def test_stride2x3(request, tensile_client_dir, tmp_path):
z = {} # problemType definition
conv = Convolution(z,
'ConvolutionForward',
config={
'TensorAFormat': 'NCHW',
'Filter': '1x1',
'Stride': '2x3',
'Dilation': '1x1',
'Spatial': '17x31',
})
log.debug(conv.printUsage(z))
YamlBuilder.run_convolution_vs_contraction(request, conv, z,
tensile_client_dir, tmp_path)
def test_nchw_backwardweights_filter3x5(request, tensile_client_dir, tmp_path):
z = {} # problemType definition
conv = Convolution(z,
'ConvolutionBackwardWeights',
config={
'TensorAFormat': 'NCHW',
'Filter': '3x5',
})
log.debug(conv.printUsage(z))
assert (z['NumIndicesC'] == 4)
assert (z['IndexAssignmentsA'] == [5, 0, 1, 2, 4])
assert (z['IndexAssignmentsB'] == [5, 3, 4])
#assert(z['SetConstStrideA']==[[3,1]])
assert (z['SetConstStrideB'] == [])
YamlBuilder.run_tensile_client(request, conv, z, tensile_client_dir,
tmp_path)
def test_nchw_backwardweights_defaults(request, tensile_client_dir, tmp_path):
z = {} # problemType definition
conv = Convolution(z,
'ConvolutionBackwardWeights',
config={
'TensorAFormat': 'NCHW',
'Spatial': '14x14',
})
log.debug(conv.printUsage(z))
assert (z['NumIndicesC'] == 2)
assert (z['IndexAssignmentsA'] == [3, 0, 2])
assert (z['IndexAssignmentsB'] == [3, 1, 2])
assert (z['SetConstStrideA'] == [[3, 1]])
assert (z['SetConstStrideB'] == [])
YamlBuilder.run_tensile_client(request, conv, z, tensile_client_dir,
tmp_path)
def test_yaml(request, tensile_client_dir, tmp_path):
z = {} # problemType definition
conv = Convolution(z,
'ConvolutionForward',
config={
'TensorAFormat': 'NCHW',
})
log.debug(conv.printUsage(z))
assert (z['NumIndicesC'] == 3)
assert (z['IndexAssignmentsA'] == [0, 3, 2])
assert (z['IndexAssignmentsB'] == [3, 1, 2])
assert (z['SetConstStrideA'] == [[0, 1]])
assert (z['SetConstStrideB'] == [[2, 0]])
assert (z['UseInitialStrides'] == False)
YamlBuilder.run_tensile_client(request, conv, z, tensile_client_dir,
tmp_path)
def run(conv, problemType={}, solution=Solutions.src1, dataType='s'):
config = YamlBuilder.ConvolutionVsContraction(conv, solution, dataType)
configFile = file_with_test_name(".conv.yaml")
config.write(configFile)
args = [str(configFile), str(tmp_path), *tensile_args]
subprocess.check_call([tensile_script_path] + args)
def run(conv,
problemType={},
solution=Solutions.defaultSolution(),
dataType='s'):
config = YamlBuilder.ConvolutionVsContraction(conv, solution, dataType)
configFile = file_with_test_name(".conv.yaml")
config.write(configFile)
Tensile.Tensile([str(configFile), str(tmp_path), *tensile_args])
def run(conv, problemType, solution=Solutions.defaultSolution(), problemFunc=None, problemLevel=-1, dataType='s'):
if problemFunc == None:
problemFunc = YamlBuilder.ProblemSizes
if problemLevel==-1:
problemLevel = request.config.getoption("--problem-level")
config = YamlBuilder.ConvolutionContraction(conv, problemType, solution, dataType, problemFunc, True, problemLevel)
configFile = file_with_test_name(".contraction.yaml")
print("Generate_YAML output:", configFile)
config.write(configFile)
return configFile
def test_3d(problem_level):
"Test number of problems generated"
z={} # problemType definition
conv = Convolution(z, 'ConvolutionForward',
config={'TensorAFormat': 'NCDHW',
'Stride': '2x2x2',
'Filter': '3x3x3',
})
exacts = YamlBuilder.ProblemSizes(conv, z, problem_level)
if exacts:
None
def test_filter_stride_dilation_0(request, tensile_client_dir, tmp_path):
z = {} # problemType definition
conv = Convolution(z,
'ConvolutionForward',
config={
'TensorAFormat': 'NCHW',
'TensorBFormat': 'KCYX',
'TensorDFormat': 'NCHW',
'Filter': '2x3',
'Stride': '2x3',
'Dilation': '2x3',
'Spatial': '17x31',
})
assert (z['NumIndicesC'] == 4)
assert (z['IndexAssignmentsA'] == [6, 5, 0, 1, 4, 3])
assert (z['IndexAssignmentsB'] == [6, 5, 4, 2, 3])
assert (z['SetConstStrideA'] == [[0, 3], [6, 3]])
assert (z['SetConstStrideB'] == [[3, 0]])
assert (z['UseInitialStrides'] == True)
log.debug(conv.printUsage(z))
YamlBuilder.run_convolution_vs_contraction(request, conv, z,
tensile_client_dir, tmp_path)
def run(conv, problemType, dataType='s'):
config = YamlBuilder.ConvolutionContraction(conv, problemType, dataType)
configFile = file_with_test_name(".contraction.yaml")
config.write(configFile)
return configFile
