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import sys |
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import os.path |
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import torch |
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code_path = os.path.dirname(os.path.abspath(__file__)) + '/' |
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sys.path.append(code_path) |
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import yaml |
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from ml_collections import ConfigDict |
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torch.set_float32_matmul_precision("medium") |
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def get_model( |
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config_path, |
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weights_path, |
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device, |
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): |
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from models.bandit.core.model import MultiMaskMultiSourceBandSplitRNNSimple |
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f = open(config_path) |
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config = ConfigDict(yaml.load(f, Loader=yaml.FullLoader)) |
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f.close() |
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model = MultiMaskMultiSourceBandSplitRNNSimple( |
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**config.model |
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) |
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d = torch.load(code_path + 'model_bandit_plus_dnr_sdr_11.47.chpt') |
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model.load_state_dict(d) |
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model.to(device) |
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return model, config |
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