mindflow.pde.UnsteadyFlowWithLoss
- class mindflow.pde.UnsteadyFlowWithLoss(model, t_in=1, t_out=1, loss_fn='mse', data_format='NTCHW')[源代码]
基于数据驱动的非定常流体问题求解的基类。
- 参数:
model (mindspore.nn.Cell) - 用于训练的网络模型。
t_in (int) - 初始步长。默认值:
1
。t_out (int) - 输出步长。 默认值:
1
。loss_fn (Union[str, Cell]) - 损失函数。默认值:
'mse'
。data_format (str) - 数据格式。默认值:
'NTCHW'
。
- 支持平台:
Ascend
GPU
样例:
>>> import numpy as np >>> from mindspore import Tensor >>> import mindspore >>> from mindflow.pde import UnsteadyFlowWithLoss >>> from mindflow.cell import FNO2D >>> from mindflow.loss import RelativeRMSELoss ... >>> model = FNO2D(in_channels=1, out_channels=1, resolution=64, modes=12) >>> problem = UnsteadyFlowWithLoss(model, loss_fn=RelativeRMSELoss(), data_format='NHWTC') >>> inputs = Tensor(np.random.randn(32, 64, 64, 1, 1), mindspore.float32) >>> label = Tensor(np.random.randn(32, 64, 64, 1, 1), mindspore.float32) >>> loss = problem.get_loss(inputs, label) >>> print(loss) 31.999998