Python ModelBuilder.buildRN_IIIの例

コード例 #1

ファイル: test.py プロジェクト: MMMMasterM/rn-variations

                            args.f_layers, args.f_inner_layers, args.g_layers,
                            args.h_layers, args.appendPosVec)

(inputContext, inputContextLengths, inputContextSentenceLengths, inputQuestion,
 inputQuestionLengths, objects,
 question) = modelBuilder.buildWordProcessorLSTMs()

if modelToUse == 1:
    print("Using model I")
    rnOutput = modelBuilder.buildRN_I(objects, question)
elif modelToUse == 2:
    print("Using model II")
    rnOutput = modelBuilder.buildRN_II(objects, question)
elif modelToUse == 3:
    print("Using model III")
    rnOutput = modelBuilder.buildRN_III(objects, question)
elif modelToUse == 4:
    print("Using model IV")
    rnOutput = modelBuilder.buildRN_IV(objects, question)
elif modelToUse == 5:
    print("Using model V")
    rnOutput = modelBuilder.buildRN_V(objects, question)
elif modelToUse == 6:
    print("Using model VI")
    rnOutput = modelBuilder.buildRN_VI(objects, question)
elif modelToUse == 7:
    print("Using model VII")
    rnOutput = modelBuilder.buildRN_VII_jl(objects, question)
elif modelToUse == 8 and layerCount >= 0:
    print("Using model VIII with " + str(layerCount) + " layers")
    rnOutput = modelBuilder.buildRN_VIII_jl(objects, question, layerCount)

コード例 #2

        yield contextInput, contextLengths, contextSentenceLengths, questionInput, questionLengths, answerInput

#build the whole model and run it
modelBuilder = ModelBuilder(batch_size, macro_batch_size, question_dim, obj_dim, dictSize, args.questionAwareContext, args.f_layers, args.f_inner_layers, args.g_layers, args.h_layers, args.appendPosVec, args.batchNorm, args.layerNorm, args.weightPenalty)

(inputContext, inputContextLengths, inputContextSentenceLengths, inputQuestion, inputQuestionLengths, objects, question) = modelBuilder.buildWordProcessorLSTMs()

if modelToUse == 1:
    print("Using model I")
    (rnOutput, isTraining) = modelBuilder.buildRN_I(objects, question)
elif modelToUse == 2:
    print("Using model II")
    (rnOutput, isTraining) = modelBuilder.buildRN_II(objects, question)
elif modelToUse == 3:
    print("Using model III")
    (rnOutput, isTraining) = modelBuilder.buildRN_III(objects, question)
elif modelToUse == 4:
    print("Using model IV")
    (rnOutput, isTraining) = modelBuilder.buildRN_IV(objects, question)
elif modelToUse == 5:
    print("Using model V")
    (rnOutput, isTraining) = modelBuilder.buildRN_V(objects, question)
elif modelToUse == 6:
    print("Using model VI")
    (rnOutput, isTraining) = modelBuilder.buildRN_VI(objects, question)
elif modelToUse == 7:
    print("Using model VII")
    (rnOutput, isTraining) = modelBuilder.buildRN_VII_jl(objects, question)
elif modelToUse == 8 and layerCount >= 0:
    print("Using model VIII with " + str(layerCount) + " layers")
    (rnOutput, isTraining) = modelBuilder.buildRN_VIII_jl(objects, inputContextLengths, question, layerCount)