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142 lines
3.3 KiB
Python
142 lines
3.3 KiB
Python
import os.path
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import itertools
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import Tools
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import random
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import numpy as np
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NBTESTSAMPLES = 10
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# Nb vectors for barycenter
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NBVECTORS = [4,10,16]
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VECDIM = [12,14,20]
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def genWsum(config,nb,vecDim):
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dims=[]
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inputs=[]
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weights=[]
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output=[]
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va = np.random.rand(vecDim)
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vb = np.random.rand(vecDim)
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e = np.sum(va.T * vb) / np.sum(vb)
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inputs += list(va)
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weights += list(vb)
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output.append(e)
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inputs=np.array(inputs)
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weights=np.array(weights)
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output=np.array(output)
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config.writeInput(nb, inputs,"Inputs")
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config.writeInput(nb, weights,"Weights")
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config.writeReference(nb, output,"Ref")
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def genBarycenter(config,nb,nbTests,nbVecs,vecDim):
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dims=[]
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inputs=[]
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weights=[]
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output=[]
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dims.append(nbTests)
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dims.append(nbVecs)
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dims.append(vecDim)
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for _ in range(0,nbTests):
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vecs = []
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b = np.zeros(vecDim)
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coefs = np.random.rand(nbVecs)
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for i in range(nbVecs):
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va = np.random.rand(vecDim)
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b += va * coefs[i]
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vecs += list(va)
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b = b / np.sum(coefs)
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inputs += list(vecs)
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weights += list(coefs)
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output += list(b)
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inputs=np.array(inputs)
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weights=np.array(weights)
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output=np.array(output)
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config.writeInput(nb, inputs,"Inputs")
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config.writeInputS16(nb, dims,"Dims")
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config.writeInput(nb, weights,"Weights")
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config.writeReference(nb, output,"Ref")
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def writeTestsF32(config):
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NBSAMPLES=256
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va = np.random.rand(NBSAMPLES)
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config.writeInput(1,va,"Samples")
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config.writeInputQ15(3,va,"Samples")
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config.writeInputQ31(4,va,"Samples")
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config.writeInputQ7(5,va,"Samples")
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# This is for benchmarking the weighted sum and we use only one test pattern
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genWsum(config,6,256)
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def writeTestsQ31(config):
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NBSAMPLES=256
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va = np.random.rand(NBSAMPLES)
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config.writeInput(1,va,"Samples")
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config.writeInputQ15(3,va,"Samples")
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config.writeInputQ7(4,va,"Samples")
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def writeTestsQ15(config):
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NBSAMPLES=256
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va = np.random.rand(NBSAMPLES)
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config.writeInput(1,va,"Samples")
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config.writeInputQ31(3,va,"Samples")
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config.writeInputQ7(4,va,"Samples")
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def writeTestsQ7(config):
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NBSAMPLES=256
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va = np.random.rand(NBSAMPLES)
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config.writeInput(1,va,"Samples")
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config.writeInputQ31(3,va,"Samples")
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config.writeInputQ15(4,va,"Samples")
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def writeBarTests(config):
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# For testing
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genBarycenter(config,1,NBTESTSAMPLES,10,14)
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# For benchmarks
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va = np.random.rand(128*15)
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vb = np.random.rand(128)
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config.writeInput(1,va,"Samples")
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config.writeInput(1,vb,"Coefs")
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PATTERNDIR = os.path.join("Patterns","DSP","Support","Support")
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PARAMDIR = os.path.join("Parameters","DSP","Support","Support")
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configf32=Tools.Config(PATTERNDIR,PARAMDIR,"f32")
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configq31=Tools.Config(PATTERNDIR,PARAMDIR,"q31")
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configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")
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configq7=Tools.Config(PATTERNDIR,PARAMDIR,"q7")
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writeTestsF32(configf32)
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writeTestsQ31(configq31)
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writeTestsQ15(configq15)
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writeTestsQ7(configq7)
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# For benchmarking we need to vary number of vectors and vector dimension separately
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PATTERNBARDIR = os.path.join("Patterns","DSP","SupportBar")
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PARAMBARDIR = os.path.join("Parameters","DSP","SupportBar")
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configBarf32=Tools.Config(PATTERNBARDIR,PARAMBARDIR,"f32")
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writeBarTests(configBarf32) |