181 lines
7.0 KiB
Python
181 lines
7.0 KiB
Python
################################################################################
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#
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# Copyright (c) 2023 - 2026 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_cppgen
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from cutlass_cppgen.backend import *
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from cutlass_cppgen.epilogue import *
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from utils.evt_testbed import EVTTestBed, EVTTestCaseBase
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cutlass_cppgen.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 TestEVTStore(EVTTestCaseBase):
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@unittest.skipIf(device_cc() != 90, "This test is only for CC 90")
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def test_invalid_store(self):
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"""
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Test invalid store
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"""
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def evt_invalid_store(accum):
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D = accum
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F = D + 1 # D has users, which is not allowed on SM90 or higher
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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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"D": 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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}
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with self.assertRaisesRegex(
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RuntimeError,
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r"On SM90 or higher, D is expected to be a output node with 0 users "
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r"to enable smem reuse between C and D, but got 1"
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):
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launcher = EVTTestBed(self.element, evt_invalid_store, example_inputs)
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break # Only need to test once
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def test_aux_store(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_aux_store(accum, alpha, C):
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F = alpha * accum
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D = F + 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, 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_aux_store, 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_col_reduce(self):
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"""
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Reduction [m, n] -> [m, 1]
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"""
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def evt_row_reduce(accum, alpha, C):
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acc_row_max = max(accum, dim=[2,])
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F = alpha * accum
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F_row_max = max(F, dim=[0, 2])
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D = F + C
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return D, F_row_max, acc_row_max
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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": 2.0,
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"C": self.fake_tensor(self.element, (l, m, n)),
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"F_row_max": self.fake_tensor(np.float32, (m, 1)),
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"acc_row_max": self.fake_tensor(np.float32, (l, m, 1)),
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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_row_reduce, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F_row_max", "acc_row_max"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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def test_row_reduce(self):
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"""
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Reduction [m, n] -> [n]
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"""
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def evt_col_reduce(accum, alpha, C):
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acc_col_max = max(accum, dim=[1,])
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F = alpha * accum
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F_col_max = max(F, dim=[0, 1])
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D = F + C
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return D, F_col_max, acc_col_max
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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": 2.0,
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"C": self.fake_tensor(self.element, (l, m, n)),
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"F_col_max": self.fake_tensor(np.float32, (n,)),
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"acc_col_max": self.fake_tensor(np.float32, (l, 1, 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_col_reduce, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F_col_max", "acc_col_max"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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def test_scalar_reduce(self):
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"""
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Reduction [m, n] -> [1,]
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"""
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def evt_scalar_reduce(accum, alpha, C):
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acc_max = max(accum, dim=[1, 2])
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F = alpha * accum
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F_max = max(F, dim=[0, 1, 2])
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D = F + C
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return D, F_max, acc_max
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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": 2.0,
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"C": self.fake_tensor(self.element, (l, m, n)),
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"acc_max": self.fake_tensor(np.float32, (l, 1, 1)),
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"F_max": self.fake_tensor(np.float32, (1,)),
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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_scalar_reduce, example_inputs)
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input_keys = ["C", "alpha"]
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result_keys = ["D", "F_max", "acc_max"]
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launcher.verify((m, n, k), input_keys, result_keys, l)
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if __name__ == '__main__':
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unittest.main()
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