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904bbdae65
* 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
Installation
From the candle-pyo3 directory, enable a virtual env where you will want the
candle package to be installed then run.
maturin develop -r
python test.py
Generating Stub Files for Type Hinting
For type hinting support, the candle-pyo3 package requires *.pyi files. You can automatically generate these files using the stub.py script.
Steps:
- Install the package using
maturin. - Generate the stub files by running:
python stub.py
Validation:
To ensure that the stub files match the current implementation, execute:
python stub.py --check