本文整理汇总了Python中tensorflow.python.ops.nn_ops.conv2d_backprop_filter方法的典型用法代码示例。如果您正苦于以下问题：Python nn_ops.conv2d_backprop_filter方法的具体用法？Python nn_ops.conv2d_backprop_filter怎么用？Python nn_ops.conv2d_backprop_filter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_ops的用法示例。
在下文中一共展示了nn_ops.conv2d_backprop_filter方法的3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: _Conv2DBackpropInputGrad
# 需要导入模块: from tensorflow.python.ops import nn_ops [as 别名]
# 或者: from tensorflow.python.ops.nn_ops import conv2d_backprop_filter [as 别名]
def _Conv2DBackpropInputGrad(op, grad):
"""The derivatives for deconvolution.
Args:
op: the Deconvolution op.
grad: the tensor representing the gradient w.r.t. the output
Returns:
the gradients w.r.t. the input and the filter
"""
return [None,
nn_ops.conv2d_backprop_filter(grad, array_ops.shape(op.inputs[1]),
op.inputs[2], op.get_attr("strides"),
op.get_attr("padding"),
op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format")),
nn_ops.conv2d(grad, op.inputs[1], op.get_attr("strides"),
op.get_attr("padding"), op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format"))] 示例2: _Conv2DGrad
# 需要导入模块: from tensorflow.python.ops import nn_ops [as 别名]
# 或者: from tensorflow.python.ops.nn_ops import conv2d_backprop_filter [as 别名]
def _Conv2DGrad(op, grad):
strides = op.get_attr("strides")
padding = op.get_attr("padding")
use_cudnn_on_gpu = op.get_attr("use_cudnn_on_gpu")
data_format = op.get_attr("data_format")
shape_0, shape_1 = array_ops.shape_n([op.inputs[0], op.inputs[1]])
return [nn_ops.conv2d_backprop_input(shape_0,
op.inputs[1],
grad,
strides,
padding,
use_cudnn_on_gpu,
data_format),
nn_ops.conv2d_backprop_filter(op.inputs[0],
shape_1,
grad,
strides,
padding,
use_cudnn_on_gpu,
data_format)] 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:22，代码来源:nn_grad.py
示例3: _Conv2DGrad
# 需要导入模块: from tensorflow.python.ops import nn_ops [as 别名]
# 或者: from tensorflow.python.ops.nn_ops import conv2d_backprop_filter [as 别名]
def _Conv2DGrad(op, grad):
return [nn_ops.conv2d_backprop_input(
array_ops.shape(op.inputs[0]), op.inputs[1], grad, op.get_attr("strides"),
op.get_attr("padding"), op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format")),
nn_ops.conv2d_backprop_filter(op.inputs[0],
array_ops.shape(op.inputs[1]), grad,
op.get_attr("strides"),
op.get_attr("padding"),
op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format"))]