f3a4f3db76
PyO3: Add optional candle.onnx module ( #1282 )
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* Start onnx integration
* Merge remote-tracking branch 'upstream/main' into feat/pyo3-onnx
* Implement ONNXModel
* `fmt`
* add `onnx` flag to python ci
* Pin `protoc` to `25.0`
* Setup `protoc` in wheel builds
* Build wheels with `onnx`
* Install `protoc` in manylinux containers
* `apt` -> `yum`
* Download `protoc` via bash script
* Back to `manylinux: auto`
* Disable `onnx` builds for linux
2023-11-08 06:37:50 +01:00
c05c0a8213
PyO3: Add equal and __richcmp__ to candle.Tensor ( #1099 )
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* add `equal` to tensor
* add `__richcmp__` support for tensors and scalars
* typo
* more typos
* Add `abs` + `candle.testing`
* remove duplicated `broadcast_shape_binary_op`
* `candle.i16` => `candle.i64`
* `tensor.nelements` -> `tensor.nelement`
* Cleanup `abs`
2023-10-30 15:17:28 +00:00
174b208052
PyO3: Better shape handling ( #1143 )
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* Negative and `*args` shape handling
* Rename to `PyShapeWithHole` + validate that only one hole exists
* Regenerate stubs
---------
Co-authored-by: Laurent Mazare <laurent.mazare@gmail.com >
2023-10-29 15:41:44 +00:00
6a446d9d73
convert pytorch's tensor in Python API ( #1172 )
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* convert pytorch's tensor
* separate tests for convert pytorch tensor
2023-10-25 19:39:14 +01:00
eae94a451b
PyO3: Add mkl support ( #1159 )
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* Add `mkl` support
* Set `mkl` path on linux
2023-10-23 20:10:59 +01:00
cfb423ab76
PyO3: Add CI ( #1135 )
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* Add PyO3 ci
* Update python.yml
* Format `bert.py`
2023-10-20 19:05:14 +01:00
6684b7127a
PyO3: Add pytorch like .to() operator to candle.Tensor ( #1100 )
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* add `.to()` operator
* Only allow each value to be provided once via `args` or `kwargs`
2023-10-19 21:46:21 +01:00
f9e93f5b69
Extend stub.py to accept external typehinting ( #1102 )
2023-10-17 11:07:26 +01:00
2c110ac7d9
Add the pooling operators to the pyo3 layer. ( #1086 )
2023-10-13 20:18:10 +01:00
75989fc3b7
Use an attention mask in the e5 padding case. ( #1085 )
2023-10-13 18:53:40 +01:00
904bbdae65
Make the Python Wrapper more Hackable and simplify Quantization ( #1010 )
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* Some first `Module` implementations
* Add `state_dict` and `load_state_dict` functionality
* Move modules around and create `candle.nn.Linear`
* Add `nn.Embedding` and `nn.LayerNorm`
* Add BERT implementation
* Batch q-matmul
* Automatically dequantize `QTensors` if a `Tensor` is expected
* Add Module `.to()`, `.cuda()`, `cpu()` and `.type()` functionality
* Unittests for `Module`, `Tensor` and `candle.utils`
* Add `pytorch` like slicing to `Tensor`
* Cleanup and BERT fixes
* `black` formatting + unit-test for `nn.Linear`
* Refactor slicing implementation
2023-10-06 19:01:07 +01:00
03e194123d
Add return types to *.pyi stubs ( #880 )
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* Start generating return types
* Finish tensor type hinting
* Add `save_gguf` to `utils`
* Typehint `quant-llama.py`
2023-09-17 22:11:01 +01:00
8658df3485
Generate *.pyi stubs for PyO3 wrapper ( #870 )
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* Begin to generate typehints.
* generate correct stubs
* Correctly include stubs
* Add comments and typhints to static functions
* ensure candle-pyo3 directory
* Make `llama.rope.freq_base` optional
* `fmt`
2023-09-16 17:23:38 +01:00
