Dynet

Latest version: v2.1.2

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2.0

This release includes a number of new features that are breaking changes with respect to v1.1.

- DyNet no longer requires boost (thanks xunzhang)! This means that models are now not saved in Boost format, but instead a format supported natively by DyNet.
- Other changes to reading and writing include the ability to read/write only parts of models. There have been a number of changes to the reading/writing interface as well, and examples of how to use it can be found in the "examples". (https://github.com/clab/dynet/issues/84)
- Renaming of "Model" as "ParameterCollection"
- Removing the dynet::expr namespace in C++ (now expressions are in the dynet:: namespace)
- Making VanillaLSTMBuilder the default LSTM interface https://github.com/clab/dynet/issues/474

Other new features include

- Autobatching (by yoavgo and neubig): https://github.com/clab/dynet/blob/master/examples/python/tutorials/Autobatching.ipynb
- Scala bindings (thanks joelgrus!) https://github.com/clab/dynet/pull/357
- Dynamically increasing memory pools (thanks yoavgo) https://github.com/clab/dynet/pull/364
- Convolutions and cuDNN (thanks zhisbug!): https://github.com/clab/dynet/issues/229https://github.com/clab/dynet/issues/236
- Better error handling: https://github.com/clab/dynet/pull/358https://github.com/clab/dynet/pull/365
- Better documentation (thanks pmichel31415!)
- Gal dropout (thanks yoavgo and pmichel31415!): https://github.com/clab/dynet/pull/261
- Integration into pip (thanks danielhers !)
- A cool new logo! (http://dynet.readthedocs.io/en/latest/citing.html)
- A huge number of other changes by other contributors. Thank you everyone!

1.1

This is the branch before transitioning to version 2.

1.0rc1

This is the first release candidate for DyNet version 1.0.
Compared to the previous [cnn](https://github.com/clab/cnn-v1), it supports a number of new features:
- Full GPU support
- Simple support of mini-batching
- Better integration with Python bindings
- Better efficiency
- Correct implementation of l2 regularization
- More supported functions
- And much more!

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