import pycutlass
from pycutlass import *
from pycutlass.test import *
import unittest

from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc


@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class GemmBF16TensorOpSm80(unittest.TestCase):
    def SM80_Device_Gemm_bf16n_bf16n_f32t_tensor_op_f32_64x128x64_32x64x64(self):
        math_inst = MathInstruction(
            instruction_shape=[16, 8, 16],
            element_a=cutlass.bfloat16, element_b=cutlass.bfloat16,
            element_accumulator=cutlass.float32, opcode_class=cutlass.OpClass.TensorOp,
            math_operation=MathOperation.multiply_add
        )

        tile_description = TileDescription(
            threadblock_shape=[64, 128, 64],
            stages=4, warp_count=[2, 2, 1],
            math_instruction=math_inst
        )

        A = TensorDescription(
            element=cutlass.bfloat16, layout=cutlass.ColumnMajor,
            alignment=8
        )
        B = TensorDescription(
            element=cutlass.bfloat16, layout=cutlass.ColumnMajor,
            alignment=8
        )
        C = TensorDescription(
            element=cutlass.float32, layout=cutlass.RowMajor,
            alignment=4
        )

        epilogue_functor = LinearCombination(
            C.element, C.alignment, 
            math_inst.element_accumulator, cutlass.float32)
        
        swizzling_functor = cutlass.IdentitySwizzle1

        operation = GemmOperationUniversal(
            arch=80, tile_description=tile_description,
            A=A, B=B, C=C, 
            epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
        )

        self.assertTrue(test_all_gemm(operation, "universal"))
    
    def test_SM80_Device_Gemm_bf16t_bf16t_bf16t_tensor_op_f32_128x256x64_64x64x64(self):
        math_inst = MathInstruction(
            instruction_shape=[16, 8, 16],
            element_a=cutlass.bfloat16, element_b=cutlass.bfloat16,
            element_accumulator=cutlass.float32, opcode_class=cutlass.OpClass.TensorOp,
            math_operation=MathOperation.multiply_add
        )

        tile_description = TileDescription(
            threadblock_shape=[64, 128, 32],
            stages=6, warp_count=[2, 2, 1],
            math_instruction=math_inst
        )

        A = TensorDescription(
            element=cutlass.bfloat16, layout=cutlass.RowMajor,
            alignment=8
        )
        B = TensorDescription(
            element=cutlass.bfloat16, layout=cutlass.RowMajor,
            alignment=8
        )
        C = TensorDescription(
            element=cutlass.bfloat16, layout=cutlass.RowMajor,
            alignment=8
        )

        epilogue_functor = LinearCombination(
            C.element, C.alignment, 
            math_inst.element_accumulator, cutlass.float32)
        
        swizzling_functor = cutlass.IdentitySwizzle1

        operation = GemmOperationUniversal(
            arch=80, tile_description=tile_description,
            A=A, B=B, C=C, 
            epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
        )

        self.assertTrue(test_all_gemm(operation, "multistage"))

if __name__ == '__main__':
    pycutlass.get_memory_pool(2**24, 2**24)
    unittest.main()
