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Mojo function

matmul_Q4_K

def matmul_Q4_K[elementwise_lambda_fn: Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None] = None](a_tt: TileTensor[DType.float32, Storage=a_tt.Storage, linear_idx_type=a_tt.linear_idx_type], b_tt: TileTensor[DType.uint8, Storage=b_tt.Storage, linear_idx_type=b_tt.linear_idx_type], c_tt: TileTensor[DType.float32, Storage=c_tt.Storage, linear_idx_type=c_tt.linear_idx_type], ctx: Optional[DeviceContext] = None)

Computes a matrix multiplication with Q4_K block-quantized weights.

Dispatches to an x86 or ARM NEON implementation at compile time; other targets fail to compile.

Parameters:

elementwise_lambda_fn (Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None]): Optional epilogue applied to each output element.

Args:

a_tt (TileTensor[DType.float32, Storage=a_tt.Storage, linear_idx_type=a_tt.linear_idx_type]): Left-hand operand tensor in float32.
b_tt (TileTensor[DType.uint8, Storage=b_tt.Storage, linear_idx_type=b_tt.linear_idx_type]): Right-hand operand tensor holding Q4_K quantized uint8 weights.
c_tt (TileTensor[DType.float32, Storage=c_tt.Storage, linear_idx_type=c_tt.linear_idx_type]): Output tensor in float32.
ctx (Optional[DeviceContext]): Optional device context for parallel execution.