本文整理汇总了Python中pylearn2.datasets.dense_design_matrix.DenseDesignMatrix.y_coarse方法的典型用法代码示例。如果您正苦于以下问题:Python DenseDesignMatrix.y_coarse方法的具体用法?Python DenseDesignMatrix.y_coarse怎么用?Python DenseDesignMatrix.y_coarse使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pylearn2.datasets.dense_design_matrix.DenseDesignMatrix
的用法示例。
在下文中一共展示了DenseDesignMatrix.y_coarse方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_split_nfold_datasets
# 需要导入模块: from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix [as 别名]
# 或者: from pylearn2.datasets.dense_design_matrix.DenseDesignMatrix import y_coarse [as 别名]
def test_split_nfold_datasets():
#Load and create ddm from cifar100
path = "/data/lisa/data/cifar100/cifar-100-python/train"
obj = serial.load(path)
X = obj['data']
assert X.max() == 255.
assert X.min() == 0.
X = np.cast['float32'](X)
y = None #not implemented yet
view_converter = DefaultViewConverter((32,32,3))
ddm = DenseDesignMatrix(X = X, y =y, view_converter = view_converter)
assert not np.any(np.isnan(ddm.X))
ddm.y_fine = np.asarray(obj['fine_labels'])
ddm.y_coarse = np.asarray(obj['coarse_labels'])
folds = ddm.split_dataset_nfolds(10)
print folds[0].shape
示例2: test_split_datasets
# 需要导入模块: from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix [as 别名]
# 或者: from pylearn2.datasets.dense_design_matrix.DenseDesignMatrix import y_coarse [as 别名]
def test_split_datasets():
#Load and create ddm from cifar100
path = "/data/lisa/data/cifar100/cifar-100-python/train"
obj = serial.load(path)
X = obj['data']
assert X.max() == 255.
assert X.min() == 0.
X = np.cast['float32'](X)
y = None #not implemented yet
view_converter = DefaultViewConverter((32,32,3))
ddm = DenseDesignMatrix(X = X, y =y, view_converter = view_converter)
assert not np.any(np.isnan(ddm.X))
ddm.y_fine = np.asarray(obj['fine_labels'])
ddm.y_coarse = np.asarray(obj['coarse_labels'])
(train, valid) = ddm.split_dataset_holdout(train_prop=0.5)
assert valid.shape[0] == np.ceil(ddm.num_examples * 0.5)
assert train.shape[0] == (ddm.num_examples - valid.shape[0])