| op { |
| graph_op_name: "ArgMin" |
| in_arg { |
| name: "dimension" |
| description: <<END |
| int32 or int64, must be in the range `[-rank(input), rank(input))`. |
| Describes which dimension of the input Tensor to reduce across. For vectors, |
| use dimension = 0. |
| END |
| } |
| summary: "Returns the index with the smallest value across dimensions of a tensor." |
| description: <<END |
| Note that in case of ties the identity of the return value is not guaranteed. |
| |
| Usage: |
| ```python |
| import tensorflow as tf |
| a = [1, 10, 26.9, 2.8, 166.32, 62.3] |
| b = tf.math.argmin(input = a) |
| c = tf.keras.backend.eval(b) |
| # c = 0 |
| # here a[0] = 1 which is the smallest element of a across axis 0 |
| ``` |
| END |
| } |
