%load_ext d2lbook.tab
tab.interact_select(['mxnet', 'pytorch', 'tensorflow', 'jax'])

Documentation

:begin_tab:mxnet While we cannot possibly introduce every single MXNet function and class (and the information might become outdated quickly), the API documentation and additional tutorials and examples provide such documentation. This section provides some guidance for how to explore the MXNet API. :end_tab:

:begin_tab:pytorch While we cannot possibly introduce every single PyTorch function and class (and the information might become outdated quickly), the API documentation and additional tutorials and examples provide such documentation. This section provides some guidance for how to explore the PyTorch API. :end_tab:

:begin_tab:tensorflow While we cannot possibly introduce every single TensorFlow function and class (and the information might become outdated quickly), the API documentation and additional tutorials and examples provide such documentation. This section provides some guidance for how to explore the TensorFlow API. :end_tab:

%%tab mxnet
from mxnet import np

%%tab pytorch
import torch

%%tab tensorflow
import tensorflow as tf

%%tab jax
import jax

Functions and Classes in a Module

To know which functions and classes can be called in a module, we invoke the dir function. For instance, we can (query all properties in the module for generating random numbers):

%%tab mxnet
print(dir(np.random))

%%tab pytorch
print(dir(torch.distributions))

%%tab tensorflow
print(dir(tf.random))

%%tab jax
print(dir(jax.random))

Generally, we can ignore functions that start and end with __ (special objects in Python) or functions that start with a single _(usually internal functions). Based on the remaining function or attribute names, we might hazard a guess that this module offers various methods for generating random numbers, including sampling from the uniform distribution (uniform), normal distribution (normal), and multinomial distribution (multinomial).

Specific Functions and Classes

For specific instructions on how to use a given function or class, we can invoke the help function. As an example, let's [explore the usage instructions for tensors' ones function].

%%tab mxnet
help(np.ones)

%%tab pytorch
help(torch.ones)

%%tab tensorflow
help(tf.ones)

%%tab jax
help(jax.numpy.ones)

From the documentation, we can see that the ones function creates a new tensor with the specified shape and sets all the elements to the value of 1. Whenever possible, you should (run a quick test) to confirm your interpretation:

%%tab mxnet
np.ones(4)

%%tab pytorch
torch.ones(4)

%%tab tensorflow
tf.ones(4)

%%tab jax
jax.numpy.ones(4)

In the Jupyter notebook, we can use ? to display the document in another window. For example, list? will create content that is almost identical to help(list), displaying it in a new browser window. In addition, if we use two question marks, such as list??, the Python code implementing the function will also be displayed.

The official documentation provides plenty of descriptions and examples that are beyond this book. We emphasize important use cases that will get you started quickly with practical problems, rather than completeness of coverage. We also encourage you to study the source code of the libraries to see examples of high-quality implementations of production code. By doing this you will become a better engineer in addition to becoming a better scientist.

:begin_tab:mxnet Discussions :end_tab:

:begin_tab:pytorch Discussions :end_tab:

:begin_tab:tensorflow Discussions :end_tab:

:begin_tab:jax Discussions :end_tab:

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最后更新: November 25, 2023
创建日期: November 25, 2023