forked from mindspore-Ecosystem/mindspore
fix sens shape error in loss_scale one_step_wrap
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@ -249,7 +249,9 @@ class TrainOneStepWithLossScaleCell(Cell):
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scaling_sens = self.loss_scale
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else:
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scaling_sens = sens
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grads = self.grad(self.network, weights)(data, label, F.cast(scaling_sens, F.dtype(loss)))
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scaling_sens_filled = C.ones_like(loss) * F.cast(scaling_sens, F.dtype(loss))
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grads = self.grad(self.network, weights)(data, label, scaling_sens_filled)
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grads = self.hyper_map(F.partial(_grad_scale, scaling_sens), grads)
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# apply grad reducer on grads
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grads = self.grad_reducer(grads)
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@ -154,7 +154,8 @@ def build_train_network(network, optimizer, loss_fn=None, level='O0', **kwargs):
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loss_scale = loss_scale_manager.get_loss_scale()
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update_cell = loss_scale_manager.get_update_cell()
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if update_cell is not None:
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if not (context.get_context("enable_ge") or (context.get_context("device_target") == "GPU")):
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# only cpu not support `TrainOneStepWithLossScaleCell` for control flow.
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if not context.get_context("enable_ge") and context.get_context("device_target") == "CPU":
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raise ValueError("Only `loss_scale_manager=None` and "
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"`loss_scale_manager=FixedLossScaleManager(drop_overflow_update=False)`"
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"are supported in current version. If you use `O2` option, please"
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@ -93,7 +93,8 @@ def loss_scale_manager_common(strategy1):
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assert False
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def test_dataset_interface_sens_scalar():
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def fixme_test_dataset_interface_sens_scalar():
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# With error: "The type of sens node is not Tensor or Parameter, it is unsupported now."
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strategy1 = ((8, 1), )
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loss_scale_manager_common(strategy1)
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