Improve vision models (#17731)
* Improve vision models * Add a lot of improvements * Remove to_2tuple from swin tests * Fix TF Swin * Fix more tests * Fix copies * Improve more models * Fix ViTMAE test * Add channel check for TF models * Add proper channel check for TF models * Apply suggestion from code review * Apply suggestions from code review * Add channel check for Flax models, apply suggestion * Fix bug * Add tests for greyscale images * Add test for interpolation of pos encodigns Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
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@@ -31,7 +31,7 @@ if is_torch_available():
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from torch import nn
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from transformers import YolosForObjectDetection, YolosModel
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from transformers.models.yolos.modeling_yolos import YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST, to_2tuple
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from transformers.models.yolos.modeling_yolos import YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST
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if is_vision_available():
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@@ -86,9 +86,7 @@ class YolosModelTester:
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self.num_detection_tokens = num_detection_tokens
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# we set the expected sequence length (which is used in several tests)
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# expected sequence length = num_patches + 1 (we add 1 for the [CLS] token) + num_detection_tokens
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image_size = to_2tuple(self.image_size)
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patch_size = to_2tuple(self.patch_size)
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num_patches = (image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
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num_patches = (image_size[1] // patch_size) * (image_size[0] // patch_size)
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self.expected_seq_len = num_patches + 1 + self.num_detection_tokens
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def prepare_config_and_inputs(self):
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