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124 lines
4.6 KiB
Python
124 lines
4.6 KiB
Python
################################################################################
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#
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# Copyright (C) 2019-2022 Advanced Micro Devices, Inc. All rights reserved.
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in
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# all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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#
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################################################################################
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import pytest,logging
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from Tensile.SolutionStructs import Convolution,ConvolutionConfig
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log =logging.getLogger("testlog")
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def test_spatial_in():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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})
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log.debug(conv.printUsage(z))
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pcc = ConvolutionConfig(spatial=[14,15])
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p = conv.makeProblem(n=64, c=1024, k=256, pcc=pcc)
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assert(p[0] == [210, 256, 64, 1024])
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assert(p[1] == [1, 210, 215040])
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assert(p[2] == [-1, -1, 0])
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def test_spatial_parm():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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'Spatial' : '13x14',
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})
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log.debug(conv.printUsage(z))
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pcc = ConvolutionConfig()
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p = conv.makeProblem(n=64, c=1024, k=256, pcc=pcc)
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assert(p[0] == [182, 256, 64, 1024])
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assert(p[1] == [1, 182, 186368])
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assert(p[2] == [-1, -1, 0])
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def test_stride():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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'Spatial' : '13x14',
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'Stride' : '2x3',
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})
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log.debug(conv.printUsage(z))
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p = conv.makeProblem(n=64, c=1024, k=256, pcc=conv.cc)
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assert(p[0] == [5, 7, 256, 64, 1024])
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assert(p[1] == [3, 28, 182, 186368])
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assert(p[2] == [-1, -1, 0])
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def test_stride_filter():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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'Spatial' : '13x14',
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'Stride' : '2x3',
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'Filter' : '3x4',
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})
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log.debug(conv.printUsage(z))
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p = conv.makeProblem(n=64, c=1024, k=256, pcc=conv.cc)
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assert(p[0] == [4, 6, 256, 64, 3, 4, 1024])
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assert(p[1] == [1, 14, 3, 28, 182, 186368])
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assert(p[2] == [-1, -1, -1, -1, 0])
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def test_stride_filter_dilated():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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'Spatial' : '13x14',
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'Stride' : '2x3',
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'Filter' : '3x4',
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'Dilation': '2x3',
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})
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log.debug(conv.printUsage(z))
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p = conv.makeProblem(n=64, c=1024, k=256, pcc=conv.cc)
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assert(p[0] == [2, 5, 256, 64, 3, 4, 1024])
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assert(p[1] == [3, 28, 3, 28, 182, 186368])
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assert(p[2] == [-1, -1, -1, -1, 0])
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def test_spatial_unspecified():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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})
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log.debug(conv.printUsage(z))
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with pytest.raises(RuntimeError, match="ConvolutionConfig field 'spatial' == None"):
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conv.makeProblem(n=64, c=1024, k=256, pcc=conv.cc)
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def test_mismatch():
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z={} # problemType definition
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conv = Convolution(z, 'ConvolutionForward',
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config={'TensorAFormat': 'NCHW',
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'Spatial' : '34x99',
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})
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log.debug(conv.printUsage(z))
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pcc = ConvolutionConfig(spatial=[14,15])
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with pytest.raises(RuntimeError, match="Mismatch between ConvolutionConfig value"):
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conv.makeProblem(n=64, c=1024, k=256, pcc=pcc)
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