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Python utils.normalize_data_format方法代碼示例

本文整理匯總了Python中tensorflow.python.layers.utils.normalize_data_format方法的典型用法代碼示例。如果您正苦於以下問題：Python utils.normalize_data_format方法的具體用法？Python utils.normalize_data_format怎麽用？Python utils.normalize_data_format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.layers.utils的用法示例。


在下文中一共展示了utils.normalize_data_format方法的6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: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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)
開發者ID:ryfeus，項目名稱:lambda-packs，代碼行數:12，代碼來源:pooling.py

示例2: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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)
開發者ID:ryfeus，項目名稱:lambda-packs，代碼行數:37，代碼來源:convolutional.py

示例3: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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)
開發者ID:abhisuri97，項目名稱:auto-alt-text-lambda-api，代碼行數:11，代碼來源:pooling.py

示例4: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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
開發者ID:abhisuri97，項目名稱:auto-alt-text-lambda-api，代碼行數:36，代碼來源:convolutional.py

示例5: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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)
開發者ID:PacktPublishing，項目名稱:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代碼行數:41，代碼來源:convolutional.py

示例6: __init__

# 需要導入模塊: from tensorflow.python.layers import utils [as 別名]
# 或者: from tensorflow.python.layers.utils import normalize_data_format [as 別名]
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)
開發者ID:mauriceqch，項目名稱:pcc_geo_cnn，代碼行數:44，代碼來源:signal_conv.py


注：本文中的tensorflow.python.layers.utils.normalize_data_format方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。