本文整理汇总了Python中tensorflow.python.ops.gen_nn_ops._max_pool方法的典型用法代码示例。如果您正苦于以下问题：Python gen_nn_ops._max_pool方法的具体用法？Python gen_nn_ops._max_pool怎么用？Python gen_nn_ops._max_pool使用的例子？那么恭喜您, 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.gen_nn_ops的用法示例。
在下文中一共展示了gen_nn_ops._max_pool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: max_pool
# 需要导入模块: from tensorflow.python.ops import gen_nn_ops [as 别名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 别名]
def max_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
"""Performs the max pooling on the input.
Args:
value: A 4-D `Tensor` with shape `[batch, height, width, channels]` and
type `tf.float32`.
ksize: A list of ints that has length >= 4. The size of the window for
each dimension of the input tensor.
strides: A list of ints that has length >= 4. The stride of the sliding
window for each dimension of the input tensor.
padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
See the @{tf.nn.convolution$comment here}
data_format: A string. 'NHWC' and 'NCHW' are supported.
name: Optional name for the operation.
Returns:
A `Tensor` with type `tf.float32`. The max pooled output tensor.
"""
with ops.name_scope(name, "MaxPool", [value]) as name:
value = ops.convert_to_tensor(value, name="input")
return gen_nn_ops._max_pool(value,
ksize=ksize,
strides=strides,
padding=padding,
data_format=data_format,
name=name) 示例2: max_pool
# 需要导入模块: from tensorflow.python.ops import gen_nn_ops [as 别名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 别名]
def max_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
"""Performs the max pooling on the input.
Args:
value: A 4-D `Tensor` with shape `[batch, height, width, channels]` and
type `tf.float32`.
ksize: A list of ints that has length >= 4. The size of the window for
each dimension of the input tensor.
strides: A list of ints that has length >= 4. The stride of the sliding
window for each dimension of the input tensor.
padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
See the [comment here](https://www.tensorflow.org/api_docs/python/nn.html#convolution)
data_format: A string. 'NHWC' and 'NCHW' are supported.
name: Optional name for the operation.
Returns:
A `Tensor` with type `tf.float32`. The max pooled output tensor.
"""
with ops.name_scope(name, "MaxPool", [value]) as name:
value = ops.convert_to_tensor(value, name="input")
return gen_nn_ops._max_pool(value,
ksize=ksize,
strides=strides,
padding=padding,
data_format=data_format,
name=name) 示例3: max_pool
# 需要导入模块: from tensorflow.python.ops import gen_nn_ops [as 别名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 别名]
def max_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
"""Performs the max pooling on the input.
Args:
value: A 4-D `Tensor` of the format specified by `data_format`.
ksize: A 1-D int Tensor of 4 elements. The size of the window for
each dimension of the input tensor.
strides: A 1-D int Tensor of 4 elements. The stride of the sliding
window for each dimension of the input tensor.
padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
See the @{tf.nn.convolution$comment here}
data_format: A string. 'NHWC', 'NCHW' and 'NCHW_VECT_C' are supported.
name: Optional name for the operation.
Returns:
A `Tensor` of format specified by `data_format`.
The max pooled output tensor.
"""
with ops.name_scope(name, "MaxPool", [value]) as name:
value = ops.convert_to_tensor(value, name="input")
return gen_nn_ops._max_pool(value,
ksize=ksize,
strides=strides,
padding=padding,
data_format=data_format,
name=name) 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:28，代码来源:nn_ops.py