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Tensorflow 0.5 #210
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Tensorflow 0.5 #210
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Except `main.swift` files which are the entry points for executables. Running the following command does not produce any output: `find . -type f -name "[[:lower:]]*.swift" | rg --pcre2 "^(?!.*(main.swift))"` Resolves #133.
… work with the bigger GPT-2 models (It is called "staged release". as of now, only 117M and 345M are available). (#154)
See https://bugs.swift.org/browse/TF-516 for additional context.
- Add MNIST test set evaluation. - The batch size and the optimizer are changed to `128` and `Adam`, respectively, based on test set evaluation results. Tested with higher batch sizes [256, 512], but found no improvement in performance.
…w issues caused by `swift-apis` changes. (#166) * Updated Transformer and MNIST models to work with 2019-06-04 development snapshot. * Updated other models. * Updated ResNet to work with 2019-06-04 development snapshot. * Updated Catch and CIFAR models. * Added a method to satisfy TensorGroup protocol that can pass build.
New 'Differentiable' derived conformances will not include constant properties in the tangent space.
…port. (#176) This replicates the following pull request on swift-apis: tensorflow/swift-apis#374 , adding a `swift-format` configuration file. Note the cautions indicated in that pull request around use of `swift-format` at present. This also adds a .gitignore line to prevent Xcode 11's new SwiftPM support from adding supporting files to the repository.
* Replaced all Python code in the CIFAR10 and ResNet examples, removing Python 3 dependency. * Needed to import FoundationNetworking on Linux. * Added a check for FoundationNetworking, added an early exit for cached directory check. * Removed macOS availability check by targeting 10.13 in the package. * Style and formatting fixes. * Removed no-longer-needed _tensorHandles and supporting code.
* Add GAN Example * Remove do blocks * Replace lrelu with closure * Remove typealiases * Add comment * Remove labels in GAN example * Rename variables * Code formatting, update comments * Fix: latentDim -> latentSize * Add spaces around * * Code formatting, rename loss functions * Fix: generatorLossFunc -> generatorLoss * Break lines to make it fit within 100 columns * Update comments * Rename plot->plotImage, imageGrid->gridImage, Code formatting * Refactor: Label creation * Update comment * Remove type parameter, empty line * Update readme
…aset code (#182) * Extracted MNIST dataset, created LeNet network, added example combining the two. * Extracted redundant MNIST loading code from GAN and Autoencoder examples, replaced with central MNIST dataset. * Renamed input parameters and applied standard formatting style to MNIST. * Punctuation correction. Co-Authored-By: Richard Wei <[email protected]> * README formatting update. Co-Authored-By: Richard Wei <[email protected]> * Renamed trainImages -> trainingImages, corrected Python package names, formatted Package.swift.
This file is no longer needed apple/swift #26023 and may be causing the segfault reported in swift-apis #186.
#192) * [Models] Fix enumeration of blocks in `ResidualBasicBlockStack` initialization * Start range at * Update ranges
* Add files via upload * Implemented requested changes Corrected formatting mistakes, used dropout correctly, removed the hard coded number of classes and improved overall readability. * Update SqeezeNet.swift Renamed numClasses to classCount and limited all lines to a size of 100.
* add identity connections to WideResNet * rename preact1 for clarity * remove extra relu, add dropout * fix declarartion * skip dropout in expansion blocks * remove enum, res layers to one line
…dependencies (#188) * Added an Image struct as a wrapper for JPEG loading / saving, removed matplotlib dependency from GAN and Autoencoder examples using this. * Formatting update for Autoencoder. * Bring this inline with current API. * Made saveImage() a throwing function, improved formatting. * Changed function parameter.
* Convert MNIST classifier to use sequential * Review Changes * Remove ImageClassification Models
Partially fixes #202.
#198) * Implemented inference tests with random tensors and starting weights for all classification models. * Made sure tests ran on Linux, reshaped output of SqueezeNet to match other classification models. * WideResNet is expressed in terms of CIFAR10, so altered the inputs and outputs appropriately. * Wrapping the reshaping line in SqueezeNet. * Reset ownership. * Reworked TensorShape initializers to use array literals. * Minor formatting tweak to SqueezeNet.
[swift-apis/#497](tensorflow/swift-apis#497) removes deprecated apis, now that we are moving onward to v0.5. This PR updates the catch file which uses a deprecated dense layer.
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Regarding the CLA's, all the commits were already contributed to this project, we are just moving them to another branch. |
rxwei
approved these changes
Sep 24, 2019
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Staging merging the tensorflow 0.5 changes to the stable release once the release goes live.