integers(5, 8), m=st.integers(1, 1),
d=st.integers(2, 4), grad_on_w=st.booleans(),
**mu.gcs_ideep_only)
def test_weighted_sum(self, n, m, d, grad_on_w, gc, dc):
input_names = []
input_vars = []
for i in range(m):
X_name = 'X' + str(i)
w_name = 'w' + str(i)
input_names.extend([X_name, w_name])
var = np.random.rand(n, d).astype(np.float32)
vars()[X_name] = var
input_vars.append(var)
var = np.random.rand(1).astype(np.float32)
vars()[w_name] = var
input_vars.append(var)
def weighted_sum_op_ref(*args):
res = np.zeros((n, d))
for i in range(m):
res = res + args[2 * i + 1] * args[2 * i]
return (res, )
op = core.CreateOperator(
"WeightedSum",
input_names,
['Y'],
grad_on_w=grad_on_w,
)
self.assertReferenceChecks(
device_option=gc,
op=op,
inputs=input_vars,
reference=weighted_sum_op_ref,
)
if __name__ == "__main__":
unittest.main()
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