mirror of https://github.com/coqui-ai/TTS.git
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
import unittest
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import torch as T
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from utils.generic_utils import save_checkpoint, save_best_model
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from layers.tacotron import Prenet, CBHG, Decoder, Encoder
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OUT_PATH = '/tmp/test.pth.tar'
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class ModelSavingTests(unittest.TestCase):
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def save_checkpoint_test(self):
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# create a dummy model
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model = Prenet(128, out_features=[256, 128])
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model = T.nn.DataParallel(layer)
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# save the model
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save_checkpoint(model, None, 100, OUTPATH, 1, 1)
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# load the model to CPU
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model_dict = torch.load(
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MODEL_PATH, map_location=lambda storage, loc: storage)
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model.load_state_dict(model_dict['model'])
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def save_best_model_test(self):
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# create a dummy model
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model = Prenet(256, out_features=[256, 256])
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model = T.nn.DataParallel(layer)
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# save the model
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best_loss = save_best_model(model, None, 0, 100, OUT_PATH, 10, 1)
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# load the model to CPU
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model_dict = torch.load(
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MODEL_PATH, map_location=lambda storage, loc: storage)
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model.load_state_dict(model_dict['model'])
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