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#!/usr/bin/env python |
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# -*- coding: utf-8 -*- |
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from . import Dataset |
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import numpy as np |
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class MiniBatches(Dataset): |
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""" |
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Convert data into mini-batches. |
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""" |
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def __init__(self, dataset, batch_size=20, cache=True): |
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self.origin = dataset |
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self.size = batch_size |
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self._cached_train_set = None |
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self._cached_valid_set = None |
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self._cached_test_set = None |
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self.cache = cache |
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def _yield_data(self, subset): |
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if type(subset) != list: |
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subset = list(subset) |
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for i in xrange(0, len(subset), self.size): |
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yield map(np.array, list(zip(*subset[i:i + self.size]))) |
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def train_set(self): |
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if self.cache and self._cached_train_set is not None: |
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return self._cached_train_set |
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data_generator = self._yield_data(self.origin.train_set()) |
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if data_generator is None: |
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return None |
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if self.cache: |
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self._cached_train_set = list(data_generator) |
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return self._cached_train_set |
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else: |
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return data_generator |
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View Code Duplication |
def test_set(self): |
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if not self.origin.test_set(): |
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return None |
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if self.cache and self._cached_test_set is not None: |
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return self._cached_test_set |
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data_generator = self._yield_data(self.origin.test_set()) |
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if data_generator is None: |
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return None |
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if self.cache: |
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self._cached_test_set = list(data_generator) |
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return self._cached_test_set |
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else: |
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return data_generator |
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View Code Duplication |
def valid_set(self): |
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if not self.origin.valid_set(): |
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return None |
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if self.cache and self._cached_valid_set is not None: |
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return self._cached_valid_set |
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data_generator = self._yield_data(self.origin.valid_set()) |
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if data_generator is None: |
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return None |
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if self.cache: |
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self._cached_valid_set = list(data_generator) |
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return self._cached_valid_set |
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else: |
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return data_generator |
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def train_size(self): |
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train_size = self.origin.train_size() |
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if train_size is None: |
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train_size = len(list(self.origin.train_set())) |
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return train_size / self.size |
zomux /
deepy
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