Returns the index with the smallest value across dimensions of a tensor.
Note that in case of ties the identity of the return value is not guaranteed.
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
Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
Output<V> |
asOutput()
Returns the symbolic handle of the tensor.
|
static <V extends TNumber> ArgMin<V> | |
static ArgMin<TInt64> | |
Output<V> |
output()
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public Output<V> asOutput ()
Returns the symbolic handle of the tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static ArgMin<V> create (Scope scope, Operand<? extends TType> input, Operand<? extends TNumber> dimension, Class<V> outputType)
Factory method to create a class wrapping a new ArgMin operation.
Parameters
scope | current scope |
---|---|
dimension | 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. |
Returns
- a new instance of ArgMin
public static ArgMin<TInt64> create (Scope scope, Operand<? extends TType> input, Operand<? extends TNumber> dimension)
Factory method to create a class wrapping a new ArgMin operation using default output types.
Parameters
scope | current scope |
---|---|
dimension | 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. |
Returns
- a new instance of ArgMin