174 lines
6.5 KiB
Python
174 lines
6.5 KiB
Python
################################################################################
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#
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# Copyright (c) 2023 - 2024 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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"""
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Unit test for store nodes in SM90
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"""
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import logging
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import unittest
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import cutlass
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from cutlass.backend import *
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from cutlass.epilogue import *
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from utils.evt_testbed import EVTTestBed, EVTTestCaseBase
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cutlass.set_log_level(logging.WARNING)
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@unittest.skipIf(device_cc() not in [80, 86, 89, 90], "This unittest is only supported on CC [80, 86, 89, 90]")
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class TestEVTLayout(EVTTestCaseBase):
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def test_permute_1(self):
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"""
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Returning a tensor with shape [m, n]
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"""
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def evt_permute(accum, alpha, C):
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F = alpha * accum
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F_permute = permute(F, indices=(0, 2, 1))
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D_permute = F_permute + permute(C, indices=(0, 2, 1))
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D = permute(D_permute, indices=(0, 2, 1))
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return D, F
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for m, n, k, l in self.get_problem_sizes(8):
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example_inputs = {
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"accum": self.fake_tensor(self.element, (l, m, n)),
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"alpha": 0.5,
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"C": self.fake_tensor(self.element, (l, m, n)),
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"F": self.fake_tensor(self.element, (l, m, n)),
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"D": self.fake_tensor(self.element, (l, m, n)),
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}
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launcher = EVTTestBed(self.element, evt_permute, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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@unittest.skipIf(device_cc() != 90, "This unittest is for cc = Sm90 only")
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def test_permute_2(self):
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"""
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Returning a tensor with shape [m, n]
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"""
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def evt_permute(accum, alpha, C):
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F = alpha * accum
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F_permute = permute(F, indices=(0, 2, 1))
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D = F_permute + C
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return D, F
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for m, n, k, l in self.get_problem_sizes(8):
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example_inputs = {
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"accum": self.fake_tensor(self.element, (l, m, n)),
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"alpha": 0.5,
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"C": self.fake_tensor(self.element, (l, n, m)),
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"F": self.fake_tensor(self.element, (l, m, n)),
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"D": self.fake_tensor(self.element, (l, n, m)),
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}
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launcher = EVTTestBed(self.element, evt_permute, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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@unittest.skipIf(device_cc() != 90, "This unittest is for cc = Sm90 only")
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def test_permute_3(self):
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"""
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Returning a tensor with shape [m, n]
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"""
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def evt_permute(accum, alpha, C):
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F = alpha * accum
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F_permute = permute(F, indices=(1, 0, 2))
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D = F_permute + C
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return D, F
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for m, n, k, l in self.get_problem_sizes(8):
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example_inputs = {
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"accum": self.fake_tensor(self.element, (l, m, n)),
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"alpha": 0.5,
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"C": self.fake_tensor(self.element, (m, l, n)),
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"F": self.fake_tensor(self.element, (l, m, n)),
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"D": self.fake_tensor(self.element, (m, l, n)),
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}
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launcher = EVTTestBed(self.element, evt_permute, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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def test_reshape(self):
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"""
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Test reshape
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"""
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def evt_reshape(accum, alpha, TensorE):
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F = alpha * accum
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E_reshape = reshape(TensorE, new_shape=(512, 1))
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D = F + E_reshape
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return D
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example_inputs = {
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"accum": self.fake_tensor(self.element, (self.l, self.m, self.n)),
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"alpha": 0.5,
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"TensorE": self.fake_tensor(self.element, (16, 32)),
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"D": self.fake_tensor(self.element, (self.l, self.m, self.n)),
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}
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launcher = EVTTestBed(self.element, evt_reshape, example_inputs)
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input_keys = ["alpha", "TensorE"]
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result_keys = ["D"]
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launcher.verify(self.problem_size, input_keys, result_keys, self.l)
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def test_reshape2(self):
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"""
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Test reshape
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"""
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def evt_reshape(accum, alpha, TensorE):
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F = alpha * accum
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F_reshape = reshape(F, new_shape=(2, 3, 512, 256))
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D = F_reshape + TensorE
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return D
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example_inputs = {
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"accum": self.fake_tensor(self.element, (self.l, self.m, self.n)),
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"alpha": 0.5,
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"TensorE": self.fake_tensor(self.element, (2, 3, 1, self.n)),
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"D": self.fake_tensor(self.element, (2, 3, self.m, self.n)),
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}
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launcher = EVTTestBed(self.element, evt_reshape, example_inputs)
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input_keys = ["alpha", "TensorE"]
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result_keys = ["D"]
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launcher.verify(self.problem_size, input_keys, result_keys, self.l)
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if __name__ == '__main__':
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unittest.main()
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