################################################################################ # # Copyright (c) 2023 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: BSD-3-Clause # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # 3. Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ################################################################################ """ Unit test for store nodes in SM90 """ import logging import unittest import cutlass from cutlass.backend import * from cutlass.epilogue import * from utils.evt_testbed import EVTTestBed, EVTTestCaseBase cutlass.set_log_level(logging.WARNING) @unittest.skipIf(device_cc() not in [80, 86, 89, 90], "This unittest is only supported on CC [80, 86, 89, 90]") class TestEVTLayout(EVTTestCaseBase): def test_permute_1(self): """ Returning a tensor with shape [m, n] """ def evt_permute(accum, alpha, C): F = alpha * accum F_permute = permute(F, indices=(0, 2, 1)) D_permute = F_permute + permute(C, indices=(0, 2, 1)) D = permute(D_permute, indices=(0, 2, 1)) return D, F for m, n, k, l in self.get_problem_sizes(8): example_inputs = { "accum": self.fake_tensor(self.element, (l, m, n)), "alpha": 0.5, "C": self.fake_tensor(self.element, (l, m, n)), "F": self.fake_tensor(self.element, (l, m, n)), "D": self.fake_tensor(self.element, (l, m, n)), } launcher = EVTTestBed(self.element, evt_permute, example_inputs) input_keys = ["C", "alpha"] result_keys = ["D", "F"] launcher.verify((m, n, k), input_keys, result_keys, l) @unittest.skipIf(device_cc() != 90, "This unittest is for cc = Sm90 only") def test_permute_2(self): """ Returning a tensor with shape [m, n] """ def evt_permute(accum, alpha, C): F = alpha * accum F_permute = permute(F, indices=(0, 2, 1)) D = F_permute + C return D, F for m, n, k, l in self.get_problem_sizes(8): example_inputs = { "accum": self.fake_tensor(self.element, (l, m, n)), "alpha": 0.5, "C": self.fake_tensor(self.element, (l, n, m)), "F": self.fake_tensor(self.element, (l, m, n)), "D": self.fake_tensor(self.element, (l, n, m)), } launcher = EVTTestBed(self.element, evt_permute, example_inputs) input_keys = ["C", "alpha"] result_keys = ["D", "F"] launcher.verify((m, n, k), input_keys, result_keys, l) @unittest.skipIf(device_cc() != 90, "This unittest is for cc = Sm90 only") def test_permute_3(self): """ Returning a tensor with shape [m, n] """ def evt_permute(accum, alpha, C): F = alpha * accum F_permute = permute(F, indices=(1, 0, 2)) D = F_permute + C return D, F for m, n, k, l in self.get_problem_sizes(8): example_inputs = { "accum": self.fake_tensor(self.element, (l, m, n)), "alpha": 0.5, "C": self.fake_tensor(self.element, (m, l, n)), "F": self.fake_tensor(self.element, (l, m, n)), "D": self.fake_tensor(self.element, (m, l, n)), } launcher = EVTTestBed(self.element, evt_permute, example_inputs) input_keys = ["C", "alpha"] result_keys = ["D", "F"] launcher.verify((m, n, k), input_keys, result_keys, l) def test_reshape(self): """ Test reshape """ def evt_reshape(accum, alpha, TensorE): F = alpha * accum E_reshape = reshape(TensorE, new_shape=(512, 1)) D = F + E_reshape return D example_inputs = { "accum": self.fake_tensor(self.element, (self.l, self.m, self.n)), "alpha": 0.5, "TensorE": self.fake_tensor(self.element, (16, 32)), "D": self.fake_tensor(self.element, (self.l, self.m, self.n)), } launcher = EVTTestBed(self.element, evt_reshape, example_inputs) input_keys = ["alpha", "TensorE"] result_keys = ["D"] launcher.verify(self.problem_size, input_keys, result_keys, self.l) def test_reshape2(self): """ Test reshape """ def evt_reshape(accum, alpha, TensorE): F = alpha * accum F_reshape = reshape(F, new_shape=(2, 3, 512, 256)) D = F_reshape + TensorE return D example_inputs = { "accum": self.fake_tensor(self.element, (self.l, self.m, self.n)), "alpha": 0.5, "TensorE": self.fake_tensor(self.element, (2, 3, 1, self.n)), "D": self.fake_tensor(self.element, (2, 3, self.m, self.n)), } launcher = EVTTestBed(self.element, evt_reshape, example_inputs) input_keys = ["alpha", "TensorE"] result_keys = ["D"] launcher.verify(self.problem_size, input_keys, result_keys, self.l) if __name__ == '__main__': unittest.main()