Rounding and Comparison Operations
| Function | Description |
round(x, name=None) |
Rounds to the nearest integer, rounding up if there are two nearest integers |
rint(x, name=None) |
Rounds to the nearest integer, rounding to the nearest even integer if there are two nearest integers |
ceil(x, name=None) |
Returns the smallest integer greater than the value |
floor(x, name=None) |
Returns the greatest integer less than the value |
maximum(x, y, name=None) |
Returns a tensor containing the larger element of each input tensor |
minimum(x, y, name=None) |
Returns a tensor containing the smaller element of each input tensor |
argmax(x, axis=None, name=None, dimension=None) |
Returns the index of the greatest element in the tensor |
argmin(x, axis=None, name=None, dimension=None) |
Returns the index of the smallest element in the tensor |
The round function examines each element of a tensor and returns the closest integer. If two closest integers are equally close, it returns the one further from zero. rint is similar, but rounds to the nearest even value. The following code demonstrates how you can use round, rint, ceil, and floor:
t = tf.constant([-6.5, -3.5, 3.5, 6.5])The next two functions in the table,r1 = tf.round(t) # [-6. -4. 4. 6.]
r2 = tf.rint(t) # [-6. -4. 4. 6.]
r3 = tf.ceil(t) # [-6. -3. 4. 7.]
r4 = tf.floor(t) # [-7. -4. 3. 6.]
maximum and minimum, are easy to understand. maximum returns a tensor containing the larger element of each input tensor, and minimum returns a tensor containing the smaller element of each input tensor.argmax and argmin return the index values of the largest and smallest elements of a tensor. The following code shows how you can use these functions:
t1 = tf.constant([0, -2, 4, 6])If a tensor has multiple maximum/minimum values,t2 = tf.constant([[1, 3], [7, 2]])
r1 = tf.argmin(t1) # 1
r2 = tf.argmax(t2) # [ 1 0 ]
argmax and argmin will return the index values of the first occurring element.