本文整理匯總了Python中tensorflow.python.ops.gen_nn_ops._max_pool方法的典型用法代碼示例。如果您正苦於以下問題：Python gen_nn_ops._max_pool方法的具體用法？Python gen_nn_ops._max_pool怎麽用？Python gen_nn_ops._max_pool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.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: max_pool
# 需要導入模塊: from tensorflow.python.ops import gen_nn_ops [as 別名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 別名]
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
# 需要導入模塊: from tensorflow.python.ops import gen_nn_ops [as 別名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 別名]
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
# 需要導入模塊: from tensorflow.python.ops import gen_nn_ops [as 別名]
# 或者: from tensorflow.python.ops.gen_nn_ops import _max_pool [as 別名]
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) 開發者ID:PacktPublishing，項目名稱:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代碼行數:28，代碼來源:nn_ops.py