TensorFlow 1 version
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    View source on GitHub
  
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Computes tf.math.multiply of elements across dimensions of a tensor.
tf.math.reduce_prod(
    input_tensor, axis=None, keepdims=False, name=None
)
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
  TensorFlow 1 version
    View source on GitHub