def send_watchpoint_hit(self):
"""Send watchpoint hit value."""
tensors = [
TensorProto(node_name='Default/TransData-op99', slot='0'),
TensorProto(
node_name='Default/optimizer-Momentum/ApplyMomentum-op25',
slot='0')
]
response = self.stub.SendWatchpointHits(self._generate_hits(tensors))
assert response.status == EventReply.Status.OK
def generate_tensor(in_tensor=None):
"""Generate tensor message."""
tensor_content = np.asarray([1, 2, 3, 4, 5, 6]).astype(np.float32).tobytes()
tensors = [TensorProto(), TensorProto()]
tensors[0].CopyFrom(in_tensor)
tensors[0].data_type = DataType.DT_FLOAT32
tensors[0].dims.extend([2, 3])
tensors[1].CopyFrom(tensors[0])
tensors[0].tensor_content = tensor_content[:12]
tensors[1].tensor_content = tensor_content[12:]
tensors[0].finished = 0
tensors[1].finished = 1
for sub_tensor in tensors:
yield sub_tensor
def get_tensors():
"""Get tensors."""
tensor_content = np.asarray([1, 2, 3, 4, 5,
6]).astype(np.float32).tobytes()
tensor_pre = TensorProto(node_name='mock_node_name',
slot='0',
data_type=DataType.DT_FLOAT32,
dims=[2, 3],
tensor_content=tensor_content[:12],
finished=0)
tensor_succ = TensorProto()
tensor_succ.CopyFrom(tensor_pre)
tensor_succ.tensor_content = tensor_content[12:]
tensor_succ.finished = 1
return [tensor_pre, tensor_succ]