def testGlobalDispatcher(self):
original_global_dispatchers = dispatch._GLOBAL_DISPATCHERS
try:
TensorTracerOpDispatcher().register()
x = TensorTracer("x")
y = TensorTracer("y")
trace = math_ops.reduce_sum(math_ops.add(math_ops.abs(x), y), axis=3)
self.assertEqual(
str(trace), "math.reduce_sum(math.add(math.abs(x), y), axis=3)")
proto_val = TensorTracer("proto")
trace = decode_proto(proto_val, "message_type", ["field"], ["float32"])
self.assertIn("io.decode_proto(bytes=proto,", str(trace))
finally:
# Clean up.
dispatch._GLOBAL_DISPATCHERS = original_global_dispatchers
def testVecHostPortRpcUsingEncodeAndDecodeProto(self):
with self.cached_session() as sess:
request_tensors = proto_ops.encode_proto(
message_type='tensorflow.contrib.rpc.TestCase',
field_names=['values'],
sizes=[[3]] * 20,
values=[
[[i, i + 1, i + 2] for i in range(20)],
])
response_tensor_strings = self.rpc(
method=self.get_method_name('Increment'),
address=self._address,
request=request_tensors)
_, (response_shape, ) = proto_ops.decode_proto(
bytes=response_tensor_strings,
message_type='tensorflow.contrib.rpc.TestCase',
field_names=['values'],
output_types=[dtypes.int32])
response_shape_values = sess.run(response_shape)
self.assertAllEqual([[i + 1, i + 2, i + 3] for i in range(20)],
response_shape_values)
def testVecHostPortRpcUsingEncodeAndDecodeProto(self):
with self.cached_session() as sess:
request_tensors = proto_ops.encode_proto(
message_type='tensorflow.contrib.rpc.TestCase',
field_names=['values'],
sizes=[[3]] * 20,
values=[
[[i, i + 1, i + 2] for i in range(20)],
])
response_tensor_strings = self.rpc(
method=self.get_method_name('Increment'),
address=self._address,
request=request_tensors)
_, (response_shape,) = proto_ops.decode_proto(
bytes=response_tensor_strings,
message_type='tensorflow.contrib.rpc.TestCase',
field_names=['values'],
output_types=[dtypes.int32])
response_shape_values = sess.run(response_shape)
self.assertAllEqual([[i + 1, i + 2, i + 3]
for i in range(20)], response_shape_values)