toml-rs
tensorflow_macos
toml-rs | tensorflow_macos | |
---|---|---|
8 | 33 | |
1,034 | 2,887 | |
- | - | |
3.1 | 3.4 | |
over 1 year ago | almost 3 years ago | |
Rust | Shell | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
toml-rs
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`toml` vs `toml_edit` (ie `toml` 0.6 is out)
I updated the toml<->json online converter after the ValueAfterTable error has been fixed with toml 0.6. Very nice to see progress on the toml and toml_edit crates.
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Error trying to deserialize TOML using Rust/SERDE
use std::fs::File; use std::io::Write; use std::collections::BTreeMap as Map; use serde_derive::{Serialize, Deserialize}; #[derive(Debug)] #[derive(Serialize, Deserialize)] #[serde(tag = "type0")] enum FooBarTwo<'a> { FooBarOne { string1: &'a str }, } #[derive(Debug)] #[derive(Serialize, Deserialize)] #[serde(tag = "type1")] enum FooBarThree<'a> { FooBarFour { string2: &'a str }, } #[derive(Debug)] #[derive(Serialize, Deserialize)] struct FooBarFour<'a> { black: &'a str, #[serde(borrow)] green: FooBarTwo<'a>, #[serde(borrow)] blue: FooBarThree<'a>, } #[derive(Debug)] #[derive(Serialize, Deserialize)] struct FooBarFourList<'a> { // Uasing a Map to workaround a known bug (#303) when using top level Vec // see https://github.com/alexcrichton/toml-rs/issues/303 #[serde(borrow)] foo_bar_six: Map<&'a str, FooBarFour<'a>> } fn main() { let red = FooBarFour { black: "aaa", green: FooBarTwo::FooBarOne { string1: "aaaabbbb" }, blue: FooBarThree::FooBarFour { string2: "ccccccc" }, }; let pink = FooBarFour { black: "aaa", green: FooBarTwo::FooBarOne { string1: "aaaabbbb" }, blue: FooBarThree::FooBarFour { string2: "ccccccc" }, }; let mut white = Map::new(); white.insert("pink", pink); white.insert("red", red); let fbfl = FooBarFourList { foo_bar_six: white }; println!("\nTL: {:?}\n", fbfl); let filename = "./data/test.toml"; let data = toml::to_string(&fbfl).expect("Error serialising fbfl"); println!("\nTL as TOML: {:?}\n", data); let mut f = File::create(filename).expect("Unable to create file"); f.write_all(data.as_bytes()).expect("Error writing data to file"); let toml_in: FooBarFour = toml::from_str(&data).expect("Error deserialising fbfl"); println!("\n{:?}\n", toml_in); }
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Introduction to Rust generics [1/2]: Traits
This is especially useful for data deserialization: Just by implementing the Serialize and Deserialize traits from the serde crate, the (almost) universally used serialization library in the Rust world, we can then serialize and deserialize our types to a lot of data formats: JSON, YAML, TOML, BSON and so on...
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Hey Rustaceans! Got a question? Ask here! (21/2022)!
It looks like the fields are public now (https://github.com/alexcrichton/toml-rs/pull/455, https://docs.rs/toml/latest/toml/value/struct.Date.html), so just upgrading the crate should do it :-)
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anyone using rust in production? what do you do?
Pair that with Serde for serialization/deserialization (JSON, TOML, YAML, CSV/TSV, XML, URL query strings, etc.), Figment for configuration, and ignore for filesystem traversal with blacklist support, and Rust is a real joy for writing CLI utilities.
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toml_edit v0.3
Added toml-rs-compatible API via the toml_edit::easy module for when developers want to ensure consistency between format-preserving and general TOML work, with one caveat.
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Hey Rustaceans! Got an easy question? Ask here (16/2021)!
A quick example off the top of the head of my head is some tests in the toml package. It has a few different approaches. One is to use macros as in parser.rs. In valid.rs and invalid.rs it uses macros to generate a separate test for each input file. This allows you to run just one individual test from the list. These examples aren't perfect, and there are more sophisticated test utilities (like insta) that can abstract the process of "here are a bunch of inputs, test them all".
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Reading TOML with default values
I want to read a toml file with default value. I tried toml-rs but it doesn't allow for default values.
tensorflow_macos
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Updated Apple Silicon Guide for M2 Pro and M2 Max Chips
https://github.com/apple/tensorflow_macos is no longer needed
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The hunt for the M1’s neural engine
Tensorflow has a CoreML enabled version which run on ANE.
https://github.com/apple/tensorflow_macos
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M1 Mac users
Apple released a guide on how to use the M1's integrated Neural Chip in TensorFlow. Have a look at this Apple documentation page (and maybe also this GitHub that talks about TensorFlow together with Apple's own ML Compute platform).
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MacBook Air or Wait for new potential MacBook Air with M2
Tensorflow does work on Apple Silicon
- Kernels dying when using tensorflow in Jupyter Notebooks.
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Main PyTorch maintainer confirms that work is being done to support Apple Silicon GPU acceleration for the popular machine learning framework.
Apple did some work to optimize tensorflow for M1, can be found here https://github.com/apple/tensorflow_macos It's alpha, but works fine, I tried it
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The M1 Max is the fastest GPU we have ever measured in Affinity Photo benchmark
https://github.com/apple/tensorflow_macos/issues/25
https://forums.macrumors.com/threads/apple-silicon-deep-lear...
It is expected that the M1 Max should have similar performance to a RTX-2080 or Titan X.
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MacBook Pro M1 Pro benchmark
In case anyone is interested, in ran a fairly simple MNIST benchmark (proposed here : https://github.com/apple/tensorflow_macos/issues/25) on my recently acquired M1 Pro MBP (16-core GPU, 16GB RAM).
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Error while installing tensorflow on Mac M1
The only method I know of to download tensorflow on M1 macs is the one documented here: https://github.com/apple/tensorflow_macos
- How exactly does the Neural Engine benefit the consumer?
What are some alternatives?
serde-yaml - Strongly typed YAML library for Rust
miniforge - A conda-forge distribution.
cargo-flamegraph - Easy flamegraphs for Rust projects and everything else, without Perl or pipes <3
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
toml - Rust TOML Parser
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
rust-esp32-std-demo - Rust on ESP32 STD demo app. A demo STD binary crate for the ESP32[XX] and ESP-IDF, which connects to WiFi, Ethernet, drives a small HTTP server and draws on a LED screen.
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
rust - Empowering everyone to build reliable and efficient software.
flamegraph - Easy flamegraphs for Rust projects and everything else, without Perl or pipes <3
community-localization
Python-docker - Docker Official Image packaging for Python