tf.math.reduce_max
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Computes tf.math.maximum of elements across dimensions of a tensor.
tf.math.reduce_max(
input_tensor, axis=None, keepdims=False, name=None
)
This is the reduction operation for the elementwise tf.math.maximum op.
Reduces input_tensor along the dimensions given in axis.
Unless keepdims is true, the rank of the tensor is reduced by 1 for each
of the entries in axis, which must be unique. If keepdims is true, the
reduced dimensions are retained with length 1.
If axis is None, all dimensions are reduced, and a
tensor with a single element is returned.
Usage example |
|---|
>>> x = tf.constant([5, 1, 2, 4])
>>> tf.reduce_max(x)
<tf.Tensor: shape=(), dtype=int32, numpy=5>
>>> x = tf.constant([-5, -1, -2, -4])
>>> tf.reduce_max(x)
<tf.Tensor: shape=(), dtype=int32, numpy=-1>
>>> x = tf.constant([4, float('nan')])
>>> tf.reduce_max(x)
<tf.Tensor: shape=(), dtype=float32, numpy=nan>
>>> x = tf.constant([float('nan'), float('nan')])
>>> tf.reduce_max(x)
<tf.Tensor: shape=(), dtype=float32, numpy=nan>
>>> x = tf.constant([float('-inf'), float('inf')])
>>> tf.reduce_max(x)
<tf.Tensor: shape=(), dtype=float32, numpy=inf>
|
See the numpy docs for np.amax and np.nanmax behavior.
Args |
|---|
input_tensor
|
The tensor to reduce. Should have real numeric type.
|
axis
|
The dimensions to reduce. If None (the default), reduces all
dimensions. Must be in the range [-rank(input_tensor),
rank(input_tensor)).
|
keepdims
|
If true, retains reduced dimensions with length 1.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
|
The reduced tensor.
|
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.math.reduce_max\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.14.0/tensorflow/python/ops/math_ops.py#L3184-L3231) |\n\nComputes [`tf.math.maximum`](../../tf/math/maximum) of elements across dimensions of a tensor.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.reduce_max`](https://www.tensorflow.org/api_docs/python/tf/math/reduce_max)\n\n\u003cbr /\u003e\n\n tf.math.reduce_max(\n input_tensor, axis=None, keepdims=False, name=None\n )\n\nThis is the reduction operation for the elementwise [`tf.math.maximum`](../../tf/math/maximum) op.\n\nReduces `input_tensor` along the dimensions given in `axis`.\nUnless `keepdims` is true, the rank of the tensor is reduced by 1 for each\nof the entries in `axis`, which must be unique. If `keepdims` is true, the\nreduced dimensions are retained with length 1.\n\nIf `axis` is None, all dimensions are reduced, and a\ntensor with a single element is returned.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Usage example ------------- ||\n|---|---|\n| \u003cbr /\u003e \u003e\u003e\u003e x = tf.constant([5, 1, 2, 4]) \u003e\u003e\u003e tf.reduce_max(x) \u003ctf.Tensor: shape=(), dtype=int32, numpy=5\u003e \u003e\u003e\u003e x = tf.constant([-5, -1, -2, -4]) \u003e\u003e\u003e tf.reduce_max(x) \u003ctf.Tensor: shape=(), dtype=int32, numpy=-1\u003e \u003e\u003e\u003e x = tf.constant([4, float('nan')]) \u003e\u003e\u003e tf.reduce_max(x) \u003ctf.Tensor: shape=(), dtype=float32, numpy=nan\u003e \u003e\u003e\u003e x = tf.constant([float('nan'), float('nan')]) \u003e\u003e\u003e tf.reduce_max(x) \u003ctf.Tensor: shape=(), dtype=float32, numpy=nan\u003e \u003e\u003e\u003e x = tf.constant([float('-inf'), float('inf')]) \u003e\u003e\u003e tf.reduce_max(x) \u003ctf.Tensor: shape=(), dtype=float32, numpy=inf\u003e \u003cbr /\u003e ||\n\n\u003cbr /\u003e\n\nSee the numpy docs for `np.amax` and `np.nanmax` behavior.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|----------------------------------------------------------------------------------------------------------------------------------------------|\n| `input_tensor` | The tensor to reduce. Should have real numeric type. |\n| `axis` | The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))`. |\n| `keepdims` | If true, retains reduced dimensions with length 1. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The reduced tensor. ||\n\n\u003cbr /\u003e"]]
View source on GitHub