prjtrellis
Pytorch
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prjtrellis | Pytorch | |
---|---|---|
5 | 338 | |
381 | 77,783 | |
0.0% | 2.4% | |
8.5 | 10.0 | |
3 months ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 1-Clause License |
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.
prjtrellis
- Project Trellis – Documenting the Lattice ECP5 FPGA Bitstream Format
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Learning Verilog and FPGA
Yosys, the underlying compiler of ice studio, also targets the much bigger ECP5 FPGA, also by Lattice, which is called Project Trellis: https://github.com/YosysHQ/prjtrellis
Yosys functions more like a software open source tool. So command line compiling. It also has a REPL. It is very quick compared to the commercial solutions. Especially around compile times which can take seconds instead of minutes. YMMV, but I think the consensus is that it's a lot more convenient to use.
In general the hardware toolchains feel very ancient compared to software toolchains.
- Project Trellis – fully open-source flow for ECP5 FPGAs, using Yosys and nextpnr
- 5% of 666 Python repos had comma typo bugs (inc V8, TensorFlow and PyTorch)
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Lattice ECP3 - any way of working withe them with free license ?
Not that it will lead to anything soon, you could put a feature request in at Project Trellis and offer to test things, or provide hardware if you have extra.
Pytorch
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
What are some alternatives?
Vulkan-ValidationLayers - Vulkan Validation Layers (VVL)
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
icestorm - Project IceStorm - Lattice iCE40 FPGAs Bitstream Documentation (Reverse Engineered)
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
quickstep - Quickstep project
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
f4pga-arch-defs - FOSS architecture definitions of FPGA hardware useful for doing PnR device generation.
flax - Flax is a neural network library for JAX that is designed for flexibility.
icestorm - Project IceStorm - Lattice iCE40 FPGAs Bitstream Documentaion (Reverse Engineered)
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
apio - :seedling: Open source ecosystem for open FPGA boards
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more