Set dtype policy for uint8 #19327
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Set dtype policy for uint8 #19327
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…nse` Add qlora-like technique to `quantized_call` in `Dense` Update `save_own_variables` and `load_own_variables` Update `benchmark.py` update version string. Set dtype policy for uint8 (keras-team#19327) * Set Quantization policy for uint8 to float * Add uint8 to dtype_policies Use Value dim shape for Attention compute_output_shape (keras-team#19284) * Use Value dim shape for Attention compute_output_shape * Fix attention layer compute output shape * fix format * check compute_output_shape with output Update `quantized_call` in `EinsumDense` to support training with quantized weights
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Fixes issue for KerasCV where we use
uint8for dtype. Set toFloatDtypePolicyto get past the quantization dtype policy error. Tested locally with KerasCV to verify the fix.