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- import os.path
- import itertools
- import Tools
- import random
- import numpy as np
- import scipy.special as sp
- NBTESTSAMPLES = 500
- def softmax(v):
- m = sp.softmax(v)
- return(np.argmax(m)+1)
- def writeTest(config,nb,vecDim):
- dims=[]
- inputsA=[]
- outputs=[]
- outputsSamples = []
- dims.append(NBTESTSAMPLES)
- dims.append(vecDim)
- for _ in range(0,NBTESTSAMPLES):
- va = np.abs(np.random.randn(vecDim))
- va = va / np.sum(va)
- r = sp.softmax(va)
- outputsSamples += list(r)
- outputs.append(np.argmax(r)+1)
- inputsA += list(va)
- inputsA=np.array(inputsA)
- outputs=np.array(outputs)
- outputsSamples=np.array(outputsSamples)
-
- config.writeInput(nb, inputsA,"InputA")
- config.writeInputS16(nb, dims,"Dims")
- config.writeReferenceS16(nb, outputs,"Ref")
- config.writeReference(nb, outputsSamples,"Samples")
-
- def writeTests(config):
- writeTest(config,1,21)
- PATTERNDIR = os.path.join("Patterns","NN","Softmax",)
- PARAMDIR = os.path.join("Parameters","NN","Softmax")
- configq7=Tools.Config(PATTERNDIR,PARAMDIR,"q7")
- writeTests(configq7)
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