* Made compatible with thumbv6m-none-eabi
* Added example of no_std on rp2040
* Added documentation on usage in no_std
* Rename rp2040 example and add README.md
* working version
* cleanup
* wip
* working version of gather
* testsetsetser
* Revert "testsetsetser"
This reverts commit f37b329697.
* Reapply "testsetsetser"
This reverts commit f8ada0044e.
* Revert "testsetsetser"
This reverts commit f37b329697.
* Revert "working version of gather"
This reverts commit f5047c27c8.
* Revert "wip"
This reverts commit abaaa2dd55.
* Revert "Merge branch 'main' into index-cpa-to-cubecl"
This reverts commit 05bed8ea74, reversing
changes made to 94954fc32c.
* Revert "cleanup"
This reverts commit 94954fc32c.
* Revert "working version"
This reverts commit a06933f029.
* gather test
* fix
* fix clippy
* cleanup
* Add Hard Sigmoid activation function
* Add ONNX import conversion for HardSigmoid
* Update supported operators list
* Update book
* Make test comparison approximate to eliminate precision issues
* Add burn-candle test
* Fix name in E2E test generator
* renaming repeat to repeat_dim
* implementing repeat function
* renaming repeat files to repeat_dim
* renaming part 2
* renaming part 3
* renaming part 4
* renaming part 5
* adding test file
* adding unit test
* adding rust book documentation
* adding function args doc
* fixing tests
* changing repeat api to match pytorch equivalent
* fixing clippy error
* Move QuantizationScheme to burn-tensor
* Refactor QuantizedTensorPrimitive to include the quantization strategy
* Fix QFloat tensor data display
* Refactor quantization methods to use scheme and qparams (on backend device)
* Fix clippy
* Fix fmt
* Add qtensor primitive tests
* Implement 3D and transposed 3D convolutions.
* Merge changes from onnx-ir #1921 pr
---------
Co-authored-by: Dilshod Tadjibaev <939125+antimora@users.noreply.github.com>
* Move distribution to module
* Add new TensorData with serialization support
* Implement display and from for TensorData
* Add missing Cargo.lock
* Add missing bytemuck feature
* Add zeros, ones, full and random TensorData methods
* Refactor Data -> TensorData usage
* Fix tests
Since TensorData is not generic over the element type anymore no type inference can be done by the compiler. We must explicitly cast the expected results to the expected backend type.
* Remove commented line
* Fix import
* Add record-backward-compat
* Remove dim const generic from TensorData
* Support NestedValue de/serialization with TensorData
* Fix burn-jit tests
* Remove eprinln
* Refactor onnx import to use TensorData
* Fix tch from_data
* Fix nested value serialization for u8
* Fix missing import
* Fix reduce min onnx test
* Fix deprecated attribute
* Remove shape getter
* Remove strict assert in tests
* Add tensor data as_bytes
* Add tensor check for rank mismatch
* Fix typo (dimensions plural)
* Fix error message
* Update book examples with from_data and fix Display impl for TensorData
* Add deprecation note
* Updated documentation for unfold4d
Added links between the struct and the config. Added a link to the related burn_tensor function in the documentation for the forward function.
* Changing nn relu module documentation to functional api
Removing the formula for relu from the module API to the functional API,
citing a paper relevant to relu
and mentionning the functional API in the module API
* Linking gelu module API documentation to functional API documentation
* Linear module : adding documentation
Adding documentation to the Linear module
mentionning that LinearConfig struct
should be used when creating a Linear Layer
Also adding links to the documentation that points people toward
the right path
* Updated documentation for dropout
Added links between the struct and the config. Added a link to the struct in the forward function for more info.
* embedding + swiglu
* RotaryEncodying : adding documentation
Adding documentation stating the RotaryEncoding should be created using a RotaryEncodingConfig
* prelu: adding documentation
Adding documentation to the prelu module:
- Linking forward function documentation to the functional API
- Citing the first paper to mention prelu
- Adding documentation saying that prelu layer should be created using PReluConfig
* pos_encoding: adding documentation
* Updated documentation for mha
Added links for more info. Added shape info at some places.
* docs: Add documentation for Gru module
Provide documentation for the Gru module, including its configuration and usage. Include a link to the paper that introduced the Gated Recurrent Unit (GRU) and specify that the module should be created using GruConfig. Also, mention that the forward function returns a state tensor with specific dimensions.
* burn-core-nn-transformers: adding documentation
Adding documentation:
- Says to use config to create the layers
- Add mathematical formula to the pwff forward pass
- Add citation in the pwff to the "Attention is all you need" paper
* Updated documentation: ConvTranspose1d and ConvTranspose2d
* docs: Add documentation for Lstm and BiLstm modules
Provide documentation for the Lstm and BiLstm modules, including their configurations and usage. Include links to the papers that introduced Long Short-Term Memory (LSTM) and Bidirectional LSTM. Specify that the modules should be created using LstmConfig and BiLstmConfig respectively.
* docs: Update documentation for ConvTranspose1d and ConvTranspose2d modules
* loss: Adding documenntation to the loss layers
Adding documentation stating to use the config to create the layer
* chore: Refactor Conv1d module imports and update documentation
* docs: Add documentation for AdaptiveAvgPool1d and AdaptiveAvgPool2d modules
Added references to the burn_tensor associated functions. Added links between the struct and the config.
* Refactor Conv1d module imports and update documentation
* chore: Refactor Conv2d module imports and update documentation
* Add documentation for AvgPool1d and AvgPool2d modules
Added references to the burn_tensor associated functions. Added links between the struct and the config.
* Add documentation for MaxPool1d and MaxPool2d modules
Added references to the burn_tensor associated functions. Added links between the struct and the config.
* Add documentation for leaky_relu and removed Config generic
Added references to the burn_tensor associated functions. Added links between the struct and the config. Removed the backend generic from the config since it's not needed (might be a breaking change).
* refactor: Update BatchNormConfig initialization and add documentation.
* Added link to config in embedding struct documentation
* refactor: Update GroupNormConfig initialization and add documentation
* refactor: Update InstanceNormConfig initialization and add documentation
* feat: Update LayerNormConfig initialization and add documentation
* refactor: Update RmsNormConfig initialization and add documentation
* fixed: removed #derive accidentally
* Added missing backticks in pools' shapes
* Format nn doc
* Make config fields public in nn modules
* Update import statements in nn modules
Changed burn_tensor imports to crate::tensor
* Update import statements in nn modules' tests
Changed burn_tensor imports to crate::tensor
* breaking change refactor: Update GroupNormConfig and InstanceNormConfig initialization
* Make SwiGlu fields public
* grammar
* slashes
* input tensors grouping
* copy-pasta mistake
* a not an >:I
* Capitalization
* better desc
* math 'n ticks
* group_norm functional implementation
* removed the ... struct
* decoder typo
* fmt
* referring to private fn in docs
---------
Co-authored-by: Thierry Cantin-Demers <piertcd@gmail.com>
Co-authored-by: mepatrick73 <pameu17@ulaval.ca>
* #1747
Upgrade Rust dependencies
* Revert upgrade for tch
The update of tch on windows gives an error:
INTEL MKL ERROR: The specified module could not be found. mkl_vml_avx2.1.dll.
Intel MKL FATAL ERROR: cannot load mkl_vml_avx2.1.dll or mkl_vml_def.1.dll.
* Keep only .cargo/config.toml file which works with rust > 1.75
---------
Co-authored-by: Sylvain Benner <sylvain@benner.online>
* resolve conflict
* move `gate_product` to `GateController`
* BiLstm needs to use its own initializer when init
* resolve conflicts
* add some comments
* improve doc
* correct the description of GateController
* fix fmt
* add `LstmState`
* add test for state
* set batch 2 in bilstm test
* resolve conflict
* fix
* fix doc
* change the batch size back to 1
* change the batch size back to 1
* modify docstring; delete dead comment
Guillaume Lagrange