tf.keras.ops.any
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Test whether any array element along a given axis evaluates to True.
tf.keras.ops.any(
x, axis=None, keepdims=False
)
Args |
|---|
x
|
Input tensor.
|
axis
|
An integer or tuple of integers that represent the axis along
which a logical OR reduction is performed. The default
(axis=None) is to perform a logical OR over all the dimensions
of the input array. axis may be negative, in which case it counts
for the last to the first axis.
|
keepdims
|
If True, axes which are reduced are left in the result as
dimensions with size one. With this option, the result will
broadcast correctly against the input array. Defaults to False.
|
Returns |
|---|
The tensor containing the logical OR reduction over the axis.
|
Examples:
x = keras.ops.convert_to_tensor([True, False])
keras.ops.any(x)
array(True, shape=(), dtype=bool)
x = keras.ops.convert_to_tensor([[True, False], [True, True]])
keras.ops.any(x, axis=0)
array([ True True], shape=(2,), dtype=bool)
keepdims=True outputs a tensor with dimensions reduced to one.
>>> x = keras.ops.convert_to_tensor([[True, False], [True, True]])
>>> keras.ops.all(x, keepdims=True)
array([[False]], shape=(1, 1), dtype=bool)
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Last updated 2024-06-07 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.ops.any\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#L262-L296) |\n\nTest whether any array element along a given axis evaluates to `True`.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.ops.numpy.any`](https://www.tensorflow.org/api_docs/python/tf/keras/ops/any)\n\n\u003cbr /\u003e\n\n tf.keras.ops.any(\n x, axis=None, keepdims=False\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x` | Input tensor. |\n| `axis` | An integer or tuple of integers that represent the axis along which a logical OR reduction is performed. The default (`axis=None`) is to perform a logical OR over all the dimensions of the input array. `axis` may be negative, in which case it counts for the last to the first axis. |\n| `keepdims` | If `True`, axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. Defaults to `False`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The tensor containing the logical OR reduction over the `axis`. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n x = keras.ops.convert_to_tensor([True, False])\n keras.ops.any(x)\n array(True, shape=(), dtype=bool)\n\n x = keras.ops.convert_to_tensor([[True, False], [True, True]])\n keras.ops.any(x, axis=0)\n array([ True True], shape=(2,), dtype=bool)\n\n`keepdims=True` outputs a tensor with dimensions reduced to one. \n\n \u003e\u003e\u003e x = keras.ops.convert_to_tensor([[True, False], [True, True]])\n \u003e\u003e\u003e keras.ops.all(x, keepdims=True)\n array([[False]], shape=(1, 1), dtype=bool)"]]
View source on GitHub