질문이있다? TensorFlow 포럼 에서 커뮤니티와 연결

# tf.math.argmin

Returns the index with the smallest value across axes of a tensor.

Note that in case of ties the identity of the return value is not guaranteed.

`input` A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`.
`axis` A `Tensor`. Must be one of the following types: `int32`, `int64`. int32 or int64, must be in the range `-rank(input), rank(input))`. Describes which axis of the input Tensor to reduce across. For vectors, use axis = 0.
`output_type` An optional `tf.DType` from: `tf.int32, tf.int64`. Defaults to `tf.int64`.
`name` A name for the operation (optional).

A `Tensor` of type `output_type`.

#### Usage:

``````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
``````
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