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* Add files * Init * Add TimmWrapperModel * Fix up * Some fixes * Fix up * Remove old file * Sort out import orders * Fix some model loading * Compatible with pipeline and trainer * Fix up * Delete test_timm_model_1/config.json * Remove accidentally commited files * Delete src/transformers/models/modeling_timm_wrapper.py * Remove empty imports; fix transformations applied * Tidy up * Add image classifcation model to special cases * Create pretrained model; enable device_map='auto' * Enable most tests; fix init order * Sort imports * [run-slow] timm_wrapper * Pass num_classes into timm.create_model * Remove train transforms from image processor * Update timm creation with pretrained=False * Fix gamma/beta issue for timm models * Fixing gamma and beta renaming for timm models * Simplify config and model creation * Remove attn_implementation diff * Fixup * Docstrings * Fix warning msg text according to test case * Fix device_map auto * Set dtype and device for pixel_values in forward * Enable output hidden states * Enable tests for hidden_states and model parallel * Remove default scriptable arg * Refactor inner model * Update timm version * Fix _find_mismatched_keys function * Change inheritance for Classification model (fix weights loading with device_map) * Minor bugfix * Disable save pretrained for image processor * Rename hook method for loaded keys correction * Rename state dict keys on save, remove `timm_model` prefix, make checkpoint compatible with `timm` * Managing num_labels <-> num_classes attributes * Enable loading checkpoints in Trainer to resume training * Update error message for output_hidden_states * Add output hidden states test * Decouple base and classification models * Add more test cases * Add save-load-to-timm test * Fix test name * Fixup * Add do_pooling * Add test for do_pooling * Fix doc * Add tests for TimmWrapperModel * Add validation for `num_classes=0` in timm config + test for DINO checkpoint * Adjust atol for test * Fix docs * dev-ci * dev-ci * Add tests for image processor * Update docs * Update init to new format * Update docs in configuration * Fix some docs in image processor * Improve docs for modeling * fix for is_timm_checkpoint * Update code examples * Fix header * Fix typehint * Increase tolerance a bit * Fix Path * Fixing model parallel tests * Disable "parallel" tests * Add comment for metadata * Refactor AutoImageProcessor for timm wrapper loading * Remove custom test_model_outputs_equivalence * Add require_timm decorator * Fix comment * Make image processor work with older timm versions and tensor input * Save config instead of whole model in image processor tests * Add docstring for `image_processor_filename` * Sanitize kwargs for timm image processor * Fix doc style * Update check for tensor input * Update normalize * Remove _load_timm_model function --------- Co-authored-by: Amy Roberts <22614925+amyeroberts@users.noreply.github.com>
2.0 KiB
2.0 KiB
TimmWrapper
Overview
Helper class to enable loading timm models to be used with the transformers library and its autoclasses.
>>> import torch
>>> from PIL import Image
>>> from urllib.request import urlopen
>>> from transformers import AutoModelForImageClassification, AutoImageProcessor
>>> # Load image
>>> image = Image.open(urlopen(
... 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
... ))
>>> # Load model and image processor
>>> checkpoint = "timm/resnet50.a1_in1k"
>>> image_processor = AutoImageProcessor.from_pretrained(checkpoint)
>>> model = AutoModelForImageClassification.from_pretrained(checkpoint).eval()
>>> # Preprocess image
>>> inputs = image_processor(image)
>>> # Forward pass
>>> with torch.no_grad():
... logits = model(**inputs).logits
>>> # Get top 5 predictions
>>> top5_probabilities, top5_class_indices = torch.topk(logits.softmax(dim=1) * 100, k=5)
TimmWrapperConfig
autodoc TimmWrapperConfig
TimmWrapperImageProcessor
autodoc TimmWrapperImageProcessor - preprocess
TimmWrapperModel
autodoc TimmWrapperModel - forward
TimmWrapperForImageClassification
autodoc TimmWrapperForImageClassification - forward