maml

Author: yinhaofeng

datasets/omniglot/download.sh

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+wget https://paddlerec.bj.bcebos.com/datasets/omniglot/omniglot_python.zip
+unzip omniglot_python.zip
+mv images_evaluation/* images_background/
+mv images_background omniglot_raw
+rm -rf demo.py images_background_small1 images_background_small2 images_evaluation/ one-shot-classification strokes_*
+python preprocess.py

datasets/omniglot/preprocess.py

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+# Copyright (c) 2021 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.
+
+import os
+import cv2
+import numpy as np
+import random
+import shutil
+
+data_folder = './omniglot_raw'  # omniglot数据集路径
+
+character_folders = [os.path.join(data_folder, family, character) \
+                     for family in os.listdir(data_folder) \
+                     if os.path.isdir(os.path.join(data_folder, family)) \
+                     for character in os.listdir(os.path.join(data_folder, family))]
+print("The number of character folders: {}".format(len(
+    character_folders)))  # 1623
+random.seed(1)
+random.shuffle(character_folders)
+train_folders = character_folders[:973]
+val_folders = character_folders[973:1298]
+test_folders = character_folders[1298:]
+print('The number of train characters is {}'.format(len(train_folders)))  # 973
+print('The number of validation characters is {}'.format(len(
+    val_folders)))  # 325
+print('The number of test characters is {}'.format(len(test_folders)))  # 325
+
+for char_fold in train_folders:
+    path = char_fold.split("/")
+    path[1] = "omniglot_train"
+    shutil.copytree(char_fold, "/".join(path))
+
+for char_fold in val_folders:
+    path = char_fold.split("/")
+    path[1] = "omniglot_valid"
+    shutil.copytree(char_fold, "/".join(path))
+
+for char_fold in test_folders:
+    path = char_fold.split("/")
+    path[1] = "omniglot_test"
+    shutil.copytree(char_fold, "/".join(path))

datasets/omniglot/run.sh

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+wget https://paddlerec.bj.bcebos.com/datasets/omniglot/omniglot.tar
+tar -xf omniglot.tar

datasets/readme.md

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+# Copyright (c) 2020 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.
+
+# global settings 
+
+runner:
+  train_data_dir: "./data"
+  train_reader_path: "omniglot_reader" # importlib format
+  use_gpu: True
+  use_auc: False
+  train_batch_size: 32
+  epochs: 1
+  print_interval: 10
+  model_save_path: "output_model_maml"
+  test_data_dir: "./data"
+  infer_reader_path: "omniglot_reader" # importlib format
+  infer_batch_size: 32
+  infer_load_path: "output_model_maml"
+  infer_start_epoch: 0
+  infer_end_epoch: 1
+
+# hyper parameters of user-defined network
+hyper_parameters:
+  # optimizer config
+  meta_optimizer:
+    class: Adam
+    learning_rate: 0.001
+    strategy: async
+  base_optimizer:
+    class: SGD
+    learning_rate: 0.1
+    strategy: async
+  # user-defined <key, value> pairs
+  update_step: 5
+  update_step_test: 5
+  n_way: 5
+  k_spt: 1
+  k_query: 15
+  imgsize: 28
+  conv_stride: 1
+  conv_padding: 1
+  conv_kernal: [3, 3]
+  bn_channel: 64

doc/imgs/maml.png

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+# Copyright (c) 2020 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.
+
+# global settings 
+
+runner:
+  train_data_dir: "../../../datasets/omniglot/omniglot_train"
+  train_reader_path: "omniglot_reader" # importlib format
+  use_gpu: True
+  use_auc: False
+  train_batch_size: 32
+  epochs: 100
+  print_interval: 10
+  model_save_path: "output_model_all_maml"
+  test_data_dir: "../../../datasets/omniglot/omniglot_test"
+  infer_reader_path: "omniglot_reader" # importlib format
+  infer_batch_size: 32
+  infer_load_path: "output_model_all_maml"
+  infer_start_epoch: 90
+  infer_end_epoch: 91
+
+# hyper parameters of user-defined network
+hyper_parameters:
+  # optimizer config
+  meta_optimizer:
+    class: Adam
+    learning_rate: 0.001
+    strategy: async
+  base_optimizer:
+    class: SGD
+    learning_rate: 0.1
+    strategy: async
+  # user-defined <key, value> pairs
+  update_step: 5
+  update_step_test: 5
+  n_way: 5
+  k_spt: 1
+  k_query: 15
+  imgsize: 28
+  conv_stride: 1
+  conv_padding: 1
+  conv_kernal: [3, 3]
+  bn_channel: 64