Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Mini fixes in the doc #71

Merged
merged 1 commit into from
Jan 21, 2025
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
mini fixes in the doc
mariogeiger committed Jan 18, 2025
commit 0665a7208aab775c198550fd9781d7fb9d76fc56
4 changes: 3 additions & 1 deletion docs/tutorials/etp.rst
Original file line number Diff line number Diff line change
@@ -16,7 +16,7 @@
Equivariant Tensor Product
==========================

The submodule :class:`cuequivariance.descriptors` contains many descriptors of Equivariant Tensor Products (:class:`cuequivariance.EquivariantTensorProduct`).
The submodule :class:`cuequivariance.descriptors` contains many descriptors of Equivariant Tensor Products represented by the class :class:`cuequivariance.EquivariantTensorProduct`.

Examples
--------
@@ -59,6 +59,7 @@ Execution on JAX

import jax
import jax.numpy as jnp
import cuequivariance as cue
import cuequivariance_jax as cuex

e = cue.descriptors.linear(
@@ -83,6 +84,7 @@ We can execute an :class:`cuequivariance.EquivariantTensorProduct` with PyTorch.
.. jupyter-execute::

import torch
import cuequivariance as cue
import cuequivariance_torch as cuet

e = cue.descriptors.linear(
6 changes: 3 additions & 3 deletions docs/tutorials/stp.rst
Original file line number Diff line number Diff line change
@@ -50,7 +50,7 @@ The subscripts of this tensor product are "uv,iu,iv" where "uv" represents the m
d

Each operand of the tensor product descriptor has a list of segments.
We can add segments to the descriptor using the `add_segment` method.
We can add segments to the descriptor using the :meth:`add_segment <cuequivariance.SegmentedTensorProduct.add_segment>` method.
We can add the segments of the input and output representations to the descriptor.

.. jupyter-execute::
@@ -90,15 +90,15 @@ Finally, we can normalize the paths for the last operand such that the output is

As we can see, the paths coefficients has been normalized.

Now we can create a tensor product from the descriptor and execute it. In PyTorch, we can use the :class:`cuet.TensorProduct` class.
Now we can create a tensor product from the descriptor and execute it. In PyTorch, we can use the :class:`cuet.TensorProduct <cuequivariance_torch.TensorProduct>` class.

.. jupyter-execute::

linear_torch = cuet.TensorProduct(d, use_fallback=True)
linear_torch


In JAX, we can use the :func:`cuex.tensor_product` function.
In JAX, we can use the :func:`cuex.tensor_product <cuequivariance_jax.tensor_product>` function.

.. jupyter-execute::