eager-execution
There are 39 repositories under eager-execution topic.
jonasrauber/eagerpy
PyTorch, TensorFlow, JAX and NumPy — all of them natively using the same code
titu1994/tfdiffeq
Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
crisbodnar/TensorFlow-NEAT
TensorFlow Eager implementation of NEAT and Adaptive HyperNEAT
Shathe/MNasNet-Keras-Tensorflow
A Tensorflow Keras implementation (Graph and eager execution) of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.
Viredery/tf-eager-fasterrcnn
Faster R-CNN R-101-FPN model was implemented with TensorFlow2.0 eager execution.
hereismari/tensorflow-maml
TensorFlow 2.0 implementation of MAML.
DHZS/tf-deformable-conv-layer
TensorFlow implementation of Deformable Convolutional Layer
DHZS/tf-dropblock
TensorFlow implementation of DropBlock
mhmoodlan/cyclic-learning-rate
Cyclic learning rate TensorFlow implementation.
jmpap/YOLOV2-Tensorflow-2.0
Just another YOLO V2 implementation. Train your own dataset in a jupyter notebook!
hellocybernetics/TensorFlow2.0_Eager_Execution_Tutorials
Tutorials of TensorFlow eager execution
Shathe/Semantic-Segmentation-Tensorflow-Eager
An example of semantic segmentation using tensorflow in eager execution.
Rowing0914/TF_RL
Eagerly Experimentable!!!
hlamba28/NMT-with-Attention-Mechanism
In this project I implement Neural Machine Translation using Attention mechanism. The code is written using the TensorFlow library in Python. I have used TensorFlow functionalities like tf.data.Dataset to manage the input pipeline, Eager Execution and Model sub classing to create the model architecture.
dusanerdeljan/tensor-math-library
Header only lazy evaluation tensor math library with multi-backend parallel eager execution support (TBB, OpenMP, Parallel STL and in the future CUDA and OpenCL)
fomorians-oss/pyoneer
Tensor utilities, reinforcement learning, and more!
fomorians/forward-models
A tutorial on forward models for model-based reinforcement learning.
jonasrauber/foolbox-native
Foolbox Native brings native performance to Foolbox
rayruchira/Neural-Style-Transfer
Implementing Style Transfer in Tensorflow 2.0, using the VGG19 network architecture, which composes the content image in the style of the reference picture, both input by the user.
krippner/auto-diff
A modular C++17 framework for automatic differentiation
moon-home/ErrorShaping
A proposal for distribution-based loss function in neural network
paklong/Tensorflow-2.0-gradient-descent
3 different ways to implement GD in TF2.0
salty-vanilla/tf-anomaly
Major anomaly detection methods using neural networks are implemented in this repository 🔥
rkshiyaniya/Eager-Few-Shot-Object-Detection
This repository contains a notebook for object detection with the help of fine tuning of a (TF2 friendly) RetinaNet architecture on very few examples of a novel class after initializing from a pre-trained COCO checkpoint. Training runs in eager mode.
salty-vanilla/tf-gans
Major GANs are implemented in this repository 🔥
agatan/tf-mobilenetv2
MobileNetV2 written in tensorflow, training with eager mode and estimator API
DHZS/image-style-transfer-tensorflow
Image Style Transfer in TensorFlow
mrtoronto/mueller-model
Using an RNN to make predictions about redactions from the Mueller report
rkshiyaniya/Object-Detection-Using-TensorFlow
This repository contains Various Techniques that can be used for object detection.
singhsidhukuldeep/Tensorflow-Eager-Execution
Eager Execution enables you to run operations immediately
AIArabicProjects/neural-style-transfer
نقل النمط العصبوني: بناء طريقة للتعلم العميق باستخدام كيراس tf.keras و منفّذ إيجر eager execution
akashbangera758/CRNN_Text_Recognition_Tensorflow
This is a Tensorflow implementation of text recognition model from the paper "An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition".
krippner/auto-diff-python
Lightweight Python package for automatic differentiation
kbmclaren/tensorFlow-CMSC478-ML
Get started with Tensorflow/Keras API.
paklong/Tensorflow-2.0-Example
Example code for using Tensorflow 2.0 with both numerical and categorical data