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README.md
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---
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license: apache-2.0
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dataset_info:
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features:
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- name: id
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dtype: int32
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- name: x
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sequence: image
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- name: color
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dtype:
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class_label:
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names:
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'0': DarkSlateGray
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'1': OrangeRed
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'2': Yellow
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'3': SpringGreen
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'4': Cyan
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'5': Purple
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'6': DodgerBlue
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'7': DeepPink
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'8': NavajoWhite
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- name: shape
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dtype:
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class_label:
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names:
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'0': square
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'1': ellipse
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'2': heart
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- name: scale
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dtype:
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class_label:
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names:
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'0': '0.5'
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'1': '1.0'
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- name: orientation
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dtype:
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class_label:
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names:
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'0': '0.0'
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- name: posX
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dtype:
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class_label:
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names:
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'0': '0.06451612903225806'
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'1': '0.1935483870967742'
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'2': '0.3225806451612903'
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'3': '0.45161290322580644'
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'4': '0.5806451612903226'
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'5': '0.7096774193548387'
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'6': '0.8387096774193549'
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'7': '0.967741935483871'
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- name: posY
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dtype:
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class_label:
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names:
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'0': '0.06451612903225806'
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'1': '0.1935483870967742'
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'2': '0.3225806451612903'
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'3': '0.45161290322580644'
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'4': '0.5806451612903226'
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'5': '0.7096774193548387'
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'6': '0.8387096774193549'
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'7': '0.967741935483871'
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- name: scale_dynamic
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dtype:
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class_label:
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names:
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'0': increasing_1x
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'1': decreasing_1x
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'2': increasing_2x
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'3': decreasing_2x
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'4': increasing_3x
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'5': decreasing_3x
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- name: orientation_dynamic
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dtype:
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class_label:
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names:
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'0': counterclockwise
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'1': static
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'2': clockwise
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splits:
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- name: train
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num_bytes: 37545438.056
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num_examples: 21772
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- name: val
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num_bytes: 13310365.304
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num_examples: 4666
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- name: test
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num_bytes: 13289012.304
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num_examples: 4666
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download_size: 54642367
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dataset_size: 64144815.664
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: val
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path: data/val-*
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- split: test
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path: data/test-*
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---
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---
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license: apache-2.0
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dataset_info:
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features:
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- name: id
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dtype: int32
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- name: x
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sequence: image
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- name: color
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dtype:
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class_label:
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names:
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'0': DarkSlateGray
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'1': OrangeRed
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'2': Yellow
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'3': SpringGreen
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'4': Cyan
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'5': Purple
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'6': DodgerBlue
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'7': DeepPink
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'8': NavajoWhite
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- name: shape
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dtype:
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class_label:
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names:
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'0': square
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'1': ellipse
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'2': heart
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- name: scale
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dtype:
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class_label:
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names:
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'0': '0.5'
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'1': '1.0'
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- name: orientation
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dtype:
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class_label:
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names:
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'0': '0.0'
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- name: posX
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dtype:
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class_label:
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names:
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'0': '0.06451612903225806'
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| 45 |
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'1': '0.1935483870967742'
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| 46 |
+
'2': '0.3225806451612903'
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| 47 |
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'3': '0.45161290322580644'
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| 48 |
+
'4': '0.5806451612903226'
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| 49 |
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'5': '0.7096774193548387'
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'6': '0.8387096774193549'
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'7': '0.967741935483871'
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- name: posY
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dtype:
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class_label:
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names:
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'0': '0.06451612903225806'
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'1': '0.1935483870967742'
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| 58 |
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'2': '0.3225806451612903'
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| 59 |
+
'3': '0.45161290322580644'
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| 60 |
+
'4': '0.5806451612903226'
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| 61 |
+
'5': '0.7096774193548387'
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| 62 |
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'6': '0.8387096774193549'
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'7': '0.967741935483871'
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- name: scale_dynamic
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dtype:
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class_label:
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names:
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'0': increasing_1x
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'1': decreasing_1x
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'2': increasing_2x
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'3': decreasing_2x
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'4': increasing_3x
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'5': decreasing_3x
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- name: orientation_dynamic
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dtype:
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class_label:
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names:
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'0': counterclockwise
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'1': static
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'2': clockwise
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splits:
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- name: train
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num_bytes: 37545438.056
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| 84 |
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num_examples: 21772
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+
- name: val
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num_bytes: 13310365.304
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num_examples: 4666
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- name: test
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num_bytes: 13289012.304
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num_examples: 4666
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download_size: 54642367
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dataset_size: 64144815.664
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: val
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path: data/val-*
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- split: test
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path: data/test-*
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---
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## MSD dSprites-Static Dataset Attribution
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The Multi-factor Sequential Disentanglement benchmark includes a **modified variant of the dSprites dataset**, adapted to support sequential multi-factor disentanglement.
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- Original repository:
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https://github.com/deepmind/dsprites-dataset
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- Reference paper:
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M. Higgins, L. Matthey, A. Pal, C. Burgess, X. Glorot, M. Botvinick, S. Mohamed, A. Lerchner.
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*beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework*, ICLR 2017.
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https://openreview.net/forum?id=Sy2fzU9gl
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⚠ **Note:** The dSprites dataset is licensed under the Apache License 2.0. We redistribute it here solely for non-commercial research purposes, following the original license terms. Please cite the above paper when using this dataset in your work.
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In this modified sequential version, the object is colorized and remains static in position, while the dynamic factors are its **scale** and **orientation**, allowing targeted evaluation of disentanglement in temporal settings.
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