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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog.

This project adheres to Semantic Versioning, with the exception that v0.X updates include backwards-incompatible API changes. From v1.0.0 and on, the project will adherence strictly to Semantic Versioning.

Unpublished

[1.2.3] - 2023-06-16

Fixed

  • Ensure state_index remains on the same device after clean_state.

[1.2.2] - 2023-05-24

Fixed

  • Option to use strings to specify transformer activation.

[1.2.1] - 2023-03-24

### Added

  • Onnx as dev requirement.

Changed

  • Allow torch>=2.0.

[1.2.0] - 2023-03-16

### Added

  • Skip module.

  • “leading” mode in Residual.

[1.1.3] - 2023-03-15

### Added

  • Description of state handling to README.

Fixed

  • Documentation formatting for co.Identity() examples.

  • Horovod check for newer pytorch lightning versions.

[1.1.2] - 2023-01-13

### Added

  • query_index argument to SingleOutputTransformerEncoderLayer.

Fixed

  • Residual centred residual and Delay auto_delay forward_step.

[1.1.1] - 2023-01-10

### Added

  • Support for GroupNorm and InstanceNorm

[1.1.0] - 2022-12-19

### Added

  • append function to co.Sequential.

  • Production-ready docstrings for public functions.

  • reduce_max to Reduce.

### Changed

  • Rename Unity to Identity to follow torch.nn.

  • Major overhaul of README, improving descriptions and adding benchmark.

  • Major overhaul of docs, improving descriptions and adding benchmark.

  • MHA warnings to only log once.

Removed

  • Unused parameters batch_first and bidirectional for RNN, GRU, and LSTM.

[1.0.4] - 2022-12-07

Fixed

  • co.Conditional onnx support for single-option config.

[1.0.3] - 2022-12-07

Fixed

  • co.Conditional onnx support.

[1.0.2] - 2022-12-06

Fixed

  • co.Conv onnx export for kernel_size=1.

[1.0.1] - 2022-12-02

Added

  • Ability to access onnx from root, i.e. co.onnx.

[1.0.0] - 2022-12-02

Added

  • ONNX compatibility to all library modules!

  • co.onnx.export function mirroring torch.onnx.export.

  • purely functional _forward_step function to all modules.

  • _state_shape and _dynamic_state_inds properties to modules.

  • Add about info to package root.

Changed

  • Change call_mode internally from enum to tensor.

  • Change internal state_indexes to tensors.

  • Change stride to tuple.

  • Change padding to tuple.

### Fixed

  • Fix assertion bug in co.Lambda.

### Removed

  • TensorPlaceholder in favour of None.

[0.17.1] - 2022-06-02

Added

  • Missing part on Continual Transformers in README.

Removed

  • Conv cpp impl.

[0.17.0] - 2022-05-12

Added

  • Citations for Continual Inference lib paper.

  • Docs.

  • Automatic conversion for RNN modules.

  • Continual Transformer modules, including:

    • RecyclingPositionalEncoding

    • RetroactiveMultiheadAttention

    • SingleOutputMultiheadAttention

    • SingleOutputTransformerEncoderLayer

    • RetroactiveTransformerEncoderLayer

    • TransformerEncoderLayerFactory

    • TransformerEncoder

[0.16.0] - 2022-04-04

### Added

  • “lagging” option for shrink in co.Delay and co.Residual.

  • co.RNN.

  • co.LSTM.

  • co.GRU.

Changed

  • phantom_padding renamed to residual_shrink.

[0.15.6] - 2022-03-18

Fixed

  • Missing cpp file in package.

[0.15.5] - 2022-03-05

Added

  • CoConv step impl in C++.

[0.15.4] - 2022-01-28

Fixed

  • FLOPs module registration compatibility with ptflops >=v0.6.8.

[0.15.3] - 2021-12-13

Added

  • Call-mode specific functions in co.Lambda

[0.15.2] - 2021-12-11

Added

  • Support for functor in co.Lambda

Removed

  • nn.LayerNorm from automatically convertible modules

[0.15.1] - 2021-12-10

Added

  • nn.LayerNorm to automatically convertible modules

[0.15.0] - 2021-10-29

Added

  • ParallelDispatch module.

  • Conditional predicate print in __repr__.

Fixed

  • Sequential padding computation.

  • Lambda __repr__ function prints.

Removed

  • CI testing for python v3.6.

[0.14.0] - 2021-09-20

Added

  • Added phantom_padding to Residual.

  • Added receptive_field property.

  • Added Reshape module.

Changed

  • Rename forward_shrink argument to auto_shrink in Delay.

  • Torch requirement to v1.9.

  • Replace Lambda unsqueeze_step with takes_time and new default to False.

Fixed

  • padding property in sequence.

  • delay property in sequence.

  • strict mode in load_state_dict.

Removed

  • Assertion error in BroadcastReduce for modules with different delays.

[0.13.0] - 2021-09-14

Added

  • Add forward_shrink option to Delay and Residual.

[0.12.0] - 2021-09-14

Added

  • Add Constant.

  • Add Zero.

  • Add One.

[0.11.4] - 2021-09-08

Fixed

  • co.ConvXd cuda compatibility.

[0.11.3] - 2021-09-08

Added

  • Add flatten_state_dict state variable.

Removed

  • Debug message for Convolutions with padding.

[0.11.2] - 2021-09-08

Fixed

  • call_mode for Linear.

[0.11.1] - 2021-09-06

Added

  • Add call_mode.

  • Add warm_up.

Changed

  • Container implementations to use __call__ with alternating call_modes. This change was necessary to properly trigger the torch hooks needed in ptflops.

Fixed

  • ptflops compatibility.

[0.11.0] - 2021-08-31

Added

  • co.Linear module.

  • Improved repr in co.Lambda.

  • Option to skip unsqueeze in co.Lambda.forward_step.

[0.10.0] - 2021-08-27

Changed

  • Renamed co.Parallel to co.BroadcastReduce.

Added

  • co.Broadcast module.

  • new co.Parallel module.

  • co.Reduce module.

  • Automatic inference of co.Broadcast.num_streams in co.Sequential.

[0.9.0] - 2021-08-26

Added

  • co.Lambda module.

  • co.Add module.

  • co.Multiply module.

  • co.Unity module.

  • co.Conditional module.

[0.8.1] - 2021-08-26

Fixed

  • Bug in forward_stepping.

  • Bug in clean_state.

[0.8.0] - 2021-08-24

Fixed

  • Bugs in forward_step(s) with update_state=False.

Changed

  • forward_steps interface to always include pad_end argument.

  • Name of “interface.py” to “module.py”.

  • Implementations of forward_step(s) to be consolidated in CoModule.

Removed

  • Padded interface.

[0.7.0] - 2021-08-24

Added

  • Independent state_dict and load_state_dict functions.

  • Added nonempty check for aggregation functions in Parallel.

  • update_state argument to all forward_step(s) methods.

  • Additional tests for edge-cases

Changed

  • Changed default pad_end value to False.

Fixed

  • Continual interface and conversion to support both class and module.

  • Replicate padding in co._ConvNd

[0.6.1] - 2021-08-23

Changed

  • co.Residual modules to be unnamed. This allows the module state dicts to be flattened.

[0.6.0] - 2021-08-23

Added

  • Flattened state dict export and loading via a flatten argument. This feature improves interoperability complex modules, that were not originally constructed with the co.Sequential and co.Parallel building blocks.

  • Context manager for triggering flattened state_dict export and loading.

[0.5.0] - 2021-08-20

Added

  • Support for zero-delay in co.Delay

  • Support for broadcasting in co.Parallel

  • Mul (hadamard product) aggregation in co.Parallel

  • Example of Squeeze and Excitation block

Changed

  • co._PoolNd attribute naming: “temporal_*” removed as prefix for kernel_size, stride, dilation, and padding.

[0.4.0] - 2021-08-19

Added

  • co.Delay handling for padding.

  • Handling of initialization and strides in containers

Changed

  • co.Conv build_from behavior to not change dilation and stride. Argument overload supported instead.

  • pad_start and pad_end args to convolution and pooling modules forward_steps.

  • Behavior of modules while they initialize. Now, a TensorPlaceholder is passed for initializing steps.

Removed

  • Automatic unsqueeze in pooling.

[0.3.1] - 2021-08-18

Added

  • Support for dropout.

[0.3.0] - 2021-08-18

Added

  • Support for dilation and stride in pooling.

Changed

  • Pooling API to match torch.nn better.

  • _ConvCoNd.forward_steps doesn’t invoke clean_state anymore.

[0.2.2] - 2021-08-17

Added

  • Automatic conversion of batch normalization and activation functions.

Fixed

  • Separate dilation and stride in pool.

Changed

  • Conv forward to use temporal padding like (like nn.Conv).

Removed

  • co.BatchNorm2d

[0.2.1] - 2021-08-17

Changed

  • Renamed unsqueezed to forward_stepping.

Removed

  • Unused utility Zeros

[0.2.0] - 2021-08-16

Changed

  • Naming to match torch.nn. This lets the continual modules be used as drop-in replacements for torch.nn modules.

  • Renamed forward_regular_unrolled to forward, forward_regular to forward_steps, and forward for forward_step.

  • Renamed from_regular to build_from.

  • Renamed continual to unsqueezed.

Added

  • Sequential wrapper for sequential application of modules

  • Parallel wrapper for parallel application and aggregation of inputs

  • Residual wrapper for adding a unity residual to a module

  • continual conversion function

  • register function for 3rd party modules to register their conversion

  • Additional tests

[0.1.2] - 2021-08-1

Added

  • Pooling modules: MaxPool1d, AvgPool3d, MaxPool3d, AdaptiveAvgPool3d, AdaptiveMaxPool3d.

[0.1.1] - 2021-08-10

Added

  • Updated README.

[0.1.0] - 2021-08-10

Added

  • Initial publicly available implementation of the library.

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