You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
111 lines
3.9 KiB
111 lines
3.9 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
from __future__ import print_function
|
|
import warnings
|
|
from ...fluid.framework import Variable, in_dygraph_mode
|
|
from ...fluid.layer_helper import LayerHelper
|
|
from ...fluid.layers import core
|
|
from ...fluid.data_feeder import check_variable_and_dtype, check_dtype
|
|
|
|
__all__ = ['one_hot']
|
|
|
|
|
|
def one_hot(x, num_classes, name=None):
|
|
"""
|
|
|
|
The operator converts each id in the input 'x' to an one-hot vector with a
|
|
num_classes length. The value in the vector dimension corresponding to the id
|
|
is 1, and the value in the remaining dimension is 0.
|
|
|
|
The shape of output Tensor is generated by appending num_classes dimension
|
|
behind the last dimension of the 'x' shape.
|
|
|
|
.. code-block:: text
|
|
|
|
Example 1:
|
|
|
|
input:
|
|
x.shape = [4]
|
|
x.data = [1, 1, 3, 0]
|
|
num_classes = 4
|
|
|
|
output:
|
|
Out.shape = [4, 4]
|
|
Out.data = [[0., 1., 0., 0.],
|
|
[0., 1., 0., 0.],
|
|
[0., 0., 0., 1.],
|
|
[1., 0., 0., 0.]]
|
|
|
|
Example 2:
|
|
|
|
input:
|
|
x.shape = [4]
|
|
x.data = [1, 1, 5, 0]
|
|
num_classes = 4
|
|
|
|
output: Throw an exception for Illegal value
|
|
The second dimension in X is 5, which is greater than num_classes,
|
|
so it throws an exception.
|
|
|
|
|
|
Args:
|
|
x(Tensor): Tensor with shape :math:`[N_1, N_2, ..., N_k]` ,
|
|
which contains at least one dimension. The data type is int32 or int64.
|
|
num_classes(int): An integer defining the num_classes of the one hot dimension. If input 'x'
|
|
is word id, num_classes is generally the dictionary size.
|
|
|
|
Returns:
|
|
Tensor: The one-hot representations of 'x'. A Tensor with type float32.
|
|
|
|
Examples:
|
|
.. code-block:: python
|
|
|
|
import paddle
|
|
# Correspond to the first example above, where label.shape is 4 and one_hot_label.shape is [4, 4].
|
|
label = paddle.data(name="label", shape=[4, 1], dtype="int64")
|
|
# label.shape = [4]
|
|
# label.data = [1, 1, 3, 0]
|
|
one_hot_label = paddle.nn.functional.one_hot(x=label, num_classes=4)
|
|
# one_hot_label.shape = [4, 4]
|
|
# one_hot_label.data = [[0., 1., 0., 0.],
|
|
# [0., 1., 0., 0.],
|
|
# [0., 0., 0., 1.],
|
|
# [1., 0., 0., 0.]]
|
|
"""
|
|
|
|
if in_dygraph_mode():
|
|
return core.ops.one_hot_v2(x, 'depth', num_classes,
|
|
'allow_out_of_range', False)
|
|
else:
|
|
check_variable_and_dtype(x, 'input', ['int32', 'int64'], 'one_hot_v2')
|
|
helper = LayerHelper("one_hot_v2", **locals())
|
|
|
|
one_hot_out = helper.create_variable_for_type_inference(dtype='float32')
|
|
if not isinstance(num_classes, Variable):
|
|
# user attribute
|
|
inputs = {'X': x}
|
|
attrs = {'depth': num_classes, 'allow_out_of_range': False}
|
|
else:
|
|
num_classes.stop_gradient = True
|
|
inputs = {'X': x, 'depth_tensor': num_classes}
|
|
attrs = {'allow_out_of_range': False}
|
|
helper.append_op(
|
|
type="one_hot_v2",
|
|
inputs=inputs,
|
|
attrs=attrs,
|
|
outputs={'Out': one_hot_out},
|
|
stop_gradient=True)
|
|
return one_hot_out
|