* Add QuantizationBackend, QTensorOps and QTensor
* Refactor QTensorOps as part of Backend trait
* Add tensor dequantize, QFloat dtype and default affine/symmetric quant
* Add ndarray default quantization implementation
* Fix clippy
* Add rayon parallel iter
* Add quantization operations to book
* Add q_shape and q_device ops to avoid converting the tensor just to get attributes
* Implement autodiff grad ops
* Mark autodiff todo for QAT
* Remove note
* Add q_inner and q_from_inner
* 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
* #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>
* Add training report summary
* Fix LossMetric batch size state
* Add NumericEntry de/serialize
* Fix clippy suggestion
* Compact recorder does not use compression (anymore)
* Add learner summary expected results tests
* Add summary to learner builder and automatically display in fit
- Add LearnerSummaryConfig
- Keep track of summary metrics names
- Add model field when displaying from learner.fit()
* Add multilabel classification dataset
- Add MultiLabel annotation support
- Refactor de/serialize annotation with AnnotationRaw
- Add ImageFolderDataset::with_items methods
* Fix custom-image-classification example deps
* Add image_folder_dataset_multilabel test
* Do not change class names order when provided
* Add hamming score and multi-label classification output
* Add new_classification_with_items test
* Fix clippy suggestions
* Implement default trait for hamming score
* Remove de/serialization and use AnnotationRaw as type
* Fix clippy
* Fix metric backend phantom data
* refactor execute_dynamic into Execution
* minor change
* extension cfg
* jitkernel and sourcekernel
* add todo statement
* cleanup and docs
* update book
* fix server dependancy on compiler
* refactor into shader information
* refactor to compile shader once
* clippy
* clippy
* clippy
* fix doc
* fix doc
* fmt
* rename feature flag
* refactor
* All broked
* compile at the right time
* todo done
* all dynamic
* all dynamic in template too
* fmt
* fix ci
---------
Co-authored-by: nathaniel <nathaniel.simard.42@gmail.com>
* Fix python main entrypoint in book example
* Remove candle windows safeguards (#1178)
* Bump candle-core from 0.3.3 to 0.4.1
* Remove windows current known issue
Combined PRs ➡️📦⬅️✅ The following pull requests have been successfully combined on this PR:
Closes Bump thiserror from 1.0.56 to 1.0.57 #1293 Bump thiserror from 1.0.56 to 1.0.57
Closes Bump tokenizers from 0.15.1 to 0.15.2 #1292 Bump tokenizers from 0.15.1 to 0.15.2
Closes Bump bytemuck from 1.14.1 to 1.14.3 #1291 Bump bytemuck from 1.14.1 to 1.14.3
Closes Bump indicatif from 0.17.7 to 0.17.8 #1290 Bump indicatif from 0.17.7 to 0.17.8
Nathaniel Simard