47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
from os.path import isfile
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from typing import *
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from precise.functions import load_keras, false_pos, false_neg, weighted_log_loss
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from precise.params import inject_params
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lstm_units = 20
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def load_precise_model(model_name: str) -> Any:
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"""Loads a Keras model from file, handling custom loss function"""
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if not model_name.endswith('.net'):
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print('Warning: Unknown model type, ', model_name)
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inject_params(model_name)
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return load_keras().models.load_model(model_name)
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def create_model(model_name: str, skip_acc: bool = False) -> Any:
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"""
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Load or create a precise model
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Args:
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model_name: Name of model
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skip_acc: Whether to skip accuracy calculation while training
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Returns:
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model: Loaded Keras model
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"""
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if isfile(model_name):
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print('Loading from ' + model_name + '...')
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model = load_precise_model(model_name)
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else:
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from keras.layers.core import Dense
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from keras.layers.recurrent import GRU
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from keras.models import Sequential
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model = Sequential()
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model.add(GRU(lstm_units, activation='linear', input_shape=(pr.n_features, pr.feature_size),
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dropout=0.3, name='net'))
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model.add(Dense(1, activation='sigmoid'))
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load_keras()
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metrics = ['accuracy', false_pos, false_neg]
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model.compile('rmsprop', weighted_log_loss, metrics=(not skip_acc) * metrics)
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return model
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