Run LDC: (Lid Driven Cavity Flow 顶盖驱动方腔流动) $ tar zxf Modulus_examples.tar.gz $ cd modulus/examples/ldc $ python ldc_2d.py 会产生训练出来的 ckpt 模型 2. LDC模型网络结构 将产生的 ckpt 模型转成 pb, 再转成tensorboard 根据模型结构能更好的理解 code 采用了 6 层 FC 输入为 x_2 ...
python ldc_2d.py 控制台应该在每一步打印损失。但是,很难通过命令窗口监控收敛,可以改用 Tensorboard,以图形方式监控训练过程中的损失。 8、结果和后处理 Tensorboard是机器学习实验可视化的绝佳工具。为了可视化各种训练和验证损失,张量板可以设置如下: 在单独的终端窗口中,导航到示例的工作目录examples/ldc/ 2、在命...
python ldc_2d.py 控制台应该在每一步打印损失。但是,很难通过命令窗口监控收敛,可以改用 Tensorboard,以图形方式监控训练过程中的损失。 8、结果和后处理 Tensorboard是机器学习实验可视化的绝佳工具。为了可视化各种训练和验证损失,张量板可以设置如下: 在单独的终端窗口中,导航到示例的工作目录examples/ldc/ 2、在命...
Technical Support (Modulus Only) python , physics , modulus 2 1266 2024 年2 月 22 日 PINN Domain Decomposition Technical Support (Modulus Only) modulus 1 1348 2023 年12 月 8 日 Omniverse - Extensio Modulus Samples & Examples modulus 1 341 2023 年11 月 22 日 ...
Check the examples below to observe the behavior of the modulo operator in Python. print(-7 % 3) print(7 % -3) Output: 2 -2 In the first example, -7 % 3 gives us the remainder -1. As the remainder (-1) and divisor (3) are of opposite signs, their sum will give us the...
For the concrete examples of DeepONet in Modulus, please see tutorialDeep Operator Network. References [1] Young, D. L., C. H. Tsai, and C. S. Wu. “A novel vector potential formulation of 3D Navier–Stokes equations with through-flow boundaries by a local meshless method.” Journal of...
Practical Differences in Output To appreciate the difference, consider these examples: intdivisionResult=10/3;// divisionResult will be 3 intmoduloResult=10%3;// moduloResult will be 1 In the division example,10 / 3yields3because 3 fits into 10 three times. However,10 % 3yields1because aft...
Themodulus operatoris an arithmetic operator in C language; it is a binary operator and works with two operands. It is used to find the remainder. Syntax operand1 % operand2; It returns the remainder which comes after dividingoperand1byoperand2. ...
min_delta: Minimum required change in the metric to qualify as a training improvement. patience: Number of training steps to wait for a training improvement to happen. mode: Choose ‘min’ if the metric is to be minimized, or ‘max’ if the metric is to be maximized. ...
cd ./examples/ldc/ # run on dynamic(i.e. eager mode) graph mode python ldc_2d.py # run on dy2st mode python ldc_2d.py jit=true jit_use_cinn=false # run on cinn mode(i.e. compiled mode, recommended for performance) python ldc_2d.py jit=true Contributing For guidance on making...