@Namespace(value="tensorflow::ops") @NoOffset @Properties(inherit=tensorflow.class) public class ArgMin extends Pointer
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
Arguments:
* scope: A Scope object
* 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:
* Output
: The output tensor.Modifier and Type | Class and Description |
---|---|
static class |
ArgMin.Attrs
Optional attribute setters for ArgMin
|
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
---|
ArgMin(Pointer p)
Pointer cast constructor.
|
ArgMin(Scope scope,
Input input,
Input dimension) |
ArgMin(Scope scope,
Input input,
Input dimension,
ArgMin.Attrs attrs) |
Modifier and Type | Method and Description |
---|---|
Input |
asInput() |
Output |
asOutput() |
Node |
node() |
Operation |
operation() |
ArgMin |
operation(Operation setter) |
Output |
output() |
ArgMin |
output(Output setter) |
static ArgMin.Attrs |
OutputType(int x) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public ArgMin(Pointer p)
Pointer(Pointer)
.public Node node()
@ByVal public static ArgMin.Attrs OutputType(@Cast(value="tensorflow::DataType") int x)
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