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.

Sign up for GitHub

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

fix typos and sentence structure in README.md #1633

Merged
merged 1 commit into from
Jul 22, 2021
Merged

fix typos and sentence structure in README.md #1633

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
6 changes: 3 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ before running this command.)

### Nightly build

Note that nightly build is build on PyTorch's nightly build. Therefore, you need to install the latest PyTorch when you use nightly build of torchaudio.
Note that nightly build is built on PyTorch's nightly build. Therefore, you need to install the latest PyTorch when you use nightly build of torchaudio.

**pip**

Expand All @@ -80,7 +80,7 @@ conda install -y -c pytorch-nightly torchaudio

### From Source

The build process builds libsox and some codecs that torchaudio need to link to. This is achieve by setting the environment variable `BUILD_SOX=1`.
The build process builds libsox and some codecs that torchaudio need to link to. This is achieved by setting the environment variable `BUILD_SOX=1`.
The build process will fetch and build libmad, lame, flac, vorbis, opus, and libsox before building extension. This process requires `cmake` and `pkg-config`.

```bash
Expand Down Expand Up @@ -144,7 +144,7 @@ Conventions
With torchaudio being a machine learning library and built on top of PyTorch,
torchaudio is standardized around the following naming conventions. Tensors are
assumed to have "channel" as the first dimension and time as the last
dimension (when applicable). This makes it consistent with PyTorch's dimensions.
dimension (when applicable). Both of these dimensions make the tensors consistent with PyTorch's dimensions.
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

cc @yangarbiter regarding #1635

For size names, the prefix `n_` is used (e.g. "a tensor of size (`n_freq`, `n_mel`)")
whereas dimension names do not have this prefix (e.g. "a tensor of
dimension (channel, time)")
Expand Down