o ý°“iXã@s|ddlZddlmZmZmZgd¢Zdefdd„Zdedejdejfd d „Zd ejdejfd d „Z d ejdejfdd„Z dS)éN)Ú BFLOAT16_DATAÚ FP4_E2M1_DATAÚQuantizationArgs)Úmaybe_convert_from_mxfp4_expÚgenerate_mxfp4_scalesÚround_to_power_2Úshould_generatre_mxfp4_scalesÚargscCs|jdko|jdko|jdkS)NéÚfloaté )Únum_bitsÚtypeÚ group_size)r ©rúe/home/ubuntu/.local/lib/python3.10/site-packages/compressed_tensors/quantization/utils/mxfp4_utils.pyr!srÚscaleÚreturncCs<|j}t|ƒr| tj¡d}d| tj¡}| |¡S|S)a Converts mxfp4 scales. Scales are powers of 2, with the exponents stored in uint8. Converts to dense dtype so that they can be applied to the weights and activations during QDQ :param scale: uint8 exponent scale :param dtype: dense dtype ég@)ÚdtyperÚtoÚtorchÚint32r )r rÚoriginal_dtypeÚ scale_exprrrr%s   rÚxcCst|jtjksJ‚| tj¡ tj¡}dtjt jd>}dtj d>dtj>}t  |||¡}| tj¡ tj¡S)a¹ Round values to the closest power of 2. This is done by masking the values with BFLOAT16_SIGN_EXPONENT_MASK which essentially removes the mantissa and keeps the exponent. i.e the closest power of 2 for the input_value. E.g: 0.0825 = 1.32 (mantissa) x 2**-4 (exponent) 0.0825 ==> -4 (exponent) + 127 = 123 = 01111011 (8 bits for bfloat16) 0.0825 ==> 0.32 (mantissa) = 0101001 (7 bits for bfloat16) 0.0825 == 0b01111011_0101001 (bfloat16) 0b01111011_0101001 & 111111111_0000000 == 0b01111011_0000000 Keep the exponent + sign bit to give you the closest power of 2, 0.0625 :param x: tensor to round to closest power of 2 é) rrÚbfloat16ÚviewÚuint16rrrÚmantissarÚexponentÚ bitwise_and)rÚBFLOAT16_VAL_TO_ADDÚBFLOAT16_SIGN_EXPONENT_MASKÚblock_max_uintrrrr8sþÿrcCs t|ƒ}dt t |¡¡dS)a Generate mxfp4 scales. The scales require the following steps 1. Round to the closest power of 2 2. Convert to exponent Called when calculating qparams using observers. :param x: tensor to round to closest power of 2 :returns scales as exponents ré)rrÚfloorÚlog2)rÚ scale_power_2rrrrZs r) rÚ*compressed_tensors.quantization.quant_argsrrrÚ__all__rÚTensorrrrrrrrÚs ÿÿ þ"