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* Clippy fixes for 1.81.0.
* Another fix.
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* onnx: fix pad, unsqueeze
both implementations have off-by-one errors:
- Pad 'reflect' cycle for eg `dim==3` is `[0,1,2,1]` which has length of
4 (or `dim*2 - 2`) not 5 (current code `dim*2 - 1`)
- Unsqueeze(-1) for tensor with `dim==3` should be 3 (ie `dim+index+1`)
not 2 (ie currently `dim+index`)
in addition, Pad is incorrectly calculating the starting padding.
If we want to pad out 2 elements to the start, and we have this cycle
of indices of length 6, then we should skip 4 elements, but currently
we skip 2. A more visual representation of what's going on is below:
```
pad_start: 2
data: [a,b,c,d]
indices: [0, 1, 2, 3, 2, 1, 0, 1, 2, 3, 2, 1, 0, ..] // zigzag between 0..4
actual: skip [ c d| c b a b]
expected: ~ skip ~ [ c b| a b c d]
```
The values between `[` and `|` are padding and the values between
`|` and `]` in the example should match the original data being padded.
* Fix clippy lints.
---------
Co-authored-by: Laurent <laurent.mazare@gmail.com>
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* Allow different dtypes in mamba.
* Add a dtype flag.
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* Update the image crate + use the re-exported version.
* Update to using ab_glyph.
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* Fix linspace implementation
`steps` should be strictly greater than 1 to make it consistent with the context.
* Handle steps == 0 and steps == 1.
* Fix rustfmt.
---------
Co-authored-by: laurent <laurent.mazare@gmail.com>
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* Add fuse-conv-bn method for Conv2d
* no unwrap
* run rustfmp and clippy
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* Simplify the safetensor usage.
* Convert more examples.
* Move more examples.
* Adapt stable-diffusion.
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* More readme tweaks.
* Update README.md
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* Add a readme for the segment-anything model.
* Add the original image.
* Clean-up the segment anything cli example.
* Also print the mask id in the outputs.
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* Move dinov2.
* Move efficientnet.
* Move the quantized llama model.
* Move segment-anything.
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* A few more contiguous fixes for cuda.
* Mask generation.
* Generic bbox.
* Generate all the masks.
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* Simplify usage of the pool functions.
* Small tweak.
* Attempt at using apply to simplify the convnet definition.
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* Add the dilation parameter.
* Restore the basic optimizer example.
* Dilation support in cudnn.
* Use the dilation parameter in the cpu backend.
* More dilation support.
* No support for dilation in transposed convolutions.
* Add dilation to a test.
* Remove a print.
* Helper function.
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* Remove some dead-code annotations.
* More dead code removal.
* One more.
* CI fix.
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* Add some configurable legend for yolo detection.
* Clippyness.
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* Move the yolo model bits in a separate file.
* Improve the drawing.
* Bugfix.
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* More support for pose estimation in yolo-v8.
* Support both object detection and pose-estimation in the yolo-v8 example.
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* Add the pose estimation head for yolo.
* Properly handle the added position dimensions.
* Integrate the pose estimation head in the forward pass.
* Renaming.
* Fix for pose estimation.
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* Add some group parameter to convolutions.
* Avoid some unnecessary groups checks.
* Move the tensor convolution bits.
* Properh handling of groups.
* Bump the crate version.
* And add a changelog.
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* Fix the aspect ratio handling in yolo-v8.
* Typo.
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* Move the yolo shared bits to a common place.
* Share more code.
* Configurable thresholds.
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* Sketch the yolo wasm example.
* Web ui.
* Get the web ui to work.
* UI tweaks.
* More UI tweaks.
* Use the natural width/height.
* Add a link to the hf space in the readme.
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* Use the weights from the hub.
* Add to the readme.
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* Fixes for the yolo-v8 layout.
* Bugfixes.
* Another silly bugfix.
* Remove the hf-hub dependency.
* Remove the transformers dependency.
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* Sketching yolo-v8.
* Get the model to load.
* yolo-v8 forward pass.
* Complete(?) the forward pass.
* Fix some shape issues.
* Add the missing padding.
* Process the predictions.
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