From d31c92a2cd8a50b4a42f3f3a0b67745f1115c138 Mon Sep 17 00:00:00 2001 From: ruri Date: Mon, 23 Sep 2019 11:32:28 +0800 Subject: [PATCH] add mse_loss (#19759) * add mse_loss op --- paddle/fluid/API.spec | 1 + python/paddle/fluid/layers/nn.py | 38 +++++++++++++ .../fluid/tests/unittests/test_layers.py | 8 +++ .../fluid/tests/unittests/test_mse_loss.py | 53 +++++++++++++++++++ 4 files changed, 100 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/test_mse_loss.py diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 444c75037f..75c68a8e71 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -297,6 +297,7 @@ paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'tran paddle.fluid.layers.filter_by_instag (ArgSpec(args=['ins', 'ins_tag', 'filter_tag', 'is_lod'], varargs=None, keywords=None, defaults=None), ('document', '7703a2088af8de4128b143ff1164ca4a')) paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', '5786fdbba6753ecd6cbce5e6b0889924')) paddle.fluid.layers.hard_swish (ArgSpec(args=['x', 'threshold', 'scale', 'offset', 'name'], varargs=None, keywords=None, defaults=(6.0, 6.0, 3.0, None)), ('document', '6a5152a7015c62cb8278fc24cb456459')) +paddle.fluid.layers.mse_loss (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'd9ede6469288636e1b3233b461a165c9')) paddle.fluid.layers.data (ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)), ('document', '9d7806e31bdf727c1a23b8782a09b545')) paddle.fluid.layers.read_file (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', '88367daf9a30c9ab83adc5d7221e23ef')) paddle.fluid.layers.double_buffer (ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '44724c493f41a124abc7531c2740e2e3')) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 1d3e316141..5c2df7a7cb 100755 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -220,6 +220,7 @@ __all__ = [ 'filter_by_instag', 'shard_index', 'hard_swish', + 'mse_loss', ] kIgnoreIndex = -100 @@ -14215,3 +14216,40 @@ def hard_swish(x, threshold=6.0, scale=6.0, offset=3.0, name=None): 'scale': scale, 'offset': offset}) return out + + +def mse_loss(input, label): + """ + **Mean square error layer** + + This layer accepts input predications and target label and returns the mean square error. + + The loss can be described as: + + .. math:: + + Out = mean((X - Y)^2) + + In the above equation: + + * :math:`X`: Input predications, a tensor. + * :math:`Y`: Input labels, a tensor. + * :math:`Out`: Output value, same shape with :math:`X`. + + Args: + input (Variable): Input tensor, has predictions. + label (Variable): Label tensor, has target labels. + + Returns: + Variable: The tensor variable storing the mean square error difference of input and label. + + Examples: + .. code-block:: python + + import paddle.fluid as fluid + y = fluid.layers.data(name='y', shape=[1], dtype='float32') + y_predict = fluid.layers.data(name='y_predict', shape=[1], dtype='float32') + mse = fluid.layers.mse_loss(input=y_predict, label=y) + + """ + return reduce_mean(square_error_cost(input, label)) diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 10e949cab2..f343af9561 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -2046,6 +2046,14 @@ class TestBook(LayerTest): out = layers.pixel_shuffle(x, upscale_factor=3) return (out) + def make_mse_loss(self): + with program_guard(fluid.default_main_program(), + fluid.default_startup_program()): + x = self._get_data(name="X", shape=[1], dtype="float32") + y = self._get_data(name="Y", shape=[1], dtype="float32") + out = layers.mse_loss(input=x, label=y) + return (out) + def make_square_error_cost(self): with program_guard(fluid.default_main_program(), fluid.default_startup_program()): diff --git a/python/paddle/fluid/tests/unittests/test_mse_loss.py b/python/paddle/fluid/tests/unittests/test_mse_loss.py new file mode 100644 index 0000000000..64b4004e4b --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_mse_loss.py @@ -0,0 +1,53 @@ +# 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 + +import unittest +import numpy as np +import sys +import paddle.fluid.core as core +import paddle.fluid as fluid +import paddle.fluid.layers as layers +from paddle.fluid.executor import Executor + + +class TestMseLoss(unittest.TestCase): + def test_mse_loss(self): + input_val = np.random.uniform(0.1, 0.5, (2, 3)).astype("float32") + label_val = np.random.uniform(0.1, 0.5, (2, 3)).astype("float32") + + sub = input_val - label_val + np_result = np.mean(sub * sub) + + input_var = layers.create_tensor(dtype="float32", name="input") + label_var = layers.create_tensor(dtype="float32", name="label") + + layers.assign(input=input_val, output=input_var) + layers.assign(input=label_val, output=label_var) + output = layers.mse_loss(input=input_var, label=label_var) + for use_cuda in ([False, True] + if core.is_compiled_with_cuda() else [False]): + place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() + exe = Executor(place) + result = exe.run(fluid.default_main_program(), + feed={"input": input_var, + "label": label_var}, + fetch_list=[output]) + + self.assertTrue(np.isclose(np_result, result).all()) + + +if __name__ == "__main__": + unittest.main() -- GitLab