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Paddle/python/paddle/fluid/input.py

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2.4 KiB

# Copyright (c) 2019 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
from .framework import Variable, in_dygraph_mode
from .layer_helper import LayerHelper
__all__ = ['one_hot']
def one_hot(input, depth, allow_out_of_range=False):
"""
This layer creates the one-hot representations for input indices.
Args:
input(Variable): Input indices represent locations, which takes value 1.0
in indices, while all other locations take value 0.
depth(scalar): An interger defining the depth of the one-hot dimension.
allow_out_of_range(bool): A bool value indicating whether the input
indices could be out of range [0, depth). When input indices are
out of range, exceptions is raised if allow_out_of_range is False,
or zero-filling representations is created if it is set True
Returns:
Variable: The one-hot representations of input.
Examples:
.. code-block:: python
import paddle.fluid as fluid
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
one_hot_label = fluid.input.one_hot(input=label, depth=10)
"""
helper = LayerHelper("one_hot_v2", **locals())
one_hot_out = helper.create_variable_for_type_inference(dtype='float32')
if in_dygraph_mode():
inputs = {'X': input}
attrs = {'depth': depth}
else:
if not isinstance(depth, Variable):
# user attribute
inputs = {'X': input}
attrs = {'depth': depth}
else:
depth.stop_gradient = True
inputs = {'X': input, 'depth_tensor': depth}
attrs = {}
helper.append_op(
type="one_hot_v2",
inputs=inputs,
attrs=attrs,
outputs={'Out': one_hot_out},
stop_gradient=True)
return one_hot_out