22 releases
new 0.3.28 | Oct 15, 2024 |
---|---|
0.3.25 | Aug 7, 2024 |
0.3.23 | Jul 30, 2024 |
0.3.11 | Mar 26, 2024 |
#129 in Machine learning
1,317 downloads per month
145KB
2K
SLoC
tlparse: Parse structured PT2 logs
tlparse
parses structured torch trace logs and outputs HTML files analyzing data.
Quick start: Run PT2 with the TORCH_TRACE environment variable set:
TORCH_TRACE=/tmp/my_traced_log example.py
Feed input into tlparse:
tlparse /tmp/my_traced_log -o tl_out/
Adding custom parsers
You can extend tlparse with custom parsers which take existing structured log data and output any file. To do so, first implement StructuredLogParser with your own trait:
pub struct MyCustomParser;
impl StructuredLogParser for MyCustomParser {
fn name(&self) -> &'static str {
"my_custom_parser"
}
fn get_metadata<'e>(&self, e: &'e Envelope) -> Option<Metadata<'e>> {
// Get required metadata from the Envelope.
// You'll need to update Envelope with your custom Metadata if you need new types here
....
}
fn parse<'e>(&self,
lineno: usize,
metadata: Metadata<'e>,
_rank: Option<u32>,
compile_id: &Option<CompileId>,
payload: &str
) -> anyhow::Result<ParserResult> {
// Use the metadata and payload however you'd like
// Return either a ParserOutput::File(filename, payload) or ParserOutput::Link(name, url)
}
}
How to release
- Make a release commit by updating Cargo.toml and then running cargo update
- Push the release commit and a tag for it. This will trigger PyPI release
- cargo publish
Dependencies
~10–20MB
~255K SLoC