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@ -29,7 +29,7 @@ from mindspore import nn, Tensor, ParameterTuple, Parameter
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from mindspore.common.initializer import Uniform, initializer
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from mindspore.common.initializer import Uniform, initializer
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
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from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_gradients_mean
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from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_gradients_mean
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
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from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
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from src.callback import EvalCallBack, LossCallBack
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from src.callback import EvalCallBack, LossCallBack
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@ -270,7 +270,7 @@ class TrainStepWrap(nn.Cell):
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self.weights = ParameterTuple(network.trainable_params())
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self.weights = ParameterTuple(network.trainable_params())
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self.optimizer = Adam(self.weights, learning_rate=lr, eps=eps, loss_scale=loss_scale)
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self.optimizer = Adam(self.weights, learning_rate=lr, eps=eps, loss_scale=loss_scale)
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self.hyper_map = C.HyperMap()
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self.hyper_map = C.HyperMap()
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self.grad = C.GradOperation('grad', get_by_list=True, sens_param=True)
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self.grad = C.GradOperation(get_by_list=True, sens_param=True)
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self.sens = loss_scale
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self.sens = loss_scale
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self.reducer_flag = False
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self.reducer_flag = False
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