tf.compat.v1.math.reduce_max | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.math.reduce_max
Computes tf.math.maximum of elements across dimensions of a tensor. (deprecated arguments)
tf.compat.v1.math.reduce_max(
input_tensor,
axis=None,
keepdims=None,
name=None,
reduction_indices=None,
keep_dims=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). |
| reduction_indices | The old (deprecated) name for axis. |
| keep_dims | Deprecated alias for keepdims. |
| Returns |
|---|
| The reduced tensor. |
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Last updated 2024-04-26 UTC.