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batra-mlp-lab / visdial-rl

PyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning
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Somehow -visdomServer is overwritten in an unexpected way #3

Closed okisy closed 6 years ago

okisy commented 6 years ago

This is related to https://github.com/batra-mlp-lab/visdial-rl/issues/2 I ran python -m visdom.server -p 8097 in order to use visdom.

After that, I ran python evaluate.py -useGPU \ -startFrom checkpoints/abot_sl_ep60.vd \ -qstartFrom checkpoints/qbot_sl_ep60.vd \ -evalMode ABotRank QBotRank \ -visdomServer http://127.0.0.1 \ -visdomServerPort 8097 \ -visdomEnv ABotRank-QBotRank Even though I clearly designated which server to use and the server port number, somehow they are overwritten as follows. How can I fix this?

{'CELossCoeff': 200, 'batchSize': 20, 'beamSize': 1, 'ckpt_iterid': 152160, 'ckpt_lRate': 4.999614155150613e-05, 'cocoDir': '', 'cocoInfo': '', 'continue': True, 'decoder': 'gen', 'dropout': 0.0, 'embedSize': 300, 'enableVisdom': 1, 'encoder': 'hre-ques-lateim-hist', 'evalModeList': ['ABotRank', 'QBotRank'], 'evalSplit': 'val', 'evalTitle': 'eval', 'featLossCoeff': 1000, 'freezeQFeatNet': 0, 'imgEmbedSize': 300, 'imgFeatureSize': 4096, 'imgNorm': 1, 'inputImg': 'data/visdial/data_img.h5', 'inputJson': 'data/visdial/chat_processed_params.json', 'inputQues': 'data/visdial/chat_processed_data.h5', 'learningRate': 0.001, 'lrDecayRate': 0.9997592083, 'minLRate': 5e-05, 'numEpochs': 65, 'numLayers': 2, 'numRounds': 10, 'numWorkers': 2, 'qdecoder': 'gen', 'qencoder': 'hre-ques-lateim-hist', 'qstartFrom': 'checkpoints/qbot_sl_ep60.vd', 'randomSeed': 32, 'rlAbotReward': 1, 'rnnHiddenSize': 512, 'saveName': 'debug-final5_sl-qbot', 'savePath': 'checkpoints/debug-final5_sl-qbot', 'startFrom': 'checkpoints/abot_sl_ep60.vd', 'trainMode': 'sl-abot', 'useCurriculum': 1, 'useGPU': True, 'useHistory': True, 'useIm': 'late', 'verbose': 1, 'visdomEnv': 'ABotRank-QBotRank', 'visdomServer': 'http://walle.cc.gatech.edu', 'visdomServerPort': 8893, 'vocabSize': 7826}

nirbhayjm commented 6 years ago

Thanks for pointing this out, the visdom parameters were being overwritten in evaluate.py with the ones loaded from checkpoint. I have added those parameters to the list of excluded parameters in 58110e2e542260bd145a28bd480eb8ad6003e3ad to prevent this. Let me know if the issue persists.