本文整理匯總了Python中mxnet.ndarray.swapaxes方法的典型用法代碼示例。如果您正苦於以下問題：Python ndarray.swapaxes方法的具體用法？Python ndarray.swapaxes怎麽用？Python ndarray.swapaxes使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類mxnet.ndarray的用法示例。
在下文中一共展示了ndarray.swapaxes方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: subtract_imagenet_mean_batch
# 需要導入模塊: from mxnet import ndarray [as 別名]
# 或者: from mxnet.ndarray import swapaxes [as 別名]
def subtract_imagenet_mean_batch(batch):
"""Subtract ImageNet mean pixel-wise from a BGR image."""
batch = F.swapaxes(batch,0, 1)
(r, g, b) = F.split(batch, num_outputs=3, axis=0)
r = r - 123.680
g = g - 116.779
b = b - 103.939
batch = F.concat(r, g, b, dim=0)
batch = F.swapaxes(batch,0, 1)
return batch 示例2: subtract_imagenet_mean_preprocess_batch
# 需要導入模塊: from mxnet import ndarray [as 別名]
# 或者: from mxnet.ndarray import swapaxes [as 別名]
def subtract_imagenet_mean_preprocess_batch(batch):
"""Subtract ImageNet mean pixel-wise from a BGR image."""
batch = F.swapaxes(batch,0, 1)
(r, g, b) = F.split(batch, num_outputs=3, axis=0)
r = r - 123.680
g = g - 116.779
b = b - 103.939
batch = F.concat(b, g, r, dim=0)
batch = F.swapaxes(batch,0, 1)
return batch 示例3: add_imagenet_mean_batch
# 需要導入模塊: from mxnet import ndarray [as 別名]
# 或者: from mxnet.ndarray import swapaxes [as 別名]
def add_imagenet_mean_batch(batch):
batch = F.swapaxes(batch,0, 1)
(b, g, r) = F.split(batch, num_outputs=3, axis=0)
r = r + 123.680
g = g + 116.779
b = b + 103.939
batch = F.concat(b, g, r, dim=0)
batch = F.swapaxes(batch,0, 1)
"""
batch = denormalizer(batch)
"""
return batch 示例4: preprocess_batch
# 需要導入模塊: from mxnet import ndarray [as 別名]
# 或者: from mxnet.ndarray import swapaxes [as 別名]
def preprocess_batch(batch):
batch = F.swapaxes(batch, 0, 1)
(r, g, b) = F.split(batch, num_outputs=3, axis=0)
batch = F.concat(b, g, r, dim=0)
batch = F.swapaxes(batch, 0, 1)
return batch 示例5: swapaxes
# 需要導入模塊: from mxnet import ndarray [as 別名]
# 或者: from mxnet.ndarray import swapaxes [as 別名]
def swapaxes(input, axis1, axis2):
return nd.swapaxes(input, axis1, axis2)