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Fix typos
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configs/legacy/sample/ilsvrc2012/single_stage/hnd/custom_inception_v3_from_inception_v3.yaml

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@@ -11,7 +11,7 @@ datasets:
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transform_params:
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- type: 'RandomResizedCrop'
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params:
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size: &input_size [224, 224]
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size: &input_size [299, 299]
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- type: 'RandomHorizontalFlip'
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params:
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p: 0.5
@@ -30,7 +30,7 @@ datasets:
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transform_params:
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- type: 'Resize'
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params:
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size: 256
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size: 327
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- type: 'CenterCrop'
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params:
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size: *input_size

configs/sample/ilsvrc2012/hnd/custom_inception_v3_from_inception_v3.yaml

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@@ -15,7 +15,7 @@ datasets:
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key: 'torchvision.transforms.RandomResizedCrop'
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init:
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kwargs:
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size: &input_size [224, 224]
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size: &input_size [299, 299]
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- !import_call
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key: 'torchvision.transforms.RandomHorizontalFlip'
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init:
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key: 'torchvision.transforms.Resize'
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init:
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kwargs:
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size: 256
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size: 327
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- !import_call
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key: 'torchvision.transforms.CenterCrop'
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init:
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weights: !getattr [*teacher_weights, 'IMAGENET1K_V1']
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src_ckpt:
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student_model:
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repo_or_dir: 'yoshitomo-matsubara/sc2-benchmark'
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key: &student_model_key 'custom_inception_v3'
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_weights: &student_weights !import_get
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key: 'torchvision.models.inception.Inception_V3_Weights'
@@ -131,11 +132,11 @@ train:
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student:
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forward_proc: 'forward_batch_only'
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adaptations:
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sequential: ['bottleneck']
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sequential: ['bottleneck_layer']
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frozen_modules: []
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forward_hook:
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input: []
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output: ['bottleneck']
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output: ['bottleneck_layer']
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wrapper: 'DistributedDataParallel'
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requires_grad: True
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optimizer:
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kwargs:
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input:
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is_from_teacher: False
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module_path: 'bottleneck'
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module_path: 'bottleneck_layer'
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io: 'output'
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target:
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is_from_teacher: True

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