Traceback (most recent call last):


 "/home/ubuntu/bitmax/hummingbot/core/utils/async_utils.py", line 9, in safe_wrapper

return await c


 "/home/ubuntu/bitmax/hummingbot/connector/exchange/bitmax/bitmax_exchange.py", line 492, in _create_order

raise ValueError(f"Notional amount {notional} is not withing the range of {bitmax_trading_rule.minNotional}-{bitmax_trading_rule.maxNotional}.")
ValueError: Notional amount 1.84714 is not withing the range of 5-400000.

Traceback (most recent call last):


 "/home/user/cluster/base/FullyConvolutional.py", line 959, in <module>

gr.pretrainSBU(110)


 "/home/user/cluster/base/FullyConvolutional.py", line 897, in pretrainSBU

period=10)]) # train the new layer until no improvement occurs


 "/home/user/software/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 1013, in fit

self._make_train_function()


 "/home/user/software/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 497, in _make_train_function

loss=self.total_loss)


 "/home/user/software/tensorflow/lib/python2.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/home/user/software/tensorflow/lib/python2.7/site-packages/keras/optimizers.py", line 381, in get_updates

new_a = self.rho * a + (1. - self.rho) * K.square(g)


 "/home/user/software/tensorflow/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 967, in binary_op_wrapper

with ops.name_scope(None, op_name, [x, y]) as name:


 "/home/user/software/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5977, in __enter__

g = _get_graph_from_inputs(self._values)


 "/home/user/software/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5637, in _get_graph_from_inputs

_assert_same_graph(original_graph_element, graph_element)


 "/home/user/software/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5573, in _assert_same_graph

original_item))
ValueError: Tensor("mul:0", shape=(3, 3, 3, 64), dtype=float32) must be from the same graph as Tensor("training/Adadelta/mul:0", shape=(3, 3, 3, 64), dtype=float32).
