support ppyolo for kunlun (#1898)

* support ppyolo for kunlun

configs/ppyolo/ppyolo_roadsign_kunlun.yml

+architecture: YOLOv3
+use_gpu: false
+use_xpu: true
+max_iters: 5000
+log_iter: 1
+save_dir: output
+snapshot_iter: 500
+metric: VOC
+pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/ppyolo.pdparams
+weights: output/ppyolo_roadsign_kunlun/model_final
+num_classes: 4
+finetune_exclude_pretrained_params: ['yolo_output']
+use_fine_grained_loss: true
+use_ema: true
+ema_decay: 0.9998
+
+YOLOv3:
+  backbone: ResNet
+  yolo_head: YOLOv3Head
+  use_fine_grained_loss: true
+
+ResNet:
+  norm_type: 'bn'
+  freeze_at: 0
+  freeze_norm: false
+  norm_decay: 0.
+  depth: 50
+  feature_maps: [3, 4, 5]
+  variant: d
+  dcn_v2_stages: [5]
+
+YOLOv3Head:
+  anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
+  anchors: [[10, 13], [16, 30], [33, 23],
+            [30, 61], [62, 45], [59, 119],
+            [116, 90], [156, 198], [373, 326]]
+  norm_decay: 0.
+  coord_conv: true
+  iou_aware: true
+  iou_aware_factor: 0.4
+  scale_x_y: 1.05
+  spp: true
+  yolo_loss: YOLOv3Loss
+  nms: MatrixNMS
+  drop_block: true
+
+YOLOv3Loss:
+  ignore_thresh: 0.7
+  scale_x_y: 1.05
+  label_smooth: false
+  use_fine_grained_loss: true
+  iou_loss: IouLoss
+  iou_aware_loss: IouAwareLoss
+
+IouLoss:
+  loss_weight: 2.5
+  max_height: 608
+  max_width: 608
+
+IouAwareLoss:
+  loss_weight: 1.0
+  max_height: 608
+  max_width: 608
+
+MatrixNMS:
+    background_label: -1
+    keep_top_k: 100
+    normalized: false
+    score_threshold: 0.01
+    post_threshold: 0.01
+
+LearningRate:
+  base_lr: 0.0001
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones:
+    - 800
+    - 110
+  - !LinearWarmup
+    start_factor: 0
+    steps: 100
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0005
+    type: L2
+
+TrainReader:
+  inputs_def:
+    fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
+    num_max_boxes: 50
+  dataset:
+    !VOCDataSet
+      dataset_dir: dataset/roadsign_voc
+      anno_path: train.txt
+      with_background: false
+  sample_transforms:
+    - !DecodeImage
+      to_rgb: True
+      with_mixup: True
+    - !MixupImage
+      alpha: 1.5
+      beta: 1.5
+    - !ColorDistort {}
+    - !RandomExpand
+      fill_value: [123.675, 116.28, 103.53]
+      ratio: 1.5
+    - !RandomCrop {}
+    - !RandomFlipImage
+      is_normalized: false
+    - !NormalizeBox {}
+    - !PadBox
+      num_max_boxes: 50
+    - !BboxXYXY2XYWH {}
+  batch_transforms:
+  - !RandomShape
+    sizes: [320]
+    random_inter: True
+  - !NormalizeImage
+    mean: [0.485, 0.456, 0.406]
+    std: [0.229, 0.224, 0.225]
+    is_scale: True
+    is_channel_first: false
+  - !Permute
+    to_bgr: false
+    channel_first: True
+  - !Gt2YoloTarget
+    anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
+    anchors: [[10, 13], [16, 30], [33, 23],
+              [30, 61], [62, 45], [59, 119],
+              [116, 90], [156, 198], [373, 326]]
+    downsample_ratios: [32, 16, 8]
+  batch_size: 8
+  shuffle: true
+  mixup_epoch: 250
+  drop_last: true
+  worker_num: 2
+  bufsize: 2
+  use_process: false #true
+
+
+EvalReader:
+  inputs_def:
+    fields: ['image', 'im_size', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
+    num_max_boxes: 50
+  dataset:
+    !VOCDataSet
+      dataset_dir: dataset/roadsign_voc
+      anno_path: valid.txt
+      with_background: false
+  sample_transforms:
+    - !DecodeImage
+      to_rgb: True
+    - !ResizeImage
+      target_size: 608
+      interp: 2
+    - !NormalizeImage
+      mean: [0.485, 0.456, 0.406]
+      std: [0.229, 0.224, 0.225]
+      is_scale: True
+      is_channel_first: false
+    - !PadBox
+      num_max_boxes: 50
+    - !Permute
+      to_bgr: false
+      channel_first: True
+  batch_size: 1
+  drop_empty: false
+  worker_num: 4
+  bufsize: 2
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 608, 608]
+    fields: ['image', 'im_size', 'im_id']
+  dataset:
+    !ImageFolder
+      anno_path: dataset/roadsign_voc/label_list.txt
+      with_background: false
+  sample_transforms:
+    - !DecodeImage
+      to_rgb: True
+    - !ResizeImage
+      target_size: 608
+      interp: 2
+    - !NormalizeImage
+      mean: [0.485, 0.456, 0.406]
+      std: [0.229, 0.224, 0.225]
+      is_scale: True
+      is_channel_first: false
+    - !Permute
+      to_bgr: false
+      channel_first: True
+  batch_size: 1

docs/tutorials/train_on_kunlun.md

+# How to train on kunlun
+
+## Prepare kunlun environment
+[Paddle installation for machines with Kunlun XPU card](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/2.0-rc1/install/install_Kunlun_zh.html)
+
+## yolov3
+
+### Prepare data
+Prepare data roadsign
+
+
+### Train
+```shell
+python3.7 -u tools/train.py -c configs/yolov3_mobilenet_v1_roadsign.yml -o use_gpu=False use_xpu=True
+```
+
+
+### Eval
+```shell
+python3.7 -u tools/eval.py -c configs/yolov3_mobilenet_v1_roadsign.yml -o weights=output/yolov3_mobilenet_v1_roadsign/model_final.pdparams use_gpu=False use_xpu=True
+```
+
+
+## ppyolo
+
+### Prepare data
+Prepare data roadsign
+
+
+### Train
+```shell
+python3.7 -u tools/train.py --eval -c configs/ppyolo/ppyolo_roadsign_kunlun.yml
+```
+
+
+### Eval
+```shell
+python3.7 -u tools/eval.py -c configs/ppyolo/ppyolo_roadsign_kunlun.yml
+```