Utilities

dist_loss(local_pred_y, local_true_y)

Calculates the distributed normalized root mean squared error (NRMSE) between predicted and actual values.

Arguments

• local_pred_y: Local tensor of predicted values, typically a subset of the whole prediction corresponding to the data handled by a specific node.
• local_true_y: Local tensor of actual values corresponding to a subset of the data

Returns

• A scalar value representing the relative L2 error of the predictions to the true values, which quantifies the prediction error normalized by the magnitude of the actual values.

dist_read_tensor(file_name, key, indices)

Reads a tensor slice from an HDF5 file based on provided indices and reshapes the result.

Arguments

• file_name: The name or path of the HDF5 file from which data is to be read.
• key: The key within the HDF5 file that corresponds to the dataset of interest.
• indices: The indices specifying the slice of the dataset to be extracted.

Returns

• A reshaped array where the first dimension is singleton, extending the dimensions of the original data slice by one.

Functionality

• Opens an HDF5 file in read-only mode.
• Accesses the dataset associated with the provided key.
• Extracts the slice of the dataset specified by indices.
• Reshapes the extracted data, adding a singleton dimension at the beginning.

Example Usage

# To read a specific slice from a dataset within an HDF5 file
tensor_data = dist_read_tensor("data.h5", "dataset_key", (1:10, 5:15, 2:2))

set_gpu_flag(flag::Bool)

Function to set the gpu_flag and update device accordingly. Should be set at the beginning of your script. All FNO computatation following this will use the device set.

set_gpu_flag(flag::Bool)

Function to set the gpu_flag and update device accordingly. Should be set at the beginning of your script. All FNO computatation following this will use the device set.