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from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestElementwiseLinearOp(serial.SerializedTestCase):
@serial.given(n=st.integers(2, 100), d=st.integers(2, 10), **hu.gcs)
# @given(n=st.integers(2, 50), d=st.integers(2, 50), **hu.gcs_cpu_only)
def test(self, n, d, gc, dc):
X = np.random.rand(n, d).astype(np.float32)
a = np.random.rand(d).astype(np.float32)
b = np.random.rand(d).astype(np.float32)
def ref_op(X, a, b):
d = a.shape[0]
return [np.multiply(X, a.reshape(1, d)) + b.reshape(1, d)]
op = core.CreateOperator(
"ElementwiseLinear",
["X", "a", "b"],
["Y"]
)
self.assertReferenceChecks(
device_option=gc,
op=op,
inputs=[X, a, b],
reference=ref_op,
)
# Check over multiple devices
self.assertDeviceChecks(dc, op, [X, a, b], [0])
# Gradient check wrt X
self.assertGradientChecks(gc, op, [X, a, b], 0, [0])
# Gradient check wrt a
self.assertGradientChecks(gc, op, [X, a, b], 1, [0])
# # Gradient check wrt b
self.assertGradientChecks(gc, op, [X, a, b], 2, [0])
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