tf.math.reduce_prod | TensorFlow v2.16.1 (original) (raw)
tf.math.reduce_prod
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Computes tf.math.multiply of elements across dimensions of a tensor.
View aliases
Main aliases
tf.math.reduce_prod(
input_tensor, axis=None, keepdims=False, name=None
)
Used in the notebooks
| Used in the guide | Used in the tutorials |
|---|---|
| Advanced automatic differentiation Sparse weights using structural pruning | Intro to Autoencoders TFP Release Notes notebook (0.12.1) TensorFlow Distributions: A Gentle Introduction |
This is the reduction operation for the elementwise tf.math.multiply 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 entry in axis. 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.
| For example |
|---|
| >>> x = tf.constant([[1., 2.], [3., 4.]]) >>> tf.math.reduce_prod(x) <tf.Tensor: shape=(), dtype=float32, numpy=24.> >>> tf.math.reduce_prod(x, 0) <tf.Tensor: shape=(2,), dtype=float32, numpy=array([3., 8.], dtype=float32)> >>> tf.math.reduce_prod(x, 1) <tf.Tensor: shape=(2,), dtype=float32, numpy=array([2., 12.], dtype=float32)> |
| Args | |
|---|---|
| input_tensor | The tensor to reduce. Should have 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. |
numpy compatibility
Equivalent to np.prod