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* implement config and model building blocks * refactor model architechture * update model outputs * update init param to include use_fov_model * update param name in config * fix hidden_states and attentions outputs for fov * sort config * complete minor todos * update patching * update config for encoder * fix config * use correct defaults in config * update merge for compatibility with different image size * restructure encoder for custom configuration * make fov model compatible with custom config * replace word "decoder" with "fusion" * weight conversion script * fix fov squeeze * update conversion script (without test) * upload ruff image processing * create fast image processing * use torch interpolation for image processing * complete post_process_depth_estimation * config: fix imports and sort args * apply inference in weight conversion * use mllama script instead for weight conversion * clean weight conversion script * add depth-pro status in other files * fill docstring in config * formatting * more formatting * formatting with ruff * formatting with style * fix copied classes * add examples; update weight convert script * fix using check_table.py and isort * fix config docstring * add depth pro to sdpa docs * undo unintentional changes in configuration_gemma.py * minor fixes * test image processing * fixes and tests * more fixes * use output states from image_encoder instead * Revert "use output states from image_encoder instead" This reverts commit2408ec54e4
. * make embeddings dynamic * reshape output hidden states and attentions as part of computation graph * fix ruff formating * fix docstring failure * use num_fov_head_layers in tests * update doc * check consistency with config * ruff formatting * update test case * fix ruff formatting * add tests for fov * use interpolation in postprocess * run and fix slow tests locally * use scaled_images_features for image and fov encoder * return fused_hidden_states in fusion stage * fix example * fix ruff * fix copyright license for all files * add __all__ for each file * minor fixes - fix download spell - add push_to_hub option - fix Optional type hinting - apply single loop for DepthProImageProcessor.preprocess * return list in post_process_depth_estimation * minor fixes - capitalize start of docstring - use ignore copy - fix examples - move docstring templates and custom output classes to top - remove "-> None" typehinting from __init__ - type hinting for forward passes - fix docstrings for custom output classes * fix "ruff check" * update upsample and projection * major changes: (image size and merge optimization) - add support for images of any size - optimize merge operation - remove image_size from config - use full names instead of B, C, H, W - remove interpolation from fusion stage - add interpolation after merge - move validations to config - update integration test - add type hints for functions * fix push_to_hub option in weights conversion * remove image_size in weights conversion * major changes in the architecture - remove all DepthProViT modules and support different backbones using the AutoModel API - set default use_fov_model to False - validate parameters in configuration - update interpolate function: use "nearest" for faster computation - update reshape_feature function: remove all special tokens, possible from different backbones - update merge function: use padding from config instead of merge_out_size - remove patch_to_batch and batch_to_patch conversions for now - calculate out_size dynamically in the encoder - leave head_mask calculation to the backbone - fix bugs with merge - add more comments - update tests * placeholder for unused config attributes * improve docs amid review * minor change in docs * further optimize merge * fix formatting * remove unused patch/batch convertion functions * use original F.interpolate * improve function naming * minor chages - use torch_int instead of int - use proper for newly initialized tensors - use user provided return_dict for patch_encoder - use if-else block instead in self.use_fov_model * rearchitect upsample block for improved modularity * update upsample keys in weight conversion * improve padding in merge_patches * use double-loop for merge * update comments * create feature_extractor, reduce some forward code * introduce config.use_mask_token in dinov2 * minor fixes * minor fixes for onnx * update __init__ to latest format * remove DepthProConfig.to_dict() * major changes in backbone * update config in weight conversion * formatting * converted model is fp32 * improve naming and docs for feature_extractor->reconstruct_feature_maps * minor fixes; amid review * create intermediate vars in func call * use torch.testing.assert_close * use ModuleList instead of Sequential and ModuleDict * update docs * include fov in integraiton tests * update docs * improve initialization of convolution layers * fix unused fov keys * update tests * ruff format * fix test, amid kaimming initialization * add depthpro to toctree * add residual layer to _no_split_modules * architecture rework * Update src/transformers/models/depth_pro/image_processing_depth_pro.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/depth_pro/image_processing_depth_pro_fast.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * update docs * improve merge_patches * use flatten with fov_output * ruff formatting * update resources section in docs Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * fix typo "final_kernal_size" Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * fix output typehint for DepthProDepthEstimator Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * residual operation in 2 steps Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * use image_size instead of global patch_size in interpolation * replace all Sequential with ModuleList * update fov * update heads * fix and update conversion script for heads * ruff formatting * remove float32 conversion * use "Fov" instead of "FOV" in class names * use "Fov" instead of "FOV" in config docs * remove prune_heads * update fusion stage * use device in examples * update processor * ruff fixes * add do_rescale in image_processor_dict * skip test: test_fast_is_faster_than_slow * ruff formatting * DepthProImageProcessorFast in other files * revert antialias removal * add antialias in BaseImageProcessorFast * Revert "revert antialias removal" This reverts commit5caa0bd8f9
. * Revert "add antialias in BaseImageProcessorFast" This reverts commit3ae1134780
. * update processor for grouping and antialias * try test_fast_is_faster_than_slow without "skip" or "flanky" * update checkpoint * update checkpoint * use @is_flanky for processor test * update checkpoint to "apple/DepthPro-hf" --------- Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
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Python
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Python