66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
"""Model trainers."""
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import time
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import logging
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from collections import OrderedDict
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logger = logging.getLogger(__name__)
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class Trainer(object):
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def __init__(self, model, cost, learning_rule, train_dataset,
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valid_dataset=None):
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self.model = model
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self.cost = cost
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self.learning_rule = learning_rule
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self.learning_rule.initialise(self.model.params)
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self.train_dataset = train_dataset
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self.valid_dataset = valid_dataset
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def do_training_epoch(self):
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for inputs_batch, targets_batch in self.train_dataset:
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activations = self.model.fprop(inputs_batch)
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grads_wrt_outputs = self.cost.grad(activations[-1], targets_batch)
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grads_wrt_params = self.model.grads_wrt_params(
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activations, grads_wrt_outputs)
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self.learning_rule.update_params(grads_wrt_params)
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self.train_dataset.reset()
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def data_cost(self, dataset):
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cost = 0.
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for inputs_batch, targets_batch in dataset:
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activations = self.model.fprop(inputs_batch)
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cost += self.cost(activations[-1], targets_batch)
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dataset.reset()
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return cost
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def get_epoch_stats(self):
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epoch_stats = OrderedDict()
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epoch_stats['cost(train)'] = self.data_cost(
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self.train_dataset)
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epoch_stats['cost(valid)'] = self.data_cost(
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self.valid_dataset)
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epoch_stats['cost(param)'] = self.model.params_cost()
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return epoch_stats
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def log_stats(self, epoch, stats):
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logger.info('Epoch {0}: {1}'.format(
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epoch,
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', '.join(['{0}={1:.3f}'.format(k, v) for (k, v) in stats.items()])
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))
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def train(self, n_epochs, stats_interval=5):
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run_stats = []
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for epoch in range(n_epochs):
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start_time = time.clock()
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self.do_training_epoch()
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epoch_time = time.clock() - start_time
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if epoch % stats_interval == 0:
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stats = self.get_epoch_stats()
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stats['time'] = epoch_time
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self.log_stats(epoch, stats)
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run_stats.append(stats.items())
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return np.array(run_stats), stats.keys()
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