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Make the Python Wrapper more Hackable and simplify Quantization (#1010)
* 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
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{
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"[python]": {
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"editor.defaultFormatter": "ms-python.black-formatter"
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},
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"python.formatting.provider": "none",
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"python.testing.pytestArgs": [
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"candle-pyo3"
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],
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"python.testing.unittestEnabled": false,
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"python.testing.pytestEnabled": true
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}
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