tf.dynamic_partition是TensorFlow中的一个函数,用于根据给定的分区索引将输入张量划分为多个分区。在PyTorch中,对应的等效项是torch.split函数。 torch...
one_hot_new_3 = tf.dynamic_partition(one_hot_new, [1,1,0],2)[0]# 按照每一维大小进行拆分one_hot_1 = tf.dynamic_partition(one_hot_new, [0,1,2],3)[0] one_hot_2 = tf.dynamic_partition(one_hot_new, [0,1,2],3)[1] one_hot_3 = tf.dynamic_partition(one_hot_new, [0,1...
tf.dynamic_partition( data, partitions, num_partitions, name=None ) For each index tuple js of size partitions.ndim, the slice data[js, ...] becomes part of outputs[partitions[js]]. The slices with partitions[js] = i are placed in outputs[i] in lexicographic order of js, and the fi...
partitioned_data[1] = partitioned_data[1] + 1.0 #这行代码是提取索引位置 condition_indices = tf.dynamic_partition( tf.range(tf.shape(x)[0]), tf.cast(condition_mask, tf.int32) , 2) x = tf.dynamic_stitch(condition_indices, partitioned_data) # Here x=[1.1, -1., 6.2, 5.3, -1,...
tf.compat.v2.dynamic_partition tf.dynamic_partition( data, partitions, num_partitions, name=None ) 1. 2. 3. 4. 5. 6. For each index tuplejsof sizepartitions.ndim, the slicedata[js, ...]becomes part ofoutputs[partitions[js]]. The slices withpartitions[js] = iare placed inoutputs[...
Tensorflow tf.dynamic_partition矩阵拆分示例(Python3) 先给出一个样例看看 import tensorflow as tf raw = tf.constant([1, 2, 3, 4, 5, 6, 6, 5, 4, 3, 2, 1]) ''' 拆成 [1,2] [3,4] [5,6] [6,5] [4,3] [2,1] ''' result_1 = tf.dynamic_partition(tf.reshape(raw, [...
Tensorflowtf.dynamic_partition矩阵拆分⽰例（Python3）先给出⼀个样例看看 import tensorflow as tf raw = tf.constant([1, 2, 3, 4, 5, 6, 6, 5, 4, 3, 2, 1])'''拆成 [1,2] [3,4] [5,6] [6,5] [4,3] [2,1]'''result_1 = tf.dynamic_partition(tf.reshape(raw, [6,2...
【Tensorflow】tf.dynamic_partition 函数 分拆数组 原生接口实例 【Tensorflow】实现简单的卷积神经网络CNN实际代码 【Tensorflow 实战】实现欧式距离 slim接口文章 【Tensorflow】tensorflow.contrib.slim 包 【Tensorflow slim】 slim.arg_scope的用法 【Tensorflow slim】slim.data包 ...
x = tf.dynamic_stitch(condition_indices, partitioned_data) # Here x=[1.1, -1., 6.2, 5.3, -1, 8.4], the -1. values remain # unchanged. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 参数: indices:包含至少一个int32类型张量对象的列表。
reduce_sum貌似不能对各个维度加权,用笨办法:将Tensor按通道拆分,再把前两个拼接起来,再用reduce_sum。 tf.dynamic_partition() 可以用tf.dynamic_partition,以下是官方文档的笔记: tf.split() 也可以用tf.split(value, num_or_size_splits, axis=0, num=None, name='split'),更加简便: 基本的使用方法是...