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#################################################################################################
#
# 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.
#
#################################################################################################
"""
Test the EVT interface
"""
import numpy as np
import unittest
import cutlass
from cutlass import LayoutType, Tensor
from cutlass.backend.utils.device import device_cc
from cutlass.epilogue import reshape, permute
from utils import ExpectException
@unittest.skipIf(device_cc() not in [80, 90], "This unittest is for Sm80 and Sm90 only")
class EVTErrorTests(unittest.TestCase):
"""
Tests various error scenarios that arise with the EVT interface
"""
@unittest.skipIf(device_cc() != 90, "Only Sm90 EVT requires root node be 'D'")
def test_root_not_d(self):
"""
Test when "D" does not exist in Sm90 EVT
"""
def evt_root_not_d(accum, alpha):
F = accum * alpha
return F
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"alpha": 1.2,
"F": self.fake_tensor(np.float16, (6, 512, 512))
}
with ExpectException(device_cc() == 90,
"SyntaxError: Sm90 EVT requires the epilogue to have a returned tensor D, "
"but the variable 'D' is not found in the return values.", True):
cutlass.epilogue.trace(evt_root_not_d, example_tensors)
def test_no_accum(self):
"""
Test when "accum" is not in input arguments
"""
def evt_no_accum(alpha, C):
D = alpha * C
return D
example_tensors = {
"C": self.fake_tensor(np.float16, (6, 512, 512)),
"alpha": 1.2,
"D": self.fake_tensor(np.float16, (6, 512, 512))
}
with ExpectException(True, "SyntaxError: Cannot find 'accum' in the argument list.", True):
cutlass.epilogue.trace(evt_no_accum, example_tensors)
@unittest.skipIf(device_cc() != 90, "Only Sm90 EVT has concern on smem size")
def test_too_much_shared_memory(self):
"""
Test when the epilogue consumes too much shared memory
"""
def evt_too_much_shared_memory(accum, C1, C2, C3, C4, C5, C6, C7, C8):
D1 = accum + C1
D2 = D1 + C2
D3 = D2 + C3
D4 = D3 + C4
D5 = D4 + C5
D6 = D5 + C6
D7 = D6 + C7
D = D7 + C8
return D, D1, D2, D3, D4, D5, D6, D7
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"C1": self.fake_tensor(np.float16, (6, 512, 512)),
"C2": self.fake_tensor(np.float16, (6, 512, 512)),
"C3": self.fake_tensor(np.float16, (6, 512, 512)),
"C4": self.fake_tensor(np.float16, (6, 512, 512)),
"C5": self.fake_tensor(np.float16, (6, 512, 512)),
"C6": self.fake_tensor(np.float16, (6, 512, 512)),
"C7": self.fake_tensor(np.float16, (6, 512, 512)),
"C8": self.fake_tensor(np.float16, (6, 512, 512)),
"D1": self.fake_tensor(np.float16, (6, 512, 512)),
"D2": self.fake_tensor(np.float16, (6, 512, 512)),
"D3": self.fake_tensor(np.float16, (6, 512, 512)),
"D4": self.fake_tensor(np.float16, (6, 512, 512)),
"D5": self.fake_tensor(np.float16, (6, 512, 512)),
"D6": self.fake_tensor(np.float16, (6, 512, 512)),
"D7": self.fake_tensor(np.float16, (6, 512, 512)),
"D": self.fake_tensor(np.float16, (6, 512, 512))
}
epilogue_visitor = cutlass.epilogue.trace(evt_too_much_shared_memory, example_tensors)
plan = cutlass.op.Gemm(
element=np.float16, layout=cutlass.LayoutType.RowMajor,
element_accumulator=np.float32
)
with ExpectException(True,
"RuntimeError: The epilogue consumes too much shared memory. "
"No valid tile description is found in the generator.", True):
plan.epilogue_visitor = epilogue_visitor
def test_not_ssa(self):
"""
Test when the epilogue is not in SSA
"""
def evt_redefine(accum, C, alpha):
F = accum + C
F = F * alpha
D = F
return D, F
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"C": self.fake_tensor(np.float16, (6, 512, 512)),
"alpha": 1.5,
"D": self.fake_tensor(np.float16, (6, 512, 512)),
"F": self.fake_tensor(np.float16, (6, 512, 512))
}
with ExpectException(True, "SyntaxError: Variable 'F' cannot be defined twice.", True):
cutlass.epilogue.trace(evt_redefine, example_tensors)
def evt_undefine(accum, alpha):
F = accum + C
D = F * alpha
return D, F
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"alpha": 1.5,
"D": self.fake_tensor(np.float16, (6, 512, 512)),
"F": self.fake_tensor(np.float16, (6, 512, 512))
}
with ExpectException(True, "SyntaxError: Variable 'C' is undefined.", True):
cutlass.epilogue.trace(evt_undefine, example_tensors)
def test_missing_example_tensor(self):
"""
Test when the example tensor of an input/output variable is not provided
"""
def evt_missing_example_tensor(accum, C):
D = accum + C
return D
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"C": self.fake_tensor(np.float16, (6, 512, 512)),
}
with ExpectException(True, "RuntimeError: Example input for D is not provided.", True):
cutlass.epilogue.trace(evt_missing_example_tensor, example_tensors)
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"D": self.fake_tensor(np.float16, (6, 512, 512)),
}
with ExpectException(True, "RuntimeError: Example input for C is not provided.", True):
cutlass.epilogue.trace(evt_missing_example_tensor, example_tensors)
def test_return_expression(self):
"""
Test when the return value is an expression
"""
def evt_return_expr(accum, C):
return accum + C
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 512)),
"C": self.fake_tensor(np.float16, (6, 512, 512)),
}
with ExpectException(True, "SyntaxError: Return value cannot be an expression", True):
cutlass.epilogue.trace(evt_return_expr, example_tensors)
def test_incompatible_shape(self):
"""
Test when the shape of example tensors are incompatible
"""
def evt_incompatible_shape(accum, C):
D = accum + C
return D
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 256, 512)),
"C": self.fake_tensor(np.float16, (6, 512, 512)),
"D": self.fake_tensor(np.float16, (6, 512, 512))
}
with ExpectException(True,
"RuntimeError: Dimension mismatch between accum(6, 256, 512), C(6, 512, 512).", True):
cutlass.epilogue.trace(evt_incompatible_shape, example_tensors)
def test_no_matching_impl(self):
def evt_no_matching_impl(accum, bias):
D = accum + reshape(permute(bias, indices=(1, 0)), new_shape=(512, 1))
return D
example_tensors = {
"accum": self.fake_tensor(np.float16, (6, 512, 256)),
"bias": self.fake_tensor(np.float16, (16, 32)),
"D": self.fake_tensor(np.float16, (6, 512, 256))
}
with ExpectException(True, "NotImplementedError: No matching op for node bias with stride (0, (1, 32), 0).", True):
cutlass.epilogue.trace(evt_no_matching_impl, example_tensors)
#
# Helper functions
#
def fake_tensor(self, element, shape):
return Tensor(element=element, shape=shape, layout_tag=LayoutType.RowMajor)
if __name__ == '__main__':
unittest.main()
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