aesara VS deepo

Compare aesara vs deepo and see what are their differences.

aesara

Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. (by aesara-devs)
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aesara deepo
1 1
1,163 6,314
0.7% -
7.7 3.0
3 months ago over 1 year ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

aesara

Posts with mentions or reviews of aesara. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-16.

deepo

Posts with mentions or reviews of deepo. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing aesara and deepo you can also consider the following projects:

triton - Development repository for the Triton language and compiler

einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

Py2Jl - Python to Julia transpiler.

netron - Visualizer for neural network, deep learning and machine learning models

keras-rl - Deep Reinforcement Learning for Keras.

torchinfo - View model summaries in PyTorch!

MMdnn - MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

Jetson-Nano-Ubuntu-20-image - Jetson Nano with Ubuntu 20.04 image

zipslicer - A library for incremental loading of large PyTorch checkpoints

optimizer - Actively maintained ONNX Optimizer

FloorplanTransformation - Raster-to-Vector: Revisiting Floorplan Transformation

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.