Splits a tensor value
into a list of sub tensors.
tfp.experimental.distributions.marginal_fns.ps.split(
value, num_or_size_splits, axis=0, num=None, name='split'
)
See also tf.unstack
.
If num_or_size_splits
is an int
, then it splits value
along the
dimension axis
into num_or_size_splits
smaller tensors. This requires that
value.shape[axis]
is divisible by num_or_size_splits
.
If num_or_size_splits
is a 1-D Tensor (or list), then value
is split into
len(num_or_size_splits)
elements. The shape of the i
-th
element has the same size as the value
except along dimension axis
where
the size is num_or_size_splits[i]
.
For example:
x = tf.Variable(tf.random.uniform([5, 30], -1, 1))
# Split `x` into 3 tensors along dimension 1
s0, s1, s2 = tf.split(x, num_or_size_splits=3, axis=1)
tf.shape(s0).numpy()
array([ 5, 10], dtype=int32)
# Split `x` into 3 tensors with sizes [4, 15, 11] along dimension 1
split0, split1, split2 = tf.split(x, [4, 15, 11], 1)
tf.shape(split0).numpy()
array([5, 4], dtype=int32)
tf.shape(split1).numpy()
array([ 5, 15], dtype=int32)
tf.shape(split2).numpy()
array([ 5, 11], dtype=int32)
Returns | |
---|---|
if num_or_size_splits is an int returns a list of
num_or_size_splits Tensor objects; if num_or_size_splits is a 1-D
list or 1-D Tensor returns num_or_size_splits.get_shape[0]
Tensor objects resulting from splitting value .
|
Raises | |
---|---|
ValueError
|
If num is unspecified and cannot be inferred.
|
ValueError
|
If num_or_size_splits is a scalar Tensor .
|