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# test/unit/conv/device/conv2d_wgrad_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.cu
import cutlass.backend
from cutlass.backend import *
from cutlass.backend.test import *
from cutlass.backend.utils.device import device_cc
import unittest


@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class Conv2dWgradImplicitGemmTF32nhwcTF32nhwcTF32nhwcTensorOpF32SM80(unittest.TestCase):
    def test_SM80_Device_Conv2d_Wgrad_Optimized_ImplicitGemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32(self):
        math_inst = MathInstruction(
            instruction_shape=[16, 8, 8],
            element_a=cutlass_bindings.float32, element_b=cutlass_bindings.float32,
            element_accumulator=cutlass_bindings.float32, opcode_class=cutlass_bindings.OpClass.TensorOp,
            math_operation=MathOperation.multiply_add
        )

        A = TensorDescription(
            element=math_inst.element_a, 
            layout=cutlass_bindings.TensorNHWC,
            alignment=4)
        B = TensorDescription(
            element=math_inst.element_b, 
            layout=cutlass_bindings.TensorNHWC, 
            alignment=4)
        C = TensorDescription(
            element=cutlass_bindings.float32,
            layout=cutlass_bindings.TensorNHWC, 
            alignment=8)

        tile_description = TileDescription(
            threadblock_shape=[128, 128, 16], stages=3, 
            warp_count=[2, 2, 1],
            math_instruction=math_inst
        )

        epilogue_functor = LinearCombination(
            C.element, C.alignment, 
            math_inst.element_accumulator, cutlass_bindings.float32)

        operation = Conv2dOperation(
            conv_kind=cutlass_bindings.conv.Operator.wgrad, iterator_algorithm=cutlass_bindings.conv.IteratorAlgorithm.optimized,
            arch=80, tile_description=tile_description, A=A, B=B, C=C, 
            stride_support=StrideSupport.Strided,
            epilogue_functor=epilogue_functor,
            swizzling_functor=cutlass_bindings.IdentitySwizzle1
        )
        
        self.assertTrue(test_all_conv2d(operation))
    
    def test_SM80_Device_Conv2d_Wgrad_Optimized_ImplicitGemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_align1(self):
        math_inst = MathInstruction(
            instruction_shape=[16, 8, 8],
            element_a=cutlass_bindings.float32, element_b=cutlass_bindings.float32,
            element_accumulator=cutlass_bindings.float32, opcode_class=cutlass_bindings.OpClass.TensorOp,
            math_operation=MathOperation.multiply_add
        )

        A = TensorDescription(
            element=math_inst.element_a, 
            layout=cutlass_bindings.TensorNHWC,
            alignment=1)
        B = TensorDescription(
            element=math_inst.element_b, 
            layout=cutlass_bindings.TensorNHWC, 
            alignment=1)
        C = TensorDescription(
            element=cutlass_bindings.float32,
            layout=cutlass_bindings.TensorNHWC, 
            alignment=4)

        tile_description = TileDescription(
            threadblock_shape=[128, 128, 32], stages=3, 
            warp_count=[2, 2, 1],
            math_instruction=math_inst
        )

        epilogue_functor = LinearCombination(
            C.element, C.alignment, 
            math_inst.element_accumulator, cutlass_bindings.float32)

        operation = Conv2dOperation(
            conv_kind=cutlass_bindings.conv.Operator.wgrad, iterator_algorithm=cutlass_bindings.conv.IteratorAlgorithm.optimized,
            arch=80, tile_description=tile_description, A=A, B=B, C=C, 
            stride_support=StrideSupport.Strided,
            epilogue_functor=epilogue_functor,
            swizzling_functor=cutlass_bindings.IdentitySwizzle1
        )
        
        problem_sizes = [
            cutlass_bindings.conv.Conv2dProblemSize(
                cutlass_bindings.Tensor4DCoord(1, 8, 8, 1),
                cutlass_bindings.Tensor4DCoord(1, 3, 3, 1),
                cutlass_bindings.Tensor4DCoord(1, 1, 1, 1),
                cutlass_bindings.MatrixCoord(1, 1),
                cutlass_bindings.MatrixCoord(1, 1),
                cutlass_bindings.conv.Mode.cross_correlation,
                1, 1
            ),
        ]
        
        self.assertTrue(test_all_conv2d(operation, problem_sizes))
    
if __name__ == '__main__':
    cutlass.backend.get_memory_pool(2**26, 2**26)
    unittest.main()
