本文整理汇总了Python中tensorflow.python.layers.utils.normalize_tuple方法的典型用法代码示例。如果您正苦于以下问题：Python utils.normalize_tuple方法的具体用法？Python utils.normalize_tuple怎么用？Python utils.normalize_tuple使用的例子？那么, 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tensorflow.python.layers.utils的用法示例。
在下文中一共展示了utils.normalize_tuple方法的6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: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, pool_function, pool_size, strides,
padding='valid', data_format='channels_last',
name=None, **kwargs):
super(_Pooling1D, self).__init__(name=name, **kwargs)
self.pool_function = pool_function
self.pool_size = utils.normalize_tuple(pool_size, 1, 'pool_size')
self.strides = utils.normalize_tuple(strides, 1, 'strides')
self.padding = utils.normalize_padding(padding)
self.data_format = utils.normalize_data_format(data_format)
self.input_spec = base.InputSpec(ndim=3) 示例2: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, rank,
filters,
kernel_size,
strides=1,
padding='valid',
data_format='channels_last',
dilation_rate=1,
activation=None,
use_bias=True,
kernel_initializer=None,
bias_initializer=init_ops.zeros_initializer(),
kernel_regularizer=None,
bias_regularizer=None,
activity_regularizer=None,
trainable=True,
name=None,
**kwargs):
super(_Conv, self).__init__(trainable=trainable,
name=name, **kwargs)
self.rank = rank
self.filters = filters
self.kernel_size = utils.normalize_tuple(kernel_size, rank, 'kernel_size')
self.strides = utils.normalize_tuple(strides, rank, 'strides')
self.padding = utils.normalize_padding(padding)
self.data_format = utils.normalize_data_format(data_format)
self.dilation_rate = utils.normalize_tuple(
dilation_rate, rank, 'dilation_rate')
self.activation = activation
self.use_bias = use_bias
self.kernel_initializer = kernel_initializer
self.bias_initializer = bias_initializer
self.kernel_regularizer = kernel_regularizer
self.bias_regularizer = bias_regularizer
self.activity_regularizer = activity_regularizer
self.input_spec = base.InputSpec(ndim=self.rank + 2) 示例3: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, pool_function, pool_size, strides,
padding='valid', data_format='channels_last',
name=None, **kwargs):
super(_Pooling1D, self).__init__(name=name, **kwargs)
self.pool_function = pool_function
self.pool_size = utils.normalize_tuple(pool_size, 1, 'pool_size')
self.strides = utils.normalize_tuple(strides, 1, 'strides')
self.padding = utils.normalize_padding(padding)
self.data_format = utils.normalize_data_format(data_format) 示例4: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, rank,
filters,
kernel_size,
strides=1,
padding='valid',
data_format='channels_last',
dilation_rate=1,
activation=None,
use_bias=True,
kernel_initializer=None,
bias_initializer=init_ops.zeros_initializer(),
kernel_regularizer=None,
bias_regularizer=None,
activity_regularizer=None,
trainable=True,
name=None,
**kwargs):
super(_Conv, self).__init__(trainable=trainable,
name=name, **kwargs)
self.rank = rank
self.filters = filters
self.kernel_size = utils.normalize_tuple(kernel_size, rank, 'kernel_size')
self.strides = utils.normalize_tuple(strides, rank, 'strides')
self.padding = utils.normalize_padding(padding)
self.data_format = utils.normalize_data_format(data_format)
self.dilation_rate = utils.normalize_tuple(
dilation_rate, rank, 'dilation_rate')
self.activation = activation
self.use_bias = use_bias
self.kernel_initializer = kernel_initializer
self.bias_initializer = bias_initializer
self.kernel_regularizer = kernel_regularizer
self.bias_regularizer = bias_regularizer
self.activity_regularizer = activity_regularizer 示例5: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, rank,
filters,
kernel_size,
strides=1,
padding='valid',
data_format='channels_last',
dilation_rate=1,
activation=None,
use_bias=True,
kernel_initializer=None,
bias_initializer=init_ops.zeros_initializer(),
kernel_regularizer=None,
bias_regularizer=None,
activity_regularizer=None,
kernel_constraint=None,
bias_constraint=None,
trainable=True,
name=None,
**kwargs):
super(_Conv, self).__init__(trainable=trainable, name=name,
activity_regularizer=activity_regularizer,
**kwargs)
self.rank = rank
self.filters = filters
self.kernel_size = utils.normalize_tuple(kernel_size, rank, 'kernel_size')
self.strides = utils.normalize_tuple(strides, rank, 'strides')
self.padding = utils.normalize_padding(padding)
self.data_format = utils.normalize_data_format(data_format)
self.dilation_rate = utils.normalize_tuple(
dilation_rate, rank, 'dilation_rate')
self.activation = activation
self.use_bias = use_bias
self.kernel_initializer = kernel_initializer
self.bias_initializer = bias_initializer
self.kernel_regularizer = kernel_regularizer
self.bias_regularizer = bias_regularizer
self.kernel_constraint = kernel_constraint
self.bias_constraint = bias_constraint
self.input_spec = base.InputSpec(ndim=self.rank + 2) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:41，代码来源:convolutional.py
示例6: __init__
# 需要导入模块: from tensorflow.python.layers import utils [as 别名]
# 或者: from tensorflow.python.layers.utils import normalize_tuple [as 别名]
def __init__(self, rank, filters, kernel_support,
corr=False, strides_down=1, strides_up=1, padding="valid",
extra_pad_end=True, channel_separable=False,
data_format="channels_last",
activation=None, use_bias=False,
kernel_initializer=init_ops.VarianceScaling(),
bias_initializer=init_ops.Zeros(),
kernel_regularizer=None, bias_regularizer=None,
kernel_parameterizer=parameterizers.RDFTParameterizer(),
bias_parameterizer=None,
**kwargs):
super(_SignalConv, self).__init__(**kwargs)
self._rank = int(rank)
self._filters = int(filters)
self._kernel_support = utils.normalize_tuple(
kernel_support, self._rank, "kernel_support")
self._corr = bool(corr)
self._strides_down = utils.normalize_tuple(
strides_down, self._rank, "strides_down")
self._strides_up = utils.normalize_tuple(
strides_up, self._rank, "strides_up")
self._padding = str(padding).lower()
try:
self._pad_mode = {
"valid": None,
"same_zeros": "CONSTANT",
"same_reflect": "REFLECT",
}[self.padding]
except KeyError:
raise ValueError("Unsupported padding mode: '{}'".format(padding))
self._extra_pad_end = bool(extra_pad_end)
self._channel_separable = bool(channel_separable)
self._data_format = utils.normalize_data_format(data_format)
self._activation = activation
self._use_bias = bool(use_bias)
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._kernel_parameterizer = kernel_parameterizer
self._bias_parameterizer = bias_parameterizer
self.input_spec = base.InputSpec(ndim=self._rank + 2)