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annotate constants.py @ 11:c5150cceab47 draft default tip

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planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
author goeckslab
date Sat, 18 Oct 2025 03:17:09 +0000
parents 85e6f4b2ad18
children
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186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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1 from typing import Any, Dict
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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3 # --- Constants ---
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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4 SPLIT_COLUMN_NAME = "split"
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5 LABEL_COLUMN_NAME = "label"
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6 IMAGE_PATH_COLUMN_NAME = "image_path"
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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7 DEFAULT_SPLIT_PROBABILITIES = [0.7, 0.1, 0.2]
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8 TEMP_CSV_FILENAME = "processed_data_for_ludwig.csv"
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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9 TEMP_CONFIG_FILENAME = "ludwig_config.yaml"
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c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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10 TEMP_DIR_PREFIX = "gleam_image_work_"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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11 PREDICTIONS_PARQUET_FILE_NAME = "predictions.parquet"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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12 TEST_STATISTICS_FILE_NAME = "test_statistics.json"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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13 TRAIN_SET_METADATA_FILE_NAME = "train_set_metadata.json"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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14 DESCRIPTION_FILE_NAME = "description.json"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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15 TRAINING_STATISTICS_FILE_NAME = "training_statistics.json"
c5150cceab47 planemo upload for repository https://github.com/goeckslab/gleam.git commit 0fe927b618cd4dfc87af7baaa827034cc6813225
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16 PREDICTIONS_SHAPES_FILE_NAME = "predictions.shapes"
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186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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17 MODEL_ENCODER_TEMPLATES: Dict[str, Any] = {
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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18 "stacked_cnn": "stacked_cnn",
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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19 "resnet18": {"type": "resnet", "model_variant": 18},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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20 "resnet34": {"type": "resnet", "model_variant": 34},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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21 "resnet50": {"type": "resnet", "model_variant": 50},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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22 "resnet101": {"type": "resnet", "model_variant": 101},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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23 "resnet152": {"type": "resnet", "model_variant": 152},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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24 "resnext50_32x4d": {"type": "resnext", "model_variant": "50_32x4d"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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25 "resnext101_32x8d": {"type": "resnext", "model_variant": "101_32x8d"},
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26 "resnext101_64x4d": {"type": "resnext", "model_variant": "101_64x4d"},
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27 "resnext152_32x8d": {"type": "resnext", "model_variant": "152_32x8d"},
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28 "wide_resnet50_2": {"type": "wide_resnet", "model_variant": "50_2"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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29 "wide_resnet101_2": {"type": "wide_resnet", "model_variant": "101_2"},
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30 "wide_resnet103_2": {"type": "wide_resnet", "model_variant": "103_2"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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31 "efficientnet_b0": {"type": "efficientnet", "model_variant": "b0"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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32 "efficientnet_b1": {"type": "efficientnet", "model_variant": "b1"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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33 "efficientnet_b2": {"type": "efficientnet", "model_variant": "b2"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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34 "efficientnet_b3": {"type": "efficientnet", "model_variant": "b3"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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35 "efficientnet_b4": {"type": "efficientnet", "model_variant": "b4"},
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36 "efficientnet_b5": {"type": "efficientnet", "model_variant": "b5"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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37 "efficientnet_b6": {"type": "efficientnet", "model_variant": "b6"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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38 "efficientnet_b7": {"type": "efficientnet", "model_variant": "b7"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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39 "efficientnet_v2_s": {"type": "efficientnet", "model_variant": "v2_s"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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40 "efficientnet_v2_m": {"type": "efficientnet", "model_variant": "v2_m"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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41 "efficientnet_v2_l": {"type": "efficientnet", "model_variant": "v2_l"},
186424a7eca7 planemo upload for repository https://github.com/goeckslab/gleam.git commit 91fa4aba245520fc0680088a07cead66bcfd4ed2
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42 "regnet_y_400mf": {"type": "regnet", "model_variant": "y_400mf"},
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43 "regnet_y_800mf": {"type": "regnet", "model_variant": "y_800mf"},
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44 "regnet_y_1_6gf": {"type": "regnet", "model_variant": "y_1_6gf"},
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45 "regnet_y_3_2gf": {"type": "regnet", "model_variant": "y_3_2gf"},
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46 "regnet_y_8gf": {"type": "regnet", "model_variant": "y_8gf"},
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47 "regnet_y_16gf": {"type": "regnet", "model_variant": "y_16gf"},
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48 "regnet_y_32gf": {"type": "regnet", "model_variant": "y_32gf"},
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49 "regnet_y_128gf": {"type": "regnet", "model_variant": "y_128gf"},
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50 "regnet_x_400mf": {"type": "regnet", "model_variant": "x_400mf"},
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51 "regnet_x_800mf": {"type": "regnet", "model_variant": "x_800mf"},
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52 "regnet_x_1_6gf": {"type": "regnet", "model_variant": "x_1_6gf"},
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53 "regnet_x_3_2gf": {"type": "regnet", "model_variant": "x_3_2gf"},
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54 "regnet_x_8gf": {"type": "regnet", "model_variant": "x_8gf"},
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55 "regnet_x_16gf": {"type": "regnet", "model_variant": "x_16gf"},
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56 "regnet_x_32gf": {"type": "regnet", "model_variant": "x_32gf"},
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57 "vgg11": {"type": "vgg", "model_variant": 11},
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58 "vgg11_bn": {"type": "vgg", "model_variant": "11_bn"},
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59 "vgg13": {"type": "vgg", "model_variant": 13},
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60 "vgg13_bn": {"type": "vgg", "model_variant": "13_bn"},
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61 "vgg16": {"type": "vgg", "model_variant": 16},
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62 "vgg16_bn": {"type": "vgg", "model_variant": "16_bn"},
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63 "vgg19": {"type": "vgg", "model_variant": 19},
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64 "vgg19_bn": {"type": "vgg", "model_variant": "19_bn"},
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65 "shufflenet_v2_x0_5": {"type": "shufflenet_v2", "model_variant": "x0_5"},
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66 "shufflenet_v2_x1_0": {"type": "shufflenet_v2", "model_variant": "x1_0"},
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67 "shufflenet_v2_x1_5": {"type": "shufflenet_v2", "model_variant": "x1_5"},
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68 "shufflenet_v2_x2_0": {"type": "shufflenet_v2", "model_variant": "x2_0"},
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69 "squeezenet1_0": {"type": "squeezenet", "model_variant": "1_0"},
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70 "squeezenet1_1": {"type": "squeezenet", "model_variant": "1_1"},
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71 "swin_t": {"type": "swin_transformer", "model_variant": "t"},
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72 "swin_s": {"type": "swin_transformer", "model_variant": "s"},
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73 "swin_b": {"type": "swin_transformer", "model_variant": "b"},
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74 "swin_v2_t": {"type": "swin_transformer", "model_variant": "v2_t"},
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75 "swin_v2_s": {"type": "swin_transformer", "model_variant": "v2_s"},
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76 "swin_v2_b": {"type": "swin_transformer", "model_variant": "v2_b"},
3
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77 "vit_b_16": {"type": "vit", "model_variant": "b_16"},
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78 "vit_b_32": {"type": "vit", "model_variant": "b_32"},
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79 "vit_l_16": {"type": "vit", "model_variant": "l_16"},
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80 "vit_l_32": {"type": "vit", "model_variant": "l_32"},
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81 "vit_h_14": {"type": "vit", "model_variant": "h_14"},
11
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82 "vit_huge_timm": {"type": "vit", "model_variant": "huge_timm", "custom_encoder": True},
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83 # MetaFormer family (support all variants via custom_model)
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84 "identityformer_s12": {"type": "stacked_cnn", "custom_model": "identityformer_s12", "use_pretrained": True, "trainable": True},
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85 "identityformer_s24": {"type": "stacked_cnn", "custom_model": "identityformer_s24", "use_pretrained": True, "trainable": True},
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86 "identityformer_s36": {"type": "stacked_cnn", "custom_model": "identityformer_s36", "use_pretrained": True, "trainable": True},
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87 "identityformer_m36": {"type": "stacked_cnn", "custom_model": "identityformer_m36", "use_pretrained": True, "trainable": True},
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88 "identityformer_m48": {"type": "stacked_cnn", "custom_model": "identityformer_m48", "use_pretrained": True, "trainable": True},
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89
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90 "randformer_s12": {"type": "stacked_cnn", "custom_model": "randformer_s12", "use_pretrained": True, "trainable": True},
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91 "randformer_s24": {"type": "stacked_cnn", "custom_model": "randformer_s24", "use_pretrained": True, "trainable": True},
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92 "randformer_s36": {"type": "stacked_cnn", "custom_model": "randformer_s36", "use_pretrained": True, "trainable": True},
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93 "randformer_m36": {"type": "stacked_cnn", "custom_model": "randformer_m36", "use_pretrained": True, "trainable": True},
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94 "randformer_m48": {"type": "stacked_cnn", "custom_model": "randformer_m48", "use_pretrained": True, "trainable": True},
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95
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96 "poolformerv2_s12": {"type": "stacked_cnn", "custom_model": "poolformerv2_s12", "use_pretrained": True, "trainable": True},
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97 "poolformerv2_s24": {"type": "stacked_cnn", "custom_model": "poolformerv2_s24", "use_pretrained": True, "trainable": True},
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98 "poolformerv2_s36": {"type": "stacked_cnn", "custom_model": "poolformerv2_s36", "use_pretrained": True, "trainable": True},
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99 "poolformerv2_m36": {"type": "stacked_cnn", "custom_model": "poolformerv2_m36", "use_pretrained": True, "trainable": True},
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100 "poolformerv2_m48": {"type": "stacked_cnn", "custom_model": "poolformerv2_m48", "use_pretrained": True, "trainable": True},
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101
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102 "convformer_s18": {"type": "stacked_cnn", "custom_model": "convformer_s18", "use_pretrained": True, "trainable": True},
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103 "convformer_s18_384": {"type": "stacked_cnn", "custom_model": "convformer_s18_384", "use_pretrained": True, "trainable": True},
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104 "convformer_s18_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_s18_in21ft1k", "use_pretrained": True, "trainable": True},
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105 "convformer_s18_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_s18_384_in21ft1k", "use_pretrained": True, "trainable": True},
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106 "convformer_s18_in21k": {"type": "stacked_cnn", "custom_model": "convformer_s18_in21k", "use_pretrained": True, "trainable": True},
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107 "convformer_s36": {"type": "stacked_cnn", "custom_model": "convformer_s36", "use_pretrained": True, "trainable": True},
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108 "convformer_s36_384": {"type": "stacked_cnn", "custom_model": "convformer_s36_384", "use_pretrained": True, "trainable": True},
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109 "convformer_s36_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_s36_in21ft1k", "use_pretrained": True, "trainable": True},
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110 "convformer_s36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_s36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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111 "convformer_s36_in21k": {"type": "stacked_cnn", "custom_model": "convformer_s36_in21k", "use_pretrained": True, "trainable": True},
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112 "convformer_m36": {"type": "stacked_cnn", "custom_model": "convformer_m36", "use_pretrained": True, "trainable": True},
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113 "convformer_m36_384": {"type": "stacked_cnn", "custom_model": "convformer_m36_384", "use_pretrained": True, "trainable": True},
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114 "convformer_m36_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_m36_in21ft1k", "use_pretrained": True, "trainable": True},
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115 "convformer_m36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_m36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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116 "convformer_m36_in21k": {"type": "stacked_cnn", "custom_model": "convformer_m36_in21k", "use_pretrained": True, "trainable": True},
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117 "convformer_b36": {"type": "stacked_cnn", "custom_model": "convformer_b36", "use_pretrained": True, "trainable": True},
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118 "convformer_b36_384": {"type": "stacked_cnn", "custom_model": "convformer_b36_384", "use_pretrained": True, "trainable": True},
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119 "convformer_b36_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_b36_in21ft1k", "use_pretrained": True, "trainable": True},
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120 "convformer_b36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "convformer_b36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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121 "convformer_b36_in21k": {"type": "stacked_cnn", "custom_model": "convformer_b36_in21k", "use_pretrained": True, "trainable": True},
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122
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123 "caformer_s18": {
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124 "type": "stacked_cnn",
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125 "custom_model": "caformer_s18",
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126 "use_pretrained": True,
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127 "trainable": True,
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128 },
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129 "caformer_s36": {
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130 "type": "stacked_cnn",
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131 "custom_model": "caformer_s36",
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132 "use_pretrained": True,
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133 "trainable": True,
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134 },
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135 "caformer_m36": {
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136 "type": "stacked_cnn",
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137 "custom_model": "caformer_m36",
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138 "use_pretrained": True,
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139 "trainable": True,
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140 },
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141 "caformer_b36": {
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142 "type": "stacked_cnn",
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143 "custom_model": "caformer_b36",
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144 "use_pretrained": True,
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145 "trainable": True,
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146 },
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147 "caformer_s18_384": {"type": "stacked_cnn", "custom_model": "caformer_s18_384", "use_pretrained": True, "trainable": True},
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148 "caformer_s18_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_s18_in21ft1k", "use_pretrained": True, "trainable": True},
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149 "caformer_s18_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_s18_384_in21ft1k", "use_pretrained": True, "trainable": True},
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150 "caformer_s18_in21k": {"type": "stacked_cnn", "custom_model": "caformer_s18_in21k", "use_pretrained": True, "trainable": True},
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151 "caformer_s36_384": {"type": "stacked_cnn", "custom_model": "caformer_s36_384", "use_pretrained": True, "trainable": True},
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152 "caformer_s36_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_s36_in21ft1k", "use_pretrained": True, "trainable": True},
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153 "caformer_s36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_s36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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154 "caformer_s36_in21k": {"type": "stacked_cnn", "custom_model": "caformer_s36_in21k", "use_pretrained": True, "trainable": True},
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155 "caformer_m36_384": {"type": "stacked_cnn", "custom_model": "caformer_m36_384", "use_pretrained": True, "trainable": True},
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156 "caformer_m36_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_m36_in21ft1k", "use_pretrained": True, "trainable": True},
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157 "caformer_m36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_m36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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158 "caformer_m36_in21k": {"type": "stacked_cnn", "custom_model": "caformer_m36_in21k", "use_pretrained": True, "trainable": True},
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159 "caformer_b36_384": {"type": "stacked_cnn", "custom_model": "caformer_b36_384", "use_pretrained": True, "trainable": True},
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160 "caformer_b36_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_b36_in21ft1k", "use_pretrained": True, "trainable": True},
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161 "caformer_b36_384_in21ft1k": {"type": "stacked_cnn", "custom_model": "caformer_b36_384_in21ft1k", "use_pretrained": True, "trainable": True},
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162 "caformer_b36_in21k": {"type": "stacked_cnn", "custom_model": "caformer_b36_in21k", "use_pretrained": True, "trainable": True},
2
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163 "convnext_tiny": {"type": "convnext", "model_variant": "tiny"},
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164 "convnext_small": {"type": "convnext", "model_variant": "small"},
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165 "convnext_base": {"type": "convnext", "model_variant": "base"},
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166 "convnext_large": {"type": "convnext", "model_variant": "large"},
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167 "maxvit_t": {"type": "maxvit", "model_variant": "t"},
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168 "alexnet": {"type": "alexnet"},
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169 "googlenet": {"type": "googlenet"},
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170 "inception_v3": {"type": "inceptionv3"},
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171 "mobilenet_v2": {"type": "mobilenet_v2"},
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172 "mobilenet_v3_large": {"type": "mobilenetv3", "model_variant": "large"},
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173 "mobilenet_v3_small": {"type": "mobilenetv3", "model_variant": "small"},
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174 }
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175 METRIC_DISPLAY_NAMES = {
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176 "accuracy": "Accuracy",
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177 "accuracy_micro": "Micro Accuracy",
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178 "loss": "Loss",
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179 "roc_auc": "ROC-AUC",
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180 "roc_auc_macro": "Macro ROC-AUC",
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181 "roc_auc_micro": "Micro ROC-AUC",
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182 "hits_at_k": "Hits at K",
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183 "precision": "Precision",
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184 "recall": "Recall",
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185 "specificity": "Specificity",
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186 "kappa_score": "Cohen's Kappa",
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187 "token_accuracy": "Token Accuracy",
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188 "avg_precision_macro": "Macro Precision",
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189 "avg_recall_macro": "Macro Recall",
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190 "avg_f1_score_macro": "Macro F1-score",
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191 "avg_precision_micro": "Micro Precision",
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192 "avg_recall_micro": "Micro Recall",
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193 "avg_f1_score_micro": "Micro F1-score",
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194 "avg_precision_weighted": "Weighted Precision",
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195 "avg_recall_weighted": "Weighted Recall",
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196 "avg_f1_score_weighted": "Weighted F1-score",
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197 "average_precision_macro": "Macro Precision-Average",
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198 "average_precision_micro": "Micro Precision-Average",
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199 "average_precision_samples": "Precision-Average-Samples",
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200 "mean_squared_error": "Mean Squared Error",
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201 "mean_absolute_error": "Mean Absolute Error",
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202 "r2": "R² Score",
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203 "root_mean_squared_error": "Root Mean Squared Error",
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204 "mean_absolute_percentage_error": "Mean Absolute % Error",
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205 "root_mean_squared_percentage_error": "Root Mean Squared % Error",
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206 }