Python – tensorflow.math.ceil()

TensorFlow 是由 Google 设计的开源Python库，用于开发机器学习模型和深度学习神经网络。 ceil()用于查找输入的元素 ceil 值。

Syntax: tensorflow.math.ceil( x, name)

Parameters:
 

• x: It’s a tensor and allowed dtype for this tensor are  bfloat16, half, float32, float64. int32.
• name: It’s an optional argument that defines the name for the operation.
   

Returns:
It returns a tensor of same dtype as x.
 

示例 1：

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([1.5, 2.7, 3.9, 1.2, 1.8], dtype = tf.float64)
 
# printing the input
print('a: ',a)
 
# Finding the ceil value
r = tf.math.ceil(a)
 
# printing the result
print("Result: ",r)

输出：

a:  tf.Tensor([1.5 2.7 3.9 1.2 1.8], shape=(5,), dtype=float64)
Result:  tf.Tensor([2. 3. 4. 2. 2.], shape=(5,), dtype=float64)

示例 2：在此示例中，使用了 2-D 张量。

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([[1.5, 2.7], [3.9, 1.2]], dtype = tf.float64)
 
# printing the input
print('a: ',a)
 
# Finding the ceil value
r = tf.math.ceil(a)
 
# printing the result
print('Result: ',r)

输出：

a:  tf.Tensor(
[[1.5 2.7]
 [3.9 1.2]], shape=(2, 2), dtype=float64)
Result:  tf.Tensor(
[[2. 3.]
 [4. 2.]], shape=(2, 2), dtype=float64)

示例 3：在此示例中，使用了无效的 dtype 张量。它将引发 NotFoundError。

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([1.5, 2.7, 3.9, 1.2, 1.8], dtype = tf.complex128)
 
# printing the input
print('a: ',a)
 
# Finding the ceil value
r = tf.math.ceil(a)

输出：

a:  tf.Tensor([1.5+0.j 2.7+0.j 3.9+0.j 1.2+0.j 1.8+0.j], shape=(5,), dtype=complex128)

---------------------------------------------------------------------------

NotFoundError                             Traceback (most recent call last)

 in ()
      6 
      7 # Finding the ceil value
----> 8 r = tf.math.ceil(a)

4 frames

/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)

NotFoundError: Could not find valid device for node.
Node:{{node Ceil}}
All kernels registered for op Ceil :
  device='XLA_GPU'; T in [DT_FLOAT, DT_DOUBLE, DT_BFLOAT16, DT_HALF]
  device='XLA_CPU'; T in [DT_FLOAT, DT_DOUBLE, DT_BFLOAT16, DT_HALF]
  device='XLA_CPU_JIT'; T in [DT_FLOAT, DT_DOUBLE, DT_BFLOAT16, DT_HALF]
  device='XLA_GPU_JIT'; T in [DT_FLOAT, DT_DOUBLE, DT_BFLOAT16, DT_HALF]
  device='GPU'; T in [DT_DOUBLE]
  device='GPU'; T in [DT_HALF]
  device='GPU'; T in [DT_FLOAT]
  device='CPU'; T in [DT_DOUBLE]
  device='CPU'; T in [DT_HALF]
  device='CPU'; T in [DT_FLOAT]
 [Op:Ceil]