{"push_id":3099000503,"size":7,"distinct_size":1,"ref":"refs/heads/master","head":"c8f12d3ae460685a66b9a7df960194a0bd77bf3b","before":"32f82f7e694236378a4b279028f1cd2843417cd2","commits":[{"sha":"319975abf33a6f9a2fe04b5a66a9afe1aad15c2e","author":{"name":"David Sanders","email":"748ee23f288b28090746b052c2965cbf8efff71f@ucsbalum.com"},"message":"Reset stopTraining at start of fitDataset (#376)\n\nBUG","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/319975abf33a6f9a2fe04b5a66a9afe1aad15c2e"},{"sha":"6edbeadae7493a4b1e4d45b16d38ec74686370ae","author":{"name":"David Sanders","email":"748ee23f288b28090746b052c2965cbf8efff71f@ucsbalum.com"},"message":"Fix typo in fitDataset doc string (#380)","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/6edbeadae7493a4b1e4d45b16d38ec74686370ae"},{"sha":"1f32448ee4f0b15eccdbe45bbf4d259b5a4ef8d8","author":{"name":"Shanqing Cai","email":"700532b7c2af570d950d0329a602f0a1774cbaaa@google.com"},"message":"Add tf.Model.trainOnBatch(); Use numerically-stable impl. of binaryCrossentropy and sparseCategoricalCrossentropy (#382)\n\n- Add `trainOnBatch()` as an async method of `tf.Model` and `tf.Sequential`.\r\n- Fix numerical issues in the `binaryCrossentropy` loss\r\n- Fix numerical issues in the `sparseCategoricalCrossentropy` loss\r\n- Implement metric `sparseCategoricalAccuracy`.","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/1f32448ee4f0b15eccdbe45bbf4d259b5a4ef8d8"},{"sha":"fa97d1a135004175c93f7003a23db7bcada786fd","author":{"name":"Nikhil Thorat","email":"6bc308dba35dd2b334bb766be3c7505ddeb3fb7f@google.com"},"message":"Update core version to 0.14.0 and update layers version to 0.9.0. (#383)","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/fa97d1a135004175c93f7003a23db7bcada786fd"},{"sha":"978c350843d0cbb961362d09beca2dc4dfd33171","author":{"name":"Shanqing Cai","email":"700532b7c2af570d950d0329a602f0a1774cbaaa@google.com"},"message":"Fix a bug in which kwarg is not passed properly to internally nested containers (#384)\n\n- Discovered this problem when working on the MNIST-ACGAN example. The generator model was a functional model that contained a nested sequential model. During `trainOnBatch()` calls, the kwarg `training: true` was not passed down properly. This PR fixes that.\r\n- This PR also unifies execution with `executor.execute()`. The `runInternalGraph()` method will eventually be completely removed.\r\n- The rank and shape check in the `FeedDict` class is removed. It turns out that in some special cases, it is fine to pass mismatched ranks. If such cases do cause problems, the underlying `Layer` or sub-Container will throw an error by itself.\r\n\r\nBUG","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/978c350843d0cbb961362d09beca2dc4dfd33171"},{"sha":"78bcd9adc8815437873a6c3c812a32901518ff32","author":{"name":"Shanqing Cai","email":"700532b7c2af570d950d0329a602f0a1774cbaaa@google.com"},"message":"Revise implementation of BatchNormalization training code to align with tf.keras (#385)\n\n- The implementation of the training algorithm for BatchNormalization is different between keras-team/keras and tensorflow.keras. \r\n- This PR aligns the implementation with the latter. (Previously it aligned with the former.) Rationale:\r\n  - Alignment with TensorFlow is a higher priority for TensorFlow.js than alignment with keras-team/keras\r\n  - The convergence on the MNIST-ACGAN example is better with the tf.keras implementation.\r\n- While this change has no implication for the public API of `tf.layers.batchNormalization`, it may be breaking for users who rely on the *exact numeric values* of the batchNormalization layer during *training*.\r\n\r\nBREAKING","distinct":false,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/78bcd9adc8815437873a6c3c812a32901518ff32"},{"sha":"c8f12d3ae460685a66b9a7df960194a0bd77bf3b","author":{"name":"Mi_iA","email":"0e52089d818f3d5e84b8e077bdcfa037c521ae21@gmail.com"},"message":"Applied tfjs examples' prelu method","distinct":true,"url":"https://api.github.com/repos/rouismia/tfjs-layers/commits/c8f12d3ae460685a66b9a7df960194a0bd77bf3b"}]}
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