本文整理匯總了Python中tensorflow.python.ops.nn.pool方法的典型用法代碼示例。如果您正苦於以下問題：Python nn.pool方法的具體用法？Python nn.pool怎麽用？Python nn.pool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tensorflow.python.ops.nn的用法示例。
在下文中一共展示了nn.pool方法的1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: call
# 需要導入模塊: from tensorflow.python.ops import nn [as 別名]
# 或者: from tensorflow.python.ops.nn import pool [as 別名]
def call(self, inputs):
inputs = ops.convert_to_tensor(inputs, dtype=self.dtype)
ndim = self._input_rank
shape = self.gamma.get_shape().as_list()
gamma = array_ops.reshape(self.gamma, (ndim - 2) * [1] + shape)
# Compute normalization pool.
if self.data_format == 'channels_first':
norm_pool = nn.convolution(
math_ops.square(inputs),
gamma,
'VALID',
data_format='NC' + 'DHW' [-(ndim - 2):])
if ndim == 3:
norm_pool = array_ops.expand_dims(norm_pool, 2)
norm_pool = nn.bias_add(norm_pool, self.beta, data_format='NCHW')
norm_pool = array_ops.squeeze(norm_pool, [2])
elif ndim == 5:
shape = array_ops.shape(norm_pool)
norm_pool = array_ops.reshape(norm_pool, shape[:3] + [-1])
norm_pool = nn.bias_add(norm_pool, self.beta, data_format='NCHW')
norm_pool = array_ops.reshape(norm_pool, shape)
else: # ndim == 4
norm_pool = nn.bias_add(norm_pool, self.beta, data_format='NCHW')
else: # channels_last
norm_pool = nn.convolution(math_ops.square(inputs), gamma, 'VALID')
norm_pool = nn.bias_add(norm_pool, self.beta, data_format='NHWC')
norm_pool = math_ops.sqrt(norm_pool)
if self.inverse:
outputs = inputs * norm_pool
else:
outputs = inputs / norm_pool
outputs.set_shape(inputs.get_shape())
return outputs