tf.convert_to_tensor(value,dtype=None,dtype_hint=None,name=None) 该函数将各种类型的Python对象转换为张量对象。它接受张量对象、数字数组、Python列表和Python标量。 例: 代码语言:javascript 复制 importnumpyasnp defmy_func(arg):arg=tf.convert_to_tensor(arg,dtype=tf.float32)returntf.matmul(arg,arg)...
convert_to_tensor(self.label_list, dtype=tf.string) 这里的read_labeled_image_list是用来读取图像和标签的路径的,返回两个list。 打上断点,看这两句话执行之后的效果。 tf.convert_to_tensor()执行后返回一个Tensor,问题是,这个Tensor是什么样子的? 在TF的Graph中,Tensor是边,Op是点,TensorFlow将Tensor与对应...
tf.convert_to_tensor()执行后返回一个Tensor,问题是,这个Tensor是什么样子的? 在TF的Graph中,Tensor是边,Op是点,TensorFlow将Tensor与对应的Op的关系描述为“The Operation that produces this tensor as an output.” 我们可以看到这个Tensor的Op是谁: name:"create_inputs/Const"op:"Const"attr{key:"dtype"v...
简介:【8月更文挑战第11天】利用tf.convert_to_tensor转换为类型。 从numpy,list对象创建,再利用tf.convert_to_tensor转换为类型。 将给定制转换为张量。可利用这个函数将python的数据类型转换成TensorFlow可用的tensor数据类型。 tf.convert_to_tensor(value,dtype=None,dtype_hint=None,name=None): value:需...
Convertthegivenvaluetoatensor. Examples: x=tf.convert_to_tensor([1,2])y=tf.constant([1,2])# Equivalent Parameters: value(Union[number,Sequence,numpy.ndarray])–Thevaluetoconvert. dtype(str,optional)–Theoptionaldatatype. name(str,optional)–TheOptionalname. ...
#将python的数据类型(列表和矩阵)转换成TensorFlow可用的tensor数据类型 import tensorflow as tf import numpy as np A = [1,2,3] B = np.array([1,2,3]) C = tf.convert_to_tensor(A
tf.convert_to_tensor import tensorflow as tf import numpy as np def my_func(arg):arg= tf.convert_to_tensor(arg, dtype=tf.float32)returnarg# The following calls are equivalent. value_1 = my_func(tf.constant([[1.0, 2.0], [3.0, 4.0]]))print(value_1)...
tf.convert_to_tensor(value,dtype=None,name=None,preferred_dtype=None) 参数: value 类型具有注册张量转换函数的对象。 dtype 返回张量的可选元素类型。如果缺少,则从值的类型推断类型。 name 创建新张量时使用的可选名称。 preferred_dtype 返回张量的可选元素类型,当dtype为None时使用。在某些情况下,调用者在...
import numpy.random as npr import tensorflow as tf with tf.device("GPU"): A=tf.convert_to_tensor(npr.randn(500)) will create an eager tensor A on the CPU device (it will not allocate ram on the gpu). This is counter-intuitive to someone who has only read the doc as it is writ...
TensorFlow has a function calledtf.convert_to_tensorthat takes the value and converts that value into tensor objects. Create a dictionary named city_population, as shown below. import tensorflow as tf city_population = {'Los Angeles': 3748640, 'Chicago': 2590002, 'Houston': 2305889} ...