+ ܳjvT^RIHt!RR]4t!RR]4t!RR]4tR#) )Optimizer1Statec6aa]tRt^toRV3RlltRtVtV;t#)Adagradc  <RV8:g\RV 24hRV8:g\RV 24hRV8:g\RV 24hVR8wd \R4hVR8wd \R4h\S V` RVVR VVVVV 4 R#) aM Base Adagrad optimizer. Arguments: params (`torch.tensor`): The input parameters to optimize. lr (`float`, defaults to 1e-2): The learning rate. lr_decay (`int`, defaults to 0): The learning rate decay. weight_decay (`float`, defaults to 0.0): The weight decay value for the optimizer. initial_accumulator_value (`int`, defaults to 0): The initial momemtum values. eps (`float`, defaults to 1e-10): The epsilon value prevents division by zero in the optimizer. optim_bits (`int`, defaults to 32): The number of bits of the optimizer state. args (`object`, defaults to `None`): An object with additional arguments. min_8bit_size (`int`, defaults to 4096): The minimum number of elements of the parameter tensors for 8-bit optimization. Invalid learning rate: Invalid weight_decay value: Invalid epsilon value: /Initial accumulator value != 0.0 not supported!Lr Decay != 0.0 not supported!adagradNrr ValueErrorsuper__init__ selfparamslrlr_decay weight_decayinitial_accumulator_valueeps optim_bitsargs min_8bit_size __class__s &&&&&&&&&&[/home/luca/screen-checking/.venv/lib/python3.14/site-packages/bitsandbytes/optim/adagrad.pyrAdagrad.__init__ sFby6rd;< <l";L>JK Kcz6se<= = $ +NO O s?=> >           {Gz?rrr绽|= N__name__ __module__ __qualname____firstlineno__r__static_attributes____classdictcell__ __classcell__r __classdict__s@@rrr7 7 r!rc6aa]tRt^CtoRV3RlltRtVtV;t#) Adagrad8bitc  <RV8:g\RV 24hRV8:g\RV 24hRV8:g\RV 24hVR8wd \R4hVR8wd \R4hV^8wd \R4h\S V` RVVR VV^VV 4 R #) a 8-bit Adagrad optimizer. Arguments: params (`torch.tensor`): The input parameters to optimize. lr (`float`, defaults to 1e-2): The learning rate. lr_decay (`int`, defaults to 0): The learning rate decay. weight_decay (`float`, defaults to 0.0): The weight decay value for the optimizer. initial_accumulator_value (`int`, defaults to 0): The initial momemtum values. eps (`float`, defaults to 1e-10): The epsilon value prevents division by zero in the optimizer. optim_bits (`int`, defaults to 8): The number of bits of the optimizer state. Note: This parameter is not used in Adagrad8bit as it always uses 8-bit optimization. args (`object`, defaults to `None`): An object with additional arguments. min_8bit_size (`int`, defaults to 4096): The minimum number of elements of the parameter tensors for 8-bit optimization. rrr r r r zHAdagrad8bit only supports optim_bits=8 (default value for compatibility)r Nrrrs &&&&&&&&&&rrAdagrad8bit.__init__DsHby6rd;< <l";L>JK Kcz6se<= = $ +NO O s?=> > ?gh h          r!r")r$rrrr%Nr'r(r0s@@rr4r4Cs< < r!r4c6aa]tRt^toRV3RlltRtVtV;t#) Adagrad32bitc  <RV8:g\RV 24hRV8:g\RV 24hRV8:g\RV 24hVR8wd \R4hVR8wd \R4h\S V` RVVR VV^ VV 4 R#) aO 32-bit Adagrad optimizer. Arguments: params (`torch.tensor`): The input parameters to optimize. lr (`float`, defaults to 1e-2): The learning rate. lr_decay (`int`, defaults to 0): The learning rate decay. weight_decay (`float`, defaults to 0.0): The weight decay value for the optimizer. initial_accumulator_value (`int`, defaults to 0): The initial momemtum values. eps (`float`, defaults to 1e-10): The epsilon value prevents division by zero in the optimizer. optim_bits (`int`, defaults to 32): The number of bits of the optimizer state. args (`object`, defaults to `None`): An object with additional arguments. min_8bit_size (`int`, defaults to 4096): The minimum number of elements of the parameter tensors for 8-bit optimization. rrr r r r r Nrrrs &&&&&&&&&&rrAdagrad32bit.__init__sFby6rd;< <l";L>JK Kcz6se<= = $ +NO O s?=> >           r!r"r#r(r0s@@rr9r9r2r!r9N)bitsandbytes.optim.optimizerrrr4r9r"r!rr=s0 98 o8 v= /= @8 ?8 r!