Returns a one-hot tensor.
meridian
.
backend
.
one_hot
(
indices
,
depth
,
on_value
=
None
,
off_value
=
None
,
axis
=
None
,
dtype
=
None
,
name
=
None
)
See also tf.fill
, tf.eye
.
The locations represented by indices in indices
take value on_value
,
while all other locations take value off_value
.
on_value
and off_value
must have matching data types. If dtype
is also
provided, they must be the same data type as specified by dtype
.
If on_value
is not provided, it will default to the value 1
with type dtype
If off_value
is not provided, it will default to the value 0
with type dtype
If the input indices
is rank N
, the output will have rank N+1
. The
new axis is created at dimension axis
(default: the new axis is appended
at the end).
If indices
is a scalar the output shape will be a vector of length depth
If indices
is a vector of length features
, the output shape will be:
features x depth if axis == -1
depth x features if axis == 0
If indices
is a matrix (batch) with shape [batch, features]
, the output
shape will be:
batch x features x depth if axis == -1
batch x depth x features if axis == 1
depth x batch x features if axis == 0
If indices
is a RaggedTensor, the 'axis' argument must be positive and refer
to a non-ragged axis. The output will be equivalent to applying 'one_hot' on
the values of the RaggedTensor, and creating a new RaggedTensor from the
result.
If dtype
is not provided, it will attempt to assume the data type of on_value
or off_value
, if one or both are passed in. If none of on_value
, off_value
, or dtype
are provided, dtype
will default to the
value tf.float32
.
For example:
indices
=
[
0
,
1
,
2
]
depth
=
3
tf
.
one_hot
(
indices
,
depth
)
# output: [3 x 3]
# [[1., 0., 0.],
# [0., 1., 0.],
# [0., 0., 1.]]
indices
=
[
0
,
2
,
-
1
,
1
]
depth
=
3
tf
.
one_hot
(
indices
,
depth
,
on_value
=
5.0
,
off_value
=
0.0
,
axis
=-
1
)
# output: [4 x 3]
# [[5.0, 0.0, 0.0], # one_hot(0)
# [0.0, 0.0, 5.0], # one_hot(2)
# [0.0, 0.0, 0.0], # one_hot(-1)
# [0.0, 5.0, 0.0]] # one_hot(1)
indices
=
[[
0
,
2
],
[
1
,
-
1
]]
depth
=
3
tf
.
one_hot
(
indices
,
depth
,
on_value
=
1.0
,
off_value
=
0.0
,
axis
=-
1
)
# output: [2 x 2 x 3]
# [[[1.0, 0.0, 0.0], # one_hot(0)
# [0.0, 0.0, 1.0]], # one_hot(2)
# [[0.0, 1.0, 0.0], # one_hot(1)
# [0.0, 0.0, 0.0]]] # one_hot(-1)
indices
=
tf
.
ragged
.
constant
([[
0
,
1
],
[
2
]])
depth
=
3
tf
.
one_hot
(
indices
,
depth
)
# output: [2 x None x 3]
# [[[1., 0., 0.],
# [0., 1., 0.]],
# [[0., 0., 1.]]]
Args
