262 lines
9.3 KiB
Python
262 lines
9.3 KiB
Python
#################################################################################################
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#
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# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: BSD-3-Clause
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# 3. Neither the name of the copyright holder nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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#################################################################################################
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import pycutlass
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from pycutlass import *
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from pycutlass.epilogue import LinearCombinationClamp
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from pycutlass.test import *
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import unittest
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from pycutlass.test.gemm_testbed import test_all_gemm
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from pycutlass.utils.device import device_cc
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@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
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class GemmS8TensorOpF32Sm80(unittest.TestCase):
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def test_SM80_Device_Gemm_s8t_s8n_s8t_tensor_op_s32_64x64x64_32x32x64(self):
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math_inst = MathInstruction(
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instruction_shape=[16, 8, 32],
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element_a=cutlass.int8, element_b=cutlass.int8,
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element_accumulator=cutlass.int32, opcode_class=cutlass.OpClass.TensorOp,
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math_operation=MathOperation.multiply_add_saturate
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)
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tile_description = TileDescription(
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threadblock_shape=[64, 64, 64],
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stages=6, warp_count=[2, 2, 1],
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math_instruction=math_inst
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)
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A = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajorInterleaved32,
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alignment=16
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)
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B = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajorInterleaved32,
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alignment=16
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)
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C = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajorInterleaved32,
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alignment=8
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)
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epilogue_functor = FastLinearCombinationClamp(
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C.element, C.alignment
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)
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swizzling_functor = cutlass.IdentitySwizzle1
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operation = GemmOperationUniversal(
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arch=80, tile_description=tile_description,
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A=A, B=B, C=C,
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epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
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)
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self.assertTrue(test_all_gemm(operation, "interleaved"))
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def test_SM80_Device_Gemm_s8t_s8n_s8t_tensor_op_s32_256x128x128_64x64x128(self):
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math_inst = MathInstruction(
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instruction_shape=[16, 8, 32],
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element_a=cutlass.int8, element_b=cutlass.int8,
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element_accumulator=cutlass.int32, opcode_class=cutlass.OpClass.TensorOp,
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math_operation=MathOperation.multiply_add
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)
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tile_description = TileDescription(
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threadblock_shape=[128, 128, 128],
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stages=3, warp_count=[2, 2, 1],
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math_instruction=math_inst
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)
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A = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajor,
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alignment=16
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)
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B = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajor,
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alignment=16
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)
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C = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajor,
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alignment=16
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)
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epilogue_functor = FastLinearCombinationClamp(
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C.element, C.alignment
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)
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swizzling_functor = cutlass.IdentitySwizzle1
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operation = GemmOperationUniversal(
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arch=80, tile_description=tile_description,
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A=A, B=B, C=C,
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epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
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)
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self.assertTrue(test_all_gemm(operation, "multistage"))
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def test_SM80_Device_Gemm_s8t_s8n_s8n_tensor_op_s32_128x128x128_64x64x128(self):
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math_inst = MathInstruction(
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instruction_shape=[16, 8, 32],
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element_a=cutlass.int8, element_b=cutlass.int8,
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element_accumulator=cutlass.int32, opcode_class=cutlass.OpClass.TensorOp,
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math_operation=MathOperation.multiply_add
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)
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tile_description = TileDescription(
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threadblock_shape=[128, 128, 128],
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stages=3, warp_count=[2, 2, 1],
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math_instruction=math_inst
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)
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A = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajor,
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alignment=16
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)
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B = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajor,
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alignment=16
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)
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C = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajor,
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alignment=16
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)
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epilogue_functor = FastLinearCombinationClamp(
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C.element, C.alignment
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)
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swizzling_functor = cutlass.IdentitySwizzle1
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operation = GemmOperationUniversal(
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arch=80, tile_description=tile_description,
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A=A, B=B, C=C,
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epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
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)
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self.assertTrue(test_all_gemm(operation, "multistage"))
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def test_SM80_Device_Gemm_s8t_s8n_s32n_tensor_op_s32_128x128x128_64x64x128(self):
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math_inst = MathInstruction(
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instruction_shape=[16, 8, 32],
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element_a=cutlass.int8, element_b=cutlass.int8,
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element_accumulator=cutlass.int32, opcode_class=cutlass.OpClass.TensorOp,
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math_operation=MathOperation.multiply_add
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)
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tile_description = TileDescription(
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threadblock_shape=[128, 128, 128],
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stages=3, warp_count=[2, 2, 1],
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math_instruction=math_inst
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)
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A = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajor,
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alignment=16
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)
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B = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajor,
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alignment=16
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)
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C = TensorDescription(
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element=cutlass.int32, layout=cutlass.ColumnMajor,
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alignment=4
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)
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element_epilogue = cutlass.int32
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epilogue_functor = LinearCombinationClamp(
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C.element, C.alignment, math_inst.element_accumulator,
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element_epilogue
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)
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swizzling_functor = cutlass.IdentitySwizzle1
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operation = GemmOperationUniversal(
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arch=80, tile_description=tile_description,
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A=A, B=B, C=C,
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epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
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)
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self.assertTrue(test_all_gemm(operation, "multistage"))
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def test_SM80_Device_Gemm_s8t_s8n_s32t_tensor_op_s32_128x128x128_64x64x128(self):
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math_inst = MathInstruction(
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instruction_shape=[16, 8, 32],
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element_a=cutlass.int8, element_b=cutlass.int8,
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element_accumulator=cutlass.int32, opcode_class=cutlass.OpClass.TensorOp,
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math_operation=MathOperation.multiply_add
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)
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tile_description = TileDescription(
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threadblock_shape=[128, 128, 128],
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stages=3, warp_count=[2, 2, 1],
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math_instruction=math_inst
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)
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A = TensorDescription(
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element=cutlass.int8, layout=cutlass.RowMajor,
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alignment=16
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)
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B = TensorDescription(
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element=cutlass.int8, layout=cutlass.ColumnMajor,
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alignment=16
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)
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C = TensorDescription(
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element=cutlass.int32, layout=cutlass.RowMajor,
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alignment=4
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)
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element_epilogue = cutlass.int32
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epilogue_functor = LinearCombinationClamp(
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C.element, C.alignment, math_inst.element_accumulator,
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element_epilogue
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)
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swizzling_functor = cutlass.IdentitySwizzle1
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operation = GemmOperationUniversal(
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arch=80, tile_description=tile_description,
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A=A, B=B, C=C,
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epilogue_functor=epilogue_functor, swizzling_functor=swizzling_functor
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)
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self.assertTrue(test_all_gemm(operation, "multistage"))
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if __name__ == '__main__':
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pycutlass.get_memory_pool(2**30, 2**30)
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unittest.main()
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