def testEvaluateWithMultipleDevicesContainingTheSameTensorName(self):
dump = test.mock.MagicMock()
def fake_get_tensors(node_name,
output_slot,
debug_op,
device_name=None):
del output_slot, debug_op # Unused.
if node_name == "a" and device_name is None:
raise ValueError(
"There are multiple (2) devices with nodes named 'a' but "
"device_name is not specified")
elif (node_name == "a"
and device_name == "/job:worker/replica:0/task:0/cpu:0"):
return [np.array(10.0)]
elif (node_name == "a"
and device_name == "/job:worker/replica:0/task:1/cpu:0"):
return [np.array(20.0)]
with test.mock.patch.object(dump,
"get_tensors",
side_effect=fake_get_tensors):
ev = evaluator.ExpressionEvaluator(dump)
with self.assertRaisesRegex(ValueError, r"multiple \(2\) devices"):
ev.evaluate("`a:0` + `a:0`")
self.assertAllClose(
30.0,
ev.evaluate("`/job:worker/replica:0/task:0/cpu:0:a:0` + "
"`/job:worker/replica:0/task:1/cpu:0:a:0`"))
def testEvaluateWithMultipleExecIndexes(self):
dump = test.mock.MagicMock()
def fake_get_tensors(node_name, output_slot, debug_op, device_name=None):
del debug_op, device_name # Unused.
if node_name == "a" and output_slot == 0:
return [np.array([[-1.0], [1.0]]), np.array([[-2.0], [2.0]])]
with test.mock.patch.object(
dump, "get_tensors", side_effect=fake_get_tensors, autospec=True):
ev = evaluator.ExpressionEvaluator(dump)
self.assertAllClose(
[[4.0]], ev.evaluate("np.matmul(`a:0[1]`.T, `a:0[0]`)"))
