tf.keras.ops.argsort
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Returns the indices that would sort a tensor.
tf.keras.ops.argsort(
x, axis=-1
)
Args |
|---|
x
|
Input tensor.
|
axis
|
Axis along which to sort. Defaults to-1 (the last axis). If
None, the flattened tensor is used.
|
Returns |
|---|
Tensor of indices that sort x along the specified axis.
|
Examples:
One dimensional array:
x = keras.ops.array([3, 1, 2])
keras.ops.argsort(x)
array([1, 2, 0], dtype=int32)
Two-dimensional array:
>>> x = keras.ops.array([[0, 3], [3, 2], [4, 5]])
>>> x
array([[0, 3],
[3, 2],
[4, 5]], dtype=int32)
>>> keras.ops.argsort(x, axis=0)
array([[0, 1],
[1, 0],
[2, 2]], dtype=int32)
>>> keras.ops.argsort(x, axis=1)
array([[0, 1],
[1, 0],
[0, 1]], dtype=int32)
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.ops.argsort\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/ops/numpy.py#L937-L972) |\n\nReturns the indices that would sort a tensor.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.ops.numpy.argsort`](https://www.tensorflow.org/api_docs/python/tf/keras/ops/argsort)\n\n\u003cbr /\u003e\n\n tf.keras.ops.argsort(\n x, axis=-1\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|-----------------------------------------------------------------------------------------------------|\n| `x` | Input tensor. |\n| `axis` | Axis along which to sort. Defaults to`-1` (the last axis). If `None`, the flattened tensor is used. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| Tensor of indices that sort `x` along the specified `axis`. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n#### One dimensional array:\n\n x = keras.ops.array([3, 1, 2])\n keras.ops.argsort(x)\n array([1, 2, 0], dtype=int32)\n\nTwo-dimensional array: \n\n \u003e\u003e\u003e x = keras.ops.array([[0, 3], [3, 2], [4, 5]])\n \u003e\u003e\u003e x\n array([[0, 3],\n [3, 2],\n [4, 5]], dtype=int32)\n \u003e\u003e\u003e keras.ops.argsort(x, axis=0)\n array([[0, 1],\n [1, 0],\n [2, 2]], dtype=int32)\n \u003e\u003e\u003e keras.ops.argsort(x, axis=1)\n array([[0, 1],\n [1, 0],\n [0, 1]], dtype=int32)"]]
View source on GitHub