ModelCompressionRL
labml
| ModelCompressionRL | labml | |
|---|---|---|
| 2 | 23 | |
| 0 | 1,874 | |
| - | 2.5% | |
| 2.6 | 9.7 | |
| over 1 year ago | 7 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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ModelCompressionRL
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Requesting help with Custom Layers (Layer Subclassing) - Model fit builds the model again! [Keras]
I saw that the number of filters depends on the height, is the height the same for all images? I guess so since you say that moving the Conv2D to another layer fixes that problem. If my guess is right, the error is that when the model is being build, height is None and you are trying to divide None by a number. To solve this problem you have to get the shape using h = tf.shape(inputs)[1] as 0 is the batch dimension. As for getting the tf.concat as a layer. You can use tf.keras.layers.concatenate, it works the same as tf.concat, but it is a layer. I am using it in a layer that performs to parallel convolutions and then concatenates both convolutions. When I print the summary I only get the name of the layer, not the tf.concat as you mention. Search for the FireLayer class in my code
- Adding new block/inputs to non-sequential network
labml
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Creating stickers using SD with img2img
Used the PromptArt app by labml.ai to generate a sticker of an image I took from my iPhone. The results are amazing.
- [D] Why doesn’t your team use an experiment tracking tool?
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Probe PyTorch models
💻 Github
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[P] Probe PyTorch models
🧑🏫 Demo that extracts attention maps of BERT
- Show HN: Probe PyTorch Models
- [D] How do you guys tune hyperparameters, when a single training run takes a long time (days to weeks)?
- Machine Learning Best Practices
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[D] Machine Learning Best Practices
from github
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[P] Annotated deep learning paper implementations
labmlai/labml is a set of tools (tracking experiments, configurations, a bunch of helpers) we coded to ease our ML work (which later improved and open sourced). So we use it in all our projects because it makes things easier for us.
- React's UI State Model vs. Vanilla JavaScript
What are some alternatives?
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
guildai - Experiment tracking, ML developer tools
Practical_RL - A course in reinforcement learning in the wild
Deep-Learning-Push-Up-Counter - Deep Learning approach to count the number of repetitions in a video of push ups or pull ups.
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
Lottery_Ticket_Hypothesis-TensorFlow_2 - Implementing "The Lottery Ticket Hypothesis" paper by "Jonathan Frankle, Michael Carbin"
spock - spock is a framework that helps manage complex parameter configurations during research and development of Python applications
tensorflow-deep-learning - All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow - In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
text-to-text-transfer-transformer - Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"