本文整理汇总了Python中tensorflow.python.ops.nn.separable_conv2d方法的典型用法代码示例。如果您正苦于以下问题：Python nn.separable_conv2d方法的具体用法？Python nn.separable_conv2d怎么用？Python nn.separable_conv2d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.ops.nn的用法示例。
在下文中一共展示了nn.separable_conv2d方法的4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: call
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import separable_conv2d [as 别名]
def call(self, inputs):
# Apply the actual ops.
if self.data_format == 'channels_last':
strides = (1,) + self.strides + (1,)
else:
strides = (1, 1) + self.strides
outputs = nn.separable_conv2d(
inputs,
self.depthwise_kernel,
self.pointwise_kernel,
strides=strides,
padding=self.padding.upper(),
rate=self.dilation_rate,
data_format=utils.convert_data_format(self.data_format, ndim=4))
if self.use_bias:
outputs = nn.bias_add(
outputs,
self.bias,
data_format=utils.convert_data_format(self.data_format, ndim=4))
if self.activation is not None:
return self.activation(outputs)
return outputs 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:26，代码来源:convolutional.py
示例2: call
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import separable_conv2d [as 别名]
def call(self, inputs):
if self.data_format == 'channels_first':
# Reshape to channels last
inputs = array_ops.transpose(inputs, (0, 2, 3, 1))
# Apply the actual ops.
outputs = nn.separable_conv2d(
inputs,
self.depthwise_kernel,
self.pointwise_kernel,
strides=(1,) + self.strides + (1,),
padding=self.padding.upper(),
rate=self.dilation_rate)
if self.data_format == 'channels_first':
# Reshape to channels first
outputs = array_ops.transpose(outputs, (0, 3, 1, 2))
if self.bias is not None:
outputs = nn.bias_add(
outputs,
self.bias,
data_format=utils.convert_data_format(self.data_format, ndim=4))
if self.activation is not None:
return self.activation(outputs)
return outputs 示例3: call
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import separable_conv2d [as 别名]
def call(self, inputs):
if self.data_format == 'channels_first':
# Reshape to channels last
inputs = array_ops.transpose(inputs, (0, 2, 3, 1))
# Apply the actual ops.
outputs = nn.separable_conv2d(
inputs,
self.depthwise_kernel,
self.pointwise_kernel,
strides=(1,) + self.strides + (1,),
padding=self.padding.upper(),
rate=self.dilation_rate)
if self.data_format == 'channels_first':
# Reshape to channels first
outputs = array_ops.transpose(outputs, (0, 3, 1, 2))
if self.bias:
outputs = nn.bias_add(
outputs,
self.bias,
data_format=utils.convert_data_format(self.data_format, ndim=4))
if self.activation is not None:
return self.activation(outputs)
return outputs 示例4: separable_conv2d
# 需要导入模块: from tensorflow.python.ops import nn [as 别名]
# 或者: from tensorflow.python.ops.nn import separable_conv2d [as 别名]
def separable_conv2d(x,
depthwise_kernel,
pointwise_kernel,
strides=(1, 1),
padding='valid',
data_format=None,
dilation_rate=(1, 1)):
"""2D convolution with separable filters.
Arguments:
x: input tensor
depthwise_kernel: convolution kernel for the depthwise convolution.
pointwise_kernel: kernel for the 1x1 convolution.
strides: strides tuple (length 2).
padding: padding mode, "valid" or "same".
data_format: data format, "channels_first" or "channels_last".
dilation_rate: tuple of integers,
dilation rates for the separable convolution.
Returns:
Output tensor.
Raises:
ValueError: if `data_format` is neither `channels_last` or
`channels_first`.
"""
if data_format is None:
data_format = image_data_format()
if data_format not in {'channels_first', 'channels_last'}:
raise ValueError('Unknown data_format ' + str(data_format))
x = _preprocess_conv2d_input(x, data_format)
padding = _preprocess_padding(padding)
strides = (1,) + strides + (1,)
x = nn.separable_conv2d(
x,
depthwise_kernel,
pointwise_kernel,
strides=strides,
padding=padding,
rate=dilation_rate)
return _postprocess_conv2d_output(x, data_format)