fuse_bn_into_conv optimization fails on big-endian architecture #6
Description
Bug Report
This test was run on s390x. s390x is big-endian architecture.
Failure log from pytest:
_______________________________________________ TestOptimizer.test_fuse_bn_into_conv_simple ________________________________________________
self = <optimizer_test.TestOptimizer testMethod=test_fuse_bn_into_conv_simple>
def test_fuse_bn_into_conv_simple(self): # type: () -> None
for (tensor_type, np_type) in [(TensorProto.FLOAT, np.float32), (TensorProto.DOUBLE, np.float64)]:
conv = helper.make_node("Conv", ["X", "W", "B"], ["Y"])
bn = helper.make_node("BatchNormalization", [
"Y", "scale", "b", "mean", "var"], ["Z"])
W = np.random.randn(3, 2, 5, 5).astype(np_type) + 2
B = np.random.randn(3,).astype(np_type) + 2
scale = np.random.randn(3,).astype(np_type) + 2
b = np.random.randn(3,).astype(np_type) + 2
mean = np.random.randn(3,).astype(np_type) + 2
var = np.abs(np.random.randn(3,).astype(np_type)) + 2
initializers = [
helper.make_tensor(name, tensor_type,
npa.shape, npa.tobytes(), raw=True)
for name, npa in [('W', W), ('B', B), ('scale', scale), ('b', b), ('mean', mean), ('var', var)]
]
graph = helper.make_graph(
[conv, bn],
"test",
[helper.make_tensor_value_info("X", tensor_type, (5, 2, 28, 28)),
helper.make_tensor_value_info("W", tensor_type, (3, 2, 5, 5)),
helper.make_tensor_value_info("B", tensor_type, (3,)),
helper.make_tensor_value_info("scale", tensor_type, (3,)),
helper.make_tensor_value_info("b", tensor_type, (3,)),
helper.make_tensor_value_info("mean", tensor_type, (3,)),
helper.make_tensor_value_info("var", tensor_type, (3,))],
[helper.make_tensor_value_info(
"Z", tensor_type, (5, 3, 24, 24))],
initializer=initializers,
value_info=[
helper.make_tensor_value_info(
"Y", tensor_type, (5, 3, 24, 24))
]
)
optimized_model = self._optimized(graph, ["fuse_bn_into_conv"])
self.assertEqual(len(optimized_model.graph.node), 1)
self.assertEqual(optimized_model.graph.node[0].op_type, 'Conv')
self.assertEqual(len(optimized_model.graph.initializer), 2)
new_W = numpy_helper.to_array(optimized_model.graph.initializer[0])
new_b = numpy_helper.to_array(optimized_model.graph.initializer[1])
f = scale / np.sqrt(var + 1e-5)
> np.testing.assert_almost_equal((B - mean) * f + b, new_b)
E AssertionError:
E Arrays are not almost equal to 7 decimals
E
E Mismatched elements: 3 / 3 (100%)
E Max absolute difference: 2.7824624e+14
E Max relative difference: 1.0692023e+32
E x: array([-1.3619891, 2.4206262, 2.2576501], dtype=float32)
E y: array([-4.7447069e-14, -2.2639551e-32, 2.7824624e+14], dtype=float32)
optimizer_test.py:1509: AssertionError
The fuse_bn_into_conv.h code does not account for potentially running on a big-endian architecture machine when running the optimization routines.
Attached is a patch file with updated source files with a proposed fix for this optimization issue.
A pull request can be submitted if needed.