Python Tesla.executeの例

コード例 #1

ファイル: pythonTest.py プロジェクト: BerkeleyVogelheim/ContextEngine27

firstTS = time.time();
algorithmTest.train();
secondTS = time.time();
teslaTimestamps["train"] = secondTS - firstTS;

runningTotal = 0;
for executeSample in range(numExecuteSamples):
    inputRow = next(inputReader);
    outputRow = next(outputReader);
    if (len(inputRow) > 0):
        input1 = float(inputRow[0]);
        input2 = float(inputRow[1]);
        output = float(outputRow[0]);

        firstTS = time.time();
        theor = algorithmTest.execute([input1, input2]);
        secondTS = time.time();
        teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS;
        teslaTimestamps["delta" + str(executeSample)] = abs(output - theor);
        runningTotal += output;

avgActual = runningTotal/(1.0*numExecuteSamples);

netLoadingTime = 0;
for i in range(numTrainingSamples):
    netLoadingTime += teslaTimestamps["load" + str(i)];

netExecuteTime = 0;
runningMAE = 0.0;
for i in range(numExecuteSamples):
    netExecuteTime += teslaTimestamps["test" + str(i)];

コード例 #2

print(str(trainingSample))
firstTS = time.time()
algorithmTest.train()
secondTS = time.time()
teslaTimestamps["train"] = secondTS - firstTS

runningTotal = 0
for executeSample in range(numExecuteSamples):
    inputRow = next(inputReader)
    outputRow = next(outputReader)
    if (len(inputRow) > 0):
        inputs = [float(x) for x in inputRow[0:numInputs]]
        output = float(outputRow[0])

        firstTS = time.time()
        theor = algorithmTest.execute(inputs)
        secondTS = time.time()
        teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS
        teslaTimestamps["delta" + str(executeSample)] = abs(output - theor)
        runningTotal += output
avgActual = runningTotal / (1.0 * numExecuteSamples)

netLoadingTime = 0
for i in range(numTrainingSamples):
    netLoadingTime += teslaTimestamps["load" + str(i)]

netExecuteTime = 0
runningMAE = 0.0
for i in range(numExecuteSamples):
    netExecuteTime += teslaTimestamps["test" + str(i)]
    runningMAE += teslaTimestamps["delta" + str(i)]

コード例 #3

ファイル: accessorTest.py プロジェクト: aryamansharda/ContextEngine

firstTS = time.time();
algorithmTest.train();
secondTS = time.time();
teslaTimestamps["train"] = secondTS - firstTS;

runningTotal = 0;
for executeSample in range(numExecuteSamples):
    inputRow = next(inputReader);
    outputRow = next(outputReader);
    if (len(inputRow) > 0):
        input1 = float(inputRow[0]);
        input2 = float(inputRow[1]);
        output = float(outputRow[0]);

        firstTS = time.time();
        theor = algorithmTest.execute([input1, input2]);
        secondTS = time.time();
        teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS;
        teslaTimestamps["delta" + str(executeSample)] = abs(output - theor);
        runningTotal += output;

avgActual = runningTotal/(1.0*numExecuteSamples);

netLoadingTime = 0;
for i in range(numTrainingSamples):
    netLoadingTime += teslaTimestamps["load" + str(i)];

netExecuteTime = 0;
runningMAE = 0.0;
for i in range(numExecuteSamples):
    netExecuteTime += teslaTimestamps["test" + str(i)];

コード例 #4

ファイル: aqTest.py プロジェクト: UCSD-Terraswarm/ContextEngine34

		for executeSample in range(numExecuteSamples):
			try:
				inputRow = next(inputReader);
				outputRow = next(outputReader);
			except:
				inputFile.seek(0);
				outputFile.seek(0);
				inputRow = next(inputReader);
				outputRow = next(outputReader);
		
			if (len(inputRow) > 0):
				inputVec = [ float(x) for x in inputRow ]
				output = float(outputRow[0]);

				firstTS 	= time.time();
				theor 		= algorithmTest.execute(inputVec);
				secondTS 	= time.time();
				teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS;
				teslaError["delta" + str(executeSample)] = abs(output - theor);
				runningTotal += output;
			else:
				print("Error reading test samples");
				sys.exit();

		netLoadingTime = 0;
		for i in range(numTrainingSamples):
			netLoadingTime += teslaTimestamps["load" + str(i)];

		netExecuteTime = 0;
		runningMAE = 0.0;
		for i in range(numExecuteSamples):

コード例 #5

print(str(trainingSample))
firstTS = time.time()
algorithmTest.train()
secondTS = time.time()
teslaTimestamps["train"] = secondTS - firstTS

runningTotal = 0
for executeSample in range(numExecuteSamples):
    inputRow = next(inputReader)
    outputRow = next(outputReader)
    if (len(inputRow) > 0):
        input1 = float(inputRow[0])
        output = float(outputRow[0])

        firstTS = time.time()
        theor = algorithmTest.execute([input1])
        secondTS = time.time()
        teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS
        teslaTimestamps["delta" + str(executeSample)] = abs(output - theor)
        runningTotal += output

avgActual = runningTotal / (1.0 * numExecuteSamples)

netLoadingTime = 0
for i in range(numTrainingSamples):
    netLoadingTime += teslaTimestamps["load" + str(i)]

netExecuteTime = 0
runningMAE = 0.0
for i in range(numExecuteSamples):
    netExecuteTime += teslaTimestamps["test" + str(i)]

コード例 #6

ファイル: python_PS_perday.py プロジェクト: BerkeleyVogelheim/ContextEngine27

secondTS = time.time();
teslaTimestamps["train"] = secondTS - firstTS;

runningActual = [];
for executeSample in range(numExecuteSamples):
    inputRow = next(inputReader);
    outputRow = next(outputReader);
    if (len(inputRow) > 0):
        inputs = inputRow[:numInputsToUse];
        inputs = [float(x) for x in inputs];
#        input1 = float(inputRow[0]);
#        input2 = float(inputRow[1]);
        output = float(outputRow[0]);

        firstTS = time.time();
        theor = algorithmTest.execute(inputs);
#        theor = 0 if (theor < 0.0) else theor;
#        print(str(theor) + "\t" + str(output));
#        theor = algorithmTest.execute([input1, input2]);
        secondTS = time.time();
        teslaTimestamps["test" + str(executeSample)] = secondTS - firstTS;
        teslaTimestamps["delta" + str(executeSample)] = abs(output - theor);

        runningActual.append(output);

runningActualHigh = [x for x in runningActual if x > 0];
avgActual =  sum(runningActualHigh)/(1.0*len(runningActualHigh));

netLoadingTime = 0;
for i in range(numTrainingSamples):
    netLoadingTime += teslaTimestamps["load" + str(i)];