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config.py
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config.py
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"""Configuration for models."""
import os
import tensorflow as tf
CONFIG = {
'esa': {
'msvd_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 4000,
'pretrained_embedding': 'data/msvd_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 32,
'reg_coeff': 1e-5,
'learning_rate': 0.001
}
}
},
'msrvtt_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 8000,
'pretrained_embedding': 'data/msrvtt_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 64,
'reg_coeff': 1e-6,
'learning_rate': 0.001
}
}
}
},
'emn': {
'msvd_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 4000,
'pretrained_embedding': 'data/msvd_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'memory_dim': 256
},
'train': {
'batch_size': 32,
'reg_coeff': 1e-5,
'learning_rate': 0.001
}
}
},
'msrvtt_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 8000,
'pretrained_embedding': 'data/msrvtt_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'memory_dim': 256
},
'train': {
'batch_size': 64,
'reg_coeff': 1e-6,
'learning_rate': 0.001
}
}
}
},
'evqa': {
'msvd_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 4000,
'pretrained_embedding': 'data/msvd_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 32,
'reg_coeff': 1e-5,
'learning_rate': 0.001
}
}
},
'msrvtt_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 8000,
'pretrained_embedding': 'data/msrvtt_qa/word_embedding.npy',
'video_feature_dim': 4096,
'video_feature_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 64,
'reg_coeff': 1e-6,
'learning_rate': 0.001
}
}
}
},
'gra': {
'msvd_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 4000,
'pretrained_embedding': 'data/msvd_qa/word_embedding.npy',
'appear_dim': 4096,
'frame_num': 20,
'motion_dim': 4096,
'clip_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 32,
'reg_coeff': 1e-6,
'shu_coeff': 1e-5,
'learning_rate': 0.001
}
}
},
'msrvtt_qa': {
'0': {
'model': {
'word_dim': 300,
'vocab_num': 8000,
'pretrained_embedding': 'data/msrvtt_qa/word_embedding.npy',
'appear_dim': 4096,
'frame_num': 20,
'motion_dim': 4096,
'clip_num': 20,
'answer_num': 1000,
'common_dim': 256
},
'train': {
'batch_size': 64,
'reg_coeff': 1e-7,
'shu_coeff': 1e-7,
'learning_rate': 0.001
}
}
}
}
}
def get(model, dataset, config_id, gpu_list):
"""Generate configuration."""
config = {}
if dataset == 'msvd_qa':
config['preprocess_dir'] = 'data/msvd_qa'
elif dataset == 'msrvtt_qa':
config['preprocess_dir'] = 'data/msrvtt_qa'
config['model'] = CONFIG[model][dataset][config_id]['model']
config['train'] = CONFIG[model][dataset][config_id]['train']
sess_config = tf.ConfigProto()
sess_config.gpu_options.allow_growth = True
sess_config.gpu_options.visible_device_list = gpu_list
config['session'] = sess_config
return config