Python – tensorflow.math.ceil()

TensorFlow是谷歌设计的开源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明智的ceil值。

语法: tensorflow.math.ceil( x, name)

参数:

x:它是一个张量，这个张量允许的dtype是bfloat16, half, float32, float64。
name: 这是一个可选的参数，定义了操作的名称。

返回值:
它返回一个与x具有相同dtype的张量。

示例 1:

# 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)

例子2：在这个例子中使用了二维张量。

# 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)

例子3：在这个例子中使用了无效的dtype张量。它将引发NotFoundError。

# 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)

<ipython-input-49-e349e3adf9c3> in <module>()
      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]