wehub-resource-sync
87 lines
3.1 KiB
Python
87 lines
3.1 KiB
Python
# 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 annotations
|
|
|
|
from typing import TYPE_CHECKING
|
|
|
|
from paddle import _C_ops
|
|
from paddle.base.data_feeder import check_variable_and_dtype
|
|
from paddle.base.layer_helper import LayerHelper
|
|
from paddle.framework import in_dynamic_or_pir_mode
|
|
|
|
if TYPE_CHECKING:
|
|
from typing import Literal, TypeAlias
|
|
|
|
from paddle import Tensor
|
|
|
|
_ReduceModeStringLiteral: TypeAlias = Literal['mean', 'sum', 'none']
|
|
_ReduceModeNumberLiteral: TypeAlias = Literal[0, 1, 2]
|
|
_ReduceMode: TypeAlias = _ReduceModeStringLiteral | _ReduceModeNumberLiteral
|
|
|
|
|
|
def identity_loss(x: Tensor, reduction: _ReduceMode = "none") -> Tensor:
|
|
r"""Marks a tensor as being part of the loss calculation for IPU.
|
|
|
|
This operator is used to handle on the (final) loss of a model so that
|
|
it is used as the start of backpropagation.
|
|
|
|
When `reduction` is `none`, return raw `Out`.
|
|
|
|
When `reduction` is `mean`, return
|
|
|
|
.. math::
|
|
Out = MEAN(Out)
|
|
|
|
When `reduction` is `sum`, return
|
|
|
|
.. math::
|
|
Out = SUM(Out)
|
|
|
|
Parameters:
|
|
x (Variable): The input tensor. The shapes is [N, *], where N is batch size and `*` means any number of
|
|
additional dimensions. It's data type should be float32, float64 on CPU and float16, float32 on IPU.
|
|
reduction(str|int, optional): Reduce the loss output. Supported string values are: 'sum', 'mean', 'none'
|
|
the corresponding int values are 0, 1, 2 respectively. The default value is "none".
|
|
|
|
Returns:
|
|
Variable: The loss ``Tensor`` with the specified reduction applied.
|
|
|
|
Examples:
|
|
|
|
.. code-block:: pycon
|
|
|
|
>>> import paddle
|
|
>>> paddle.enable_static()
|
|
>>> loss = paddle.static.data(name="loss", shape=[-1, 1], dtype="float32")
|
|
>>> out = paddle.incubate.identity_loss(loss, reduction=1)
|
|
"""
|
|
if isinstance(reduction, str):
|
|
reduction = {"sum": 0, "mean": 1, "none": 2}.get(reduction.lower())
|
|
if reduction is None:
|
|
raise TypeError("Unsupported reduction type.")
|
|
|
|
if in_dynamic_or_pir_mode():
|
|
return _C_ops.identity_loss(x, reduction)
|
|
|
|
check_variable_and_dtype(x, 'x', ['float32', 'float64'], "identity_loss")
|
|
attrs = {'reduction': reduction}
|
|
helper = LayerHelper('identity_loss', **locals())
|
|
dtype = helper.input_dtype(input_param_name='x')
|
|
out = helper.create_variable_for_type_inference(dtype)
|
|
helper.append_op(
|
|
type="identity_loss", inputs={"X": x}, outputs={"Out": out}, attrs=attrs
|
|
)
|
|
return out
|