深入浅出TensorFlow2函数——tf.exp

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· 深入浅出TensorFlow2函数——tf.exp
· 深入浅出TensorFlow2函数——tf.math.exp
· 深入浅出Pytorch函数——torch.exp
· 深入浅出PaddlePaddle函数——paddle.exp

按元素计算

     x 
    
   
  
    x 
   
  
x的指数 
 
  
   
   
     y 
    
   
     = 
    
    
    
      e 
     
    
      x 
     
    
   
  
    y=e^x 
   
  
y=ex。

语法

tf.exp(
    x, name=None
)

参数

• x：[tf.Tensor] 必须是以下类型之一：bfloat16、half、float32、float64、complex64、complex128。
• name：[可选] 操作的名称。

返回值

一个与

x

类型相同的

tf.Tensor

。

实例

输入：

x = tf.constant([2.0,8.0])
tf.exp(x)

输出：

<tf.Tensor: shape=(2,), dtype=float32, numpy=array([7.389056,2980.958], dtype=float32)>

函数实现

@tf_export("math.exp","exp")
@dispatch.register_unary_elementwise_api
@dispatch.add_dispatch_support
def exp(x, name=None):
  r"""Computes exponential of x element-wise.  \\(y = e^x\\).
  This function computes the exponential of the input tensor element-wise.
  i.e. `math.exp(x)` or \\(e^x\\), where `x` is the input tensor.
  \\(e\\) denotes Euler's number and is approximately equal to 2.718281.
  Output is positive for any real input.>>> x = tf.constant(2.0)>>> tf.math.exp(x)<tf.Tensor: shape=(), dtype=float32, numpy=7.389056>>>> x = tf.constant([2.0,8.0])>>> tf.math.exp(x)<tf.Tensor: shape=(2,), dtype=float32,
  numpy=array([7.389056,2980.958], dtype=float32)>
  For complex numbers, the exponential value is calculated as
  $$
  e^{x+iy}={e^x}{e^{iy}}={e^x}({\cos(y)+ i \sin(y)})
  $$
  For `1+1j` the value would be computed as:
  $$
  e^1(\cos(1)+ i \sin(1))=2.7182817 \times(0.5403023+0.84147096j)
  $$
  >>> x = tf.constant(1+1j)>>> tf.math.exp(x)<tf.Tensor: shape=(), dtype=complex128,
  numpy=(1.4686939399158851+2.2873552871788423j)>
  Args:
    x: A `tf.Tensor`. Must be one of the following types: `bfloat16`, `half`,
      `float32`, `float64`, `complex64`, `complex128`.
    name: A name for the operation(optional).
  Returns:
    A `tf.Tensor`. Has the same type as `x`.
  @compatibility(numpy)
  Equivalent to np.exp
  @end_compatibility
  """
  return gen_math_ops.exp(x, name)