zea.backend.tensorflow¶

Tensorflow Ultrasound Beamforming Library.

Initialize modules for registries.

Functions

on_device_tf(func, inputs, device[, ...])

Applies a Tensorflow function to inputs on a specified device.

zea.backend.tensorflow.on_device_tf(func, inputs, device, return_numpy=False, **kwargs)[source]¶

Applies a Tensorflow function to inputs on a specified device.

Parameters:

func (function) – Function to apply to the input data.
inputs (ndarray) – Input array.
device (str) – Device string, e.g. 'cuda', 'gpu', or 'cpu'.
return_numpy (bool, optional) – Whether to convert output data back to numpy. Defaults to False.
**kwargs – Additional keyword arguments to be passed to the func.

Returns:

The output data.

Return type:

tf.Tensor or ndarray

Raises:

AssertionError – If func is not a function from the tensorflow library.

Note

This function converts the inputs array to a tf.Tensor and moves it to the specified device. It then applies the func function to the inputs and returns the output data. If the output is a dictionary, it extracts the first value from the dictionary. If return_numpy is True, it converts the output data back to a numpy array before returning.

Example

import tensorflow as tf


def square(x):
    return x**2


inputs = [1, 2, 3, 4, 5]
device = "cuda"
output = on_device_tf(square, inputs, device)

Modules

`dataloader`	HDF5 Tensorflow dataloader.
`layers`
`losses`	Container for custom loss functions.
`models`
`utils`