From 0aaa1eba22650ed6feb126fb5c3e13a92c577a05 Mon Sep 17 00:00:00 2001 From: chenhaozhe <chenhaozhe1@huawei.com> Date: Thu, 17 Mar 2022 15:19:37 +0800 Subject: [PATCH] update _Loss to LossBase --- official/cv/vit/src/cross_entropy.py | 8 +------- research/cv/HRNetW48_cls/src/loss.py | 4 ++-- research/cv/HRNetW48_seg/src/loss.py | 6 +++--- research/cv/ICNet/Res50V1_PRE/src/CrossEntropySmooth.py | 4 ++-- research/cv/NFNet/src/tools/criterion.py | 6 +++--- research/cv/OCRNet/src/loss.py | 6 +++--- research/cv/Pix2Pix/src/models/loss.py | 8 ++++---- research/cv/ProtoNet/src/PrototypicalLoss.py | 4 ++-- research/cv/ResNeSt50/src/crossentropy.py | 4 ++-- research/cv/SE_ResNeXt50/eval.py | 4 ++-- research/cv/SE_ResNeXt50/train.py | 4 ++-- research/cv/TNT/src/tools/criterion.py | 6 +++--- research/cv/VehicleNet/src/loss.py | 4 ++-- research/cv/aecrnet/src/contras_loss.py | 4 ++-- research/cv/cct/src/tools/criterion.py | 6 +++--- research/cv/csd/src/contras_loss.py | 4 ++-- research/cv/efficientnet-b0/src/loss.py | 4 ++-- research/cv/efficientnet-b1/src/loss.py | 6 +++--- research/cv/efficientnet-b3/src/loss.py | 4 ++-- research/cv/fishnet99/eval.py | 4 ++-- research/cv/fishnet99/train.py | 4 ++-- research/cv/ghostnet/src/CrossEntropySmooth.py | 4 ++-- research/cv/inception_resnet_v2/modelarts/train_start.py | 4 ++-- research/cv/inception_resnet_v2/train.py | 4 ++-- research/cv/mnasnet/src/loss.py | 4 ++-- research/cv/mobilenetV3_small_x1_0/src/loss.py | 4 ++-- research/cv/mobilenetv3_large/train.py | 4 ++-- research/cv/pointnet2/src/pointnet2.py | 4 ++-- research/cv/resnet3d/src/loss.py | 4 ++-- research/cv/resnet50_bam/eval.py | 4 ++-- research/cv/resnet50_bam/train.py | 4 ++-- research/cv/resnext152_64x4d/src/crossentropy.py | 4 ++-- research/cv/simple_baselines/src/network_with_loss.py | 4 ++-- research/cv/single_path_nas/eval.py | 4 ++-- research/cv/single_path_nas/src/CrossEntropySmooth.py | 4 ++-- research/cv/sknet/src/CrossEntropySmooth.py | 4 ++-- research/cv/squeezenet1_1/src/CrossEntropySmooth.py | 4 ++-- research/cv/swin_transformer/src/tools/criterion.py | 6 +++--- research/cv/tsm/src/model/cross_entropy_smooth.py | 4 ++-- research/cv/wideresnet/src/cross_entropy_smooth.py | 4 ++-- 40 files changed, 88 insertions(+), 94 deletions(-) diff --git a/official/cv/vit/src/cross_entropy.py b/official/cv/vit/src/cross_entropy.py index 7cbedb5f0..1e7865b91 100644 --- a/official/cv/vit/src/cross_entropy.py +++ b/official/cv/vit/src/cross_entropy.py @@ -17,13 +17,7 @@ from mindspore import nn from mindspore import Tensor from mindspore.common import dtype as mstype -try: - from mindspore.nn.loss.loss import Loss -except ImportError: - try: - from mindspore.nn.loss.loss import LossBase as Loss - except ImportError: - from mindspore.nn.loss.loss import _Loss as Loss +from mindspore.nn.loss.loss import LossBase as Loss from mindspore.ops import functional as F from mindspore.ops import operations as P diff --git a/research/cv/HRNetW48_cls/src/loss.py b/research/cv/HRNetW48_cls/src/loss.py index 33d841525..ce56f8a41 100644 --- a/research/cv/HRNetW48_cls/src/loss.py +++ b/research/cv/HRNetW48_cls/src/loss.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/HRNetW48_seg/src/loss.py b/research/cv/HRNetW48_seg/src/loss.py index 9cde41d4c..9f88cbde6 100644 --- a/research/cv/HRNetW48_seg/src/loss.py +++ b/research/cv/HRNetW48_seg/src/loss.py @@ -18,10 +18,10 @@ import mindspore.ops.operations as P import mindspore.ops as F from mindspore.common.tensor import Tensor from mindspore import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase -class CrossEntropyWithLogits(_Loss): +class CrossEntropyWithLogits(LossBase): """ Cross-entropy loss function for semantic segmentation, and different classes have the same weight. @@ -61,7 +61,7 @@ class CrossEntropyWithLogits(_Loss): return loss -class CrossEntropyWithWeights(_Loss): +class CrossEntropyWithWeights(LossBase): """ Cross-entropy loss function for semantic segmentation, and different classes have different weights. diff --git a/research/cv/ICNet/Res50V1_PRE/src/CrossEntropySmooth.py b/research/cv/ICNet/Res50V1_PRE/src/CrossEntropySmooth.py index 24bb6995e..149f33454 100644 --- a/research/cv/ICNet/Res50V1_PRE/src/CrossEntropySmooth.py +++ b/research/cv/ICNet/Res50V1_PRE/src/CrossEntropySmooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/NFNet/src/tools/criterion.py b/research/cv/NFNet/src/tools/criterion.py index bf8a490e9..adef5e682 100644 --- a/research/cv/NFNet/src/tools/criterion.py +++ b/research/cv/NFNet/src/tools/criterion.py @@ -17,12 +17,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore import ops from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class SoftTargetCrossEntropy(_Loss): +class SoftTargetCrossEntropy(LossBase): """SoftTargetCrossEntropy for MixUp Augment""" def __init__(self): @@ -38,7 +38,7 @@ class SoftTargetCrossEntropy(_Loss): return self.mean_ops(loss) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/OCRNet/src/loss.py b/research/cv/OCRNet/src/loss.py index 99af216d1..5842464a4 100644 --- a/research/cv/OCRNet/src/loss.py +++ b/research/cv/OCRNet/src/loss.py @@ -19,7 +19,7 @@ import mindspore.ops.operations as P import mindspore.ops as F from mindspore.common.tensor import Tensor from mindspore import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from src.config import config_hrnetv2_w48 as config @@ -30,7 +30,7 @@ weights_list = [0.8373, 0.918, 0.866, 1.0345, 1.0865, 1.1529, 1.0507] -class CrossEntropyWithLogits(_Loss): +class CrossEntropyWithLogits(LossBase): """ Cross-entropy loss function for semantic segmentation, and different classes have the same weight. @@ -71,7 +71,7 @@ class CrossEntropyWithLogits(_Loss): return loss -class CrossEntropyWithLogitsAndWeights(_Loss): +class CrossEntropyWithLogitsAndWeights(LossBase): """ Cross-entropy loss function for semantic segmentation, and different classes have different weights. diff --git a/research/cv/Pix2Pix/src/models/loss.py b/research/cv/Pix2Pix/src/models/loss.py index eff9c4776..c9cca0cb9 100644 --- a/research/cv/Pix2Pix/src/models/loss.py +++ b/research/cv/Pix2Pix/src/models/loss.py @@ -24,12 +24,12 @@ import mindspore.ops.operations as P from mindspore.parallel._utils import (_get_device_num, _get_gradients_mean, _get_parallel_mode) from mindspore.context import ParallelMode from mindspore.nn.wrap.grad_reducer import DistributedGradReducer -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from src.utils.config import get_args args = get_args() -class SigmoidCrossEntropyWithLogits(_Loss): +class SigmoidCrossEntropyWithLogits(LossBase): def __init__(self): super(SigmoidCrossEntropyWithLogits, self).__init__() self.cross_entropy = P.SigmoidCrossEntropyWithLogits() @@ -38,7 +38,7 @@ class SigmoidCrossEntropyWithLogits(_Loss): x = self.cross_entropy(data, label) return self.get_loss(x) -class D_Loss(_Loss): +class D_Loss(LossBase): """ Define Dloss. """ @@ -70,7 +70,7 @@ class D_WithLossCell(nn.Cell): pred0 = self.netD(realA, fakeB) return self._loss_fn(pred1, pred0) -class G_Loss(_Loss): +class G_Loss(LossBase): """ Define Gloss. """ diff --git a/research/cv/ProtoNet/src/PrototypicalLoss.py b/research/cv/ProtoNet/src/PrototypicalLoss.py index 8faa95927..0a3a784f9 100644 --- a/research/cv/ProtoNet/src/PrototypicalLoss.py +++ b/research/cv/ProtoNet/src/PrototypicalLoss.py @@ -18,11 +18,11 @@ loss function script. import mindspore.ops as ops import mindspore.nn as nn from mindspore import Tensor -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase import mindspore as ms import numpy as np -class PrototypicalLoss(_Loss): +class PrototypicalLoss(LossBase): ''' Loss class deriving from Module for the prototypical loss function defined below ''' diff --git a/research/cv/ResNeSt50/src/crossentropy.py b/research/cv/ResNeSt50/src/crossentropy.py index a5abe6021..01039e39e 100644 --- a/research/cv/ResNeSt50/src/crossentropy.py +++ b/research/cv/ResNeSt50/src/crossentropy.py @@ -15,14 +15,14 @@ """ define loss function for network. """ -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import operations as P from mindspore.ops import functional as F from mindspore import Tensor from mindspore.common import dtype as mstype import mindspore.nn as nn -class CrossEntropy(_Loss): +class CrossEntropy(LossBase): """ the redefined loss function with SoftmaxCrossEntropyWithLogits. """ diff --git a/research/cv/SE_ResNeXt50/eval.py b/research/cv/SE_ResNeXt50/eval.py index cb109902c..a12f096dc 100644 --- a/research/cv/SE_ResNeXt50/eval.py +++ b/research/cv/SE_ResNeXt50/eval.py @@ -24,7 +24,7 @@ from mindspore.train.serialization import load_checkpoint, load_param_into_net from mindspore.common import set_seed from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -41,7 +41,7 @@ parser.add_argument('--checkpoint_path', type=str, default='./ckpt_0', help='Che args_opt = parser.parse_args() -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/SE_ResNeXt50/train.py b/research/cv/SE_ResNeXt50/train.py index b99da2f46..972626ae0 100644 --- a/research/cv/SE_ResNeXt50/train.py +++ b/research/cv/SE_ResNeXt50/train.py @@ -34,7 +34,7 @@ from mindspore.context import ParallelMode from mindspore.train.serialization import load_checkpoint, load_param_into_net from mindspore.common import set_seed from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -152,7 +152,7 @@ def warmup_cosine_annealing_lr(lr5, steps_per_epoch, warmup_epochs, max_epoch, T return np.array(lr_each_step).astype(np.float32) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/TNT/src/tools/criterion.py b/research/cv/TNT/src/tools/criterion.py index 1afdd719f..ee963c1fe 100644 --- a/research/cv/TNT/src/tools/criterion.py +++ b/research/cv/TNT/src/tools/criterion.py @@ -17,12 +17,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore import ops from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class SoftTargetCrossEntropy(_Loss): +class SoftTargetCrossEntropy(LossBase): """SoftTargetCrossEntropy for MixUp Augment""" def __init__(self): @@ -38,7 +38,7 @@ class SoftTargetCrossEntropy(_Loss): return self.mean_ops(loss) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/VehicleNet/src/loss.py b/research/cv/VehicleNet/src/loss.py index 6aca54153..673a8ab1c 100644 --- a/research/cv/VehicleNet/src/loss.py +++ b/research/cv/VehicleNet/src/loss.py @@ -13,14 +13,14 @@ # limitations under the License. # ============================================================================ """loss function""" -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import operations as P from mindspore.ops import functional as F from mindspore import Tensor from mindspore.common import dtype as mstype import mindspore.nn as nn -class CrossEntropy(_Loss): +class CrossEntropy(LossBase): """CrossEntropy""" def __init__(self, smooth_factor=0., num_classes=1000): super(CrossEntropy, self).__init__() diff --git a/research/cv/aecrnet/src/contras_loss.py b/research/cv/aecrnet/src/contras_loss.py index 93b3d61bd..fb8ea8430 100644 --- a/research/cv/aecrnet/src/contras_loss.py +++ b/research/cv/aecrnet/src/contras_loss.py @@ -16,7 +16,7 @@ import os import mindspore.ops as ops -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore import nn from mindspore import load_checkpoint, load_param_into_net from mindspore.ops.functional import stop_gradient @@ -82,7 +82,7 @@ class Vgg19(nn.Cell): return out -class ContrastLoss(_Loss): +class ContrastLoss(LossBase): """[ContrastLoss] Args: diff --git a/research/cv/cct/src/tools/criterion.py b/research/cv/cct/src/tools/criterion.py index 4ed0f0534..257aec2da 100644 --- a/research/cv/cct/src/tools/criterion.py +++ b/research/cv/cct/src/tools/criterion.py @@ -17,12 +17,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore import ops from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class SoftTargetCrossEntropy(_Loss): +class SoftTargetCrossEntropy(LossBase): """SoftTargetCrossEntropy for MixUp Augment""" def __init__(self): @@ -38,7 +38,7 @@ class SoftTargetCrossEntropy(_Loss): return self.mean_ops(loss) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/csd/src/contras_loss.py b/research/cv/csd/src/contras_loss.py index 8326af260..ac9bfa655 100644 --- a/research/cv/csd/src/contras_loss.py +++ b/research/cv/csd/src/contras_loss.py @@ -16,7 +16,7 @@ import os import mindspore.ops as ops -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore import nn from mindspore import load_checkpoint, load_param_into_net from mindspore.ops.functional import stop_gradient @@ -108,7 +108,7 @@ class Vgg19(nn.Cell): return out -class ContrastLoss(_Loss): +class ContrastLoss(LossBase): """[ContrastLoss] Args: diff --git a/research/cv/efficientnet-b0/src/loss.py b/research/cv/efficientnet-b0/src/loss.py index 6d63b6669..8400b5413 100644 --- a/research/cv/efficientnet-b0/src/loss.py +++ b/research/cv/efficientnet-b0/src/loss.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/efficientnet-b1/src/loss.py b/research/cv/efficientnet-b1/src/loss.py index 06cb51616..14ebd144f 100644 --- a/research/cv/efficientnet-b1/src/loss.py +++ b/research/cv/efficientnet-b1/src/loss.py @@ -13,7 +13,7 @@ # limitations under the License. # ============================================================================ """define loss function for network.""" -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import operations as P from mindspore.ops import functional as F from mindspore.common import dtype as mstype @@ -21,7 +21,7 @@ from mindspore import Tensor import mindspore.nn as nn -class LabelSmoothingCrossEntropy(_Loss): +class LabelSmoothingCrossEntropy(LossBase): """LabelSmoothingCrossEntropy""" def __init__(self, smooth_factor=0.1, num_classes=1000): super(LabelSmoothingCrossEntropy, self).__init__() @@ -38,7 +38,7 @@ class LabelSmoothingCrossEntropy(_Loss): return loss_logit -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/efficientnet-b3/src/loss.py b/research/cv/efficientnet-b3/src/loss.py index 6d63b6669..8400b5413 100644 --- a/research/cv/efficientnet-b3/src/loss.py +++ b/research/cv/efficientnet-b3/src/loss.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/fishnet99/eval.py b/research/cv/fishnet99/eval.py index 4cebaf5c1..84cabbeaa 100644 --- a/research/cv/fishnet99/eval.py +++ b/research/cv/fishnet99/eval.py @@ -24,7 +24,7 @@ from mindspore.train.serialization import load_checkpoint, load_param_into_net from mindspore.common import set_seed from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -43,7 +43,7 @@ parser.add_argument('--checkpoint_path', type=str, default='./ckpt_0', help='Che args_opt = parser.parse_args() -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/fishnet99/train.py b/research/cv/fishnet99/train.py index a5401d158..3901c2b2a 100644 --- a/research/cv/fishnet99/train.py +++ b/research/cv/fishnet99/train.py @@ -31,7 +31,7 @@ from mindspore.context import ParallelMode from mindspore.train.serialization import load_checkpoint, load_param_into_net from mindspore.common import set_seed from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -81,7 +81,7 @@ def warmup_cosine_annealing_lr(lr5, steps_per_epoch, warmup_epochs, max_epoch, T return np.array(lr_each_step).astype(np.float32) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/ghostnet/src/CrossEntropySmooth.py b/research/cv/ghostnet/src/CrossEntropySmooth.py index 6d63b6669..8400b5413 100644 --- a/research/cv/ghostnet/src/CrossEntropySmooth.py +++ b/research/cv/ghostnet/src/CrossEntropySmooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/inception_resnet_v2/modelarts/train_start.py b/research/cv/inception_resnet_v2/modelarts/train_start.py index 37ab60bfb..83162b746 100644 --- a/research/cv/inception_resnet_v2/modelarts/train_start.py +++ b/research/cv/inception_resnet_v2/modelarts/train_start.py @@ -33,7 +33,7 @@ from mindspore.common.initializer import XavierUniform, initializer from mindspore.communication import init from mindspore.context import ParallelMode from mindspore.nn import RMSProp, Momentum -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor from mindspore.train.loss_scale_manager import FixedLossScaleManager from mindspore.train.serialization import load_checkpoint, load_param_into_net @@ -65,7 +65,7 @@ args = arg_parser.parse_args() set_seed(1) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/inception_resnet_v2/train.py b/research/cv/inception_resnet_v2/train.py index 34f42bd1a..e5de258f7 100644 --- a/research/cv/inception_resnet_v2/train.py +++ b/research/cv/inception_resnet_v2/train.py @@ -29,7 +29,7 @@ from mindspore.common.initializer import XavierUniform, initializer from mindspore.communication import init, get_rank from mindspore.context import ParallelMode from mindspore.nn import RMSProp, Momentum -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor from mindspore.train.loss_scale_manager import FixedLossScaleManager from mindspore.train.serialization import load_checkpoint, load_param_into_net @@ -42,7 +42,7 @@ os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'python' set_seed(1) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/mnasnet/src/loss.py b/research/cv/mnasnet/src/loss.py index 6d63b6669..8400b5413 100644 --- a/research/cv/mnasnet/src/loss.py +++ b/research/cv/mnasnet/src/loss.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/mobilenetV3_small_x1_0/src/loss.py b/research/cv/mobilenetV3_small_x1_0/src/loss.py index 827f15ccb..4b1af5aa1 100644 --- a/research/cv/mobilenetV3_small_x1_0/src/loss.py +++ b/research/cv/mobilenetV3_small_x1_0/src/loss.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropyWithLabelSmooth(_Loss): +class CrossEntropyWithLabelSmooth(LossBase): """CrossEntropyWithLabelSmooth""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropyWithLabelSmooth, self).__init__() diff --git a/research/cv/mobilenetv3_large/train.py b/research/cv/mobilenetv3_large/train.py index 75fbd9437..8daf1d726 100644 --- a/research/cv/mobilenetv3_large/train.py +++ b/research/cv/mobilenetv3_large/train.py @@ -25,7 +25,7 @@ from mindspore import Tensor from mindspore import nn from mindspore.nn.optim.momentum import Momentum from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import operations as P from mindspore.ops import functional as F from mindspore.common import dtype as mstype @@ -90,7 +90,7 @@ class SaveCallback(Callback): print("Save the maximum accuracy checkpoint,the accuracy is", self.acc) -class CrossEntropyWithLabelSmooth(_Loss): +class CrossEntropyWithLabelSmooth(LossBase): """ CrossEntropyWith LabelSmooth. diff --git a/research/cv/pointnet2/src/pointnet2.py b/research/cv/pointnet2/src/pointnet2.py index 57ec6408f..9e12ce7df 100644 --- a/research/cv/pointnet2/src/pointnet2.py +++ b/research/cv/pointnet2/src/pointnet2.py @@ -16,7 +16,7 @@ import mindspore.nn as nn import mindspore.ops as P -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from src.layers import Dense @@ -74,7 +74,7 @@ class PointNet2(nn.Cell): return x -class NLLLoss(_Loss): +class NLLLoss(LossBase): """NLL loss""" def __init__(self, reduction='mean'): diff --git a/research/cv/resnet3d/src/loss.py b/research/cv/resnet3d/src/loss.py index b91818183..4f66d40ae 100644 --- a/research/cv/resnet3d/src/loss.py +++ b/research/cv/resnet3d/src/loss.py @@ -18,7 +18,7 @@ define loss for resnet3d import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P import mindspore.ops as ops @@ -61,7 +61,7 @@ class SoftmaxCrossEntropyExpand(nn.Cell): # pylint: disable=missing-docstring return loss -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=101): diff --git a/research/cv/resnet50_bam/eval.py b/research/cv/resnet50_bam/eval.py index 7244e79ab..4f2240963 100644 --- a/research/cv/resnet50_bam/eval.py +++ b/research/cv/resnet50_bam/eval.py @@ -24,7 +24,7 @@ from mindspore.train.serialization import load_checkpoint, load_param_into_net from mindspore.common import set_seed from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -45,7 +45,7 @@ parser.add_argument('--device_id', type=str, default=0, help='Device id.') args_opt = parser.parse_args() -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/resnet50_bam/train.py b/research/cv/resnet50_bam/train.py index 0427dcc2a..59da4f65d 100644 --- a/research/cv/resnet50_bam/train.py +++ b/research/cv/resnet50_bam/train.py @@ -29,7 +29,7 @@ from mindspore.communication.management import get_group_size from mindspore.communication.management import get_rank from mindspore.communication.management import init from mindspore.context import ParallelMode -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.nn.optim.momentum import Momentum from mindspore.ops import functional as F from mindspore.ops import operations as P @@ -90,7 +90,7 @@ def warmup_cosine_annealing_lr(lr5, steps_per_epoch, warmup_epochs, max_epoch, T return np.array(lr_each_step).astype(np.float32) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/resnext152_64x4d/src/crossentropy.py b/research/cv/resnext152_64x4d/src/crossentropy.py index a5abe6021..01039e39e 100644 --- a/research/cv/resnext152_64x4d/src/crossentropy.py +++ b/research/cv/resnext152_64x4d/src/crossentropy.py @@ -15,14 +15,14 @@ """ define loss function for network. """ -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import operations as P from mindspore.ops import functional as F from mindspore import Tensor from mindspore.common import dtype as mstype import mindspore.nn as nn -class CrossEntropy(_Loss): +class CrossEntropy(LossBase): """ the redefined loss function with SoftmaxCrossEntropyWithLogits. """ diff --git a/research/cv/simple_baselines/src/network_with_loss.py b/research/cv/simple_baselines/src/network_with_loss.py index 011b8be01..d671e68ea 100644 --- a/research/cv/simple_baselines/src/network_with_loss.py +++ b/research/cv/simple_baselines/src/network_with_loss.py @@ -20,10 +20,10 @@ from __future__ import division import mindspore.nn as nn from mindspore.ops import operations as P from mindspore.ops import functional as F -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.common import dtype as mstype -class JointsMSELoss(_Loss): +class JointsMSELoss(LossBase): ''' JointsMSELoss ''' diff --git a/research/cv/single_path_nas/eval.py b/research/cv/single_path_nas/eval.py index cbba5a025..ddd8a3e4b 100644 --- a/research/cv/single_path_nas/eval.py +++ b/research/cv/single_path_nas/eval.py @@ -23,7 +23,7 @@ from mindspore import Tensor from mindspore import context from mindspore.common import dtype as mstype from mindspore.common import set_seed -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P from mindspore.train.model import Model @@ -48,7 +48,7 @@ parser.add_argument('--device_id', type=int, default=None, help='device id of As args_opt = parser.parse_args() -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/single_path_nas/src/CrossEntropySmooth.py b/research/cv/single_path_nas/src/CrossEntropySmooth.py index 6d63b6669..8400b5413 100644 --- a/research/cv/single_path_nas/src/CrossEntropySmooth.py +++ b/research/cv/single_path_nas/src/CrossEntropySmooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/sknet/src/CrossEntropySmooth.py b/research/cv/sknet/src/CrossEntropySmooth.py index 6d63b6669..8400b5413 100644 --- a/research/cv/sknet/src/CrossEntropySmooth.py +++ b/research/cv/sknet/src/CrossEntropySmooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/squeezenet1_1/src/CrossEntropySmooth.py b/research/cv/squeezenet1_1/src/CrossEntropySmooth.py index 6d63b6669..8400b5413 100644 --- a/research/cv/squeezenet1_1/src/CrossEntropySmooth.py +++ b/research/cv/squeezenet1_1/src/CrossEntropySmooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/swin_transformer/src/tools/criterion.py b/research/cv/swin_transformer/src/tools/criterion.py index 1afdd719f..ee963c1fe 100644 --- a/research/cv/swin_transformer/src/tools/criterion.py +++ b/research/cv/swin_transformer/src/tools/criterion.py @@ -17,12 +17,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore import ops from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class SoftTargetCrossEntropy(_Loss): +class SoftTargetCrossEntropy(LossBase): """SoftTargetCrossEntropy for MixUp Augment""" def __init__(self): @@ -38,7 +38,7 @@ class SoftTargetCrossEntropy(_Loss): return self.mean_ops(loss) -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): diff --git a/research/cv/tsm/src/model/cross_entropy_smooth.py b/research/cv/tsm/src/model/cross_entropy_smooth.py index 5b0b977e7..596a7c867 100644 --- a/research/cv/tsm/src/model/cross_entropy_smooth.py +++ b/research/cv/tsm/src/model/cross_entropy_smooth.py @@ -16,12 +16,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=174): super(CrossEntropySmooth, self).__init__() diff --git a/research/cv/wideresnet/src/cross_entropy_smooth.py b/research/cv/wideresnet/src/cross_entropy_smooth.py index a12c43aff..b6d43e1ef 100644 --- a/research/cv/wideresnet/src/cross_entropy_smooth.py +++ b/research/cv/wideresnet/src/cross_entropy_smooth.py @@ -17,12 +17,12 @@ import mindspore.nn as nn from mindspore import Tensor from mindspore.common import dtype as mstype -from mindspore.nn.loss.loss import _Loss +from mindspore.nn.loss.loss import LossBase from mindspore.ops import functional as F from mindspore.ops import operations as P -class CrossEntropySmooth(_Loss): +class CrossEntropySmooth(LossBase): """CrossEntropy""" def __init__(self, sparse=True, reduction='mean', smooth_factor=0., num_classes=1000): super(CrossEntropySmooth, self).__init__() -- GitLab