* new upcast works
* float4 try
* fix unaligned float4
* disallow unaligned access
* upcast dim
* maybe good now
* fix gpu half
* vstore_half4
* fix deep image bugs
* improve symbolic to fix issues
* fix symbolic
* cl test
* this maybe
* gcd of 1 is 1
* real fix for old python
* improve fuzzer
* realize hotspots
* no str check
* minor changes
* make this an assert
* faster and more readable
* nicer self.buffers
* tests for weak op + LAZYCACHE=0
* refactor: print formatting for llama timing, report median and individual runs
* feat: back to mean
* fix: whitespace
* fix: add mean to print
---------
Co-authored-by: Roelof van Dijk <roelof.van.dijk@vitestro.com>
* Dedup params in optimizer
* Passing the same tensor multiple times in the set of learnable params passed to optimizers can result in models completely failing to learn, but no errors are produced. This dedups tensors to avoid the problem.
* Fix types
* Use new variable to satisfy linter
* Use `helpers.dedup` instead of `set()` to dedup params
* Add test for duped params in optimizers
* MaskRCNN weights loading
* backbone maybe works
* backbone works, but resnet body atol 1e-3
* RPN Call, but veryy wrong output
* fixed topk
* RPN maybe works, not sure about nms
* Fix cursed modules
* add back editorconfig
* Full call, wrong output
* Full call works
* fix mask
* use NMS from retinanet
* Removing extra funcs
* refactor
* readable
* Add example to run model
* remove filter
* Fix split, batched inference is worse
* Fix image sizes
* Matching reference
* merge master
* add filter on top detections
* cuda backend fixed
* add model eval and spec
* convert images to rgb
* fix eval
* simplify examples code
* remove extra code
* meshgrid using tinygrad
* removing numpy
* roi align, floor, ceil
* remove numpy from level_mapper
* remove numpy from pooler
* Revert "Merge branch 'master' of github.com:kunwar31/tinygrad into mrcnn-inference"
This reverts commit 4b95a3cb49, reversing
changes made to 98f2b1fa2e.
* roi align gather
* fix master merge
* revert to old floor, ceil as ints present in domain
* use log2 op
* fix indexes
* weird bug with ints and gpu
* weird bug with ints and gpu
* refactors, add env var for gather
* floor with contiguous, where
* refactor topk, sort
* remove staticmethod
* refactor stride
* remove log2 mlop
* realize -> contiguous
* refactor forward
* remove num_classes, stride_in_1x1 from state
* refactor forward
* refactoring
* flake8
* removing numpy in anchor gen, use numpy for gather, nonzero, optimize topk
* keep using tinygrad for smaller gathers
* fix empty tensors
* comms
* move from tensor.py
* resnet test passing
* add coco dataset back
* fix spaces
* add test for log2
* no need to create Tensors
* no need to create Tensors
---------
Co-authored-by: Kunwar Raj Singh <kunwar31@pop-os.localdomain>
* test speed llama
* oops, put it back
* uses the real device codegen
* just do it on the mac
* pp
* is faster?
* Revert "is faster?"
This reverts commit 42db542010.
* disable docker again for less load on CI
* global -> group
* allow None for local_size in custom function
* lil local
* comment on shape
* fix cuda
* smart local cast
* better local heuristic
* fix ptx, and work_dim cleanup
* fix metal
* fix ops test
* fix openpilot jit
* no more optlocal
* might fix metal tests
* try metal now
* see generated metal code
* test free removal. REVERT THIS
* mergable
* Add support for one case of `UOps.CAST` for RDNA3 assembler
* Adds support for casting from `bool` -> `float32`. Seems like a very common operation that is required in many places.
* Fix bool register definition for vector operations
* Use `vcc_lo` instead of `vcc` which seems to be required since it's configured to use wavefront_size=32
* Add vector support for some places that were scalar only in register definition and comparison ops
* Fix some issues in what seems to be defunct `external_test_image.py`
* Some tests still don't pass for other reasons, but it at least runs now and one broken test is now fixed
* Refactor RDNA3 assembler register definition
* Unify multi-registor code between dtypes and combine with single-register allocation since they're all untyped registers at the end of the day
* matrix strategy
* push env to GITHUB_ENV
* use printf instead of echo
* use temp helper function for cross os paths
* use path join
* switched to using temp helper function
* skip test on windows due to memory limit
* small fix
* removed semi
* touchups
* clean up
* seperate tests
* test changes to test_utils on windows
* small refactor
* more cleanups
* undo helpers change
* only skip if in CI and WINDOWS
* Minor improvements + cleanup to `ops_gpu.py`
* Add some previously undocumented environment variables from `ops_gpu.py` to `env_vars.md`
* Update debug print for OpenCL to print the devices that will be used post-filtering with `CL_EXCLUDE`
* Remove a couple unused or superfluous variables and assignments
* Use `fromimport` shorthand to shave off a couple precious LOC
* Couple small whitespace changes to clean things up
* Revert change to ordering of OpenCL devices
* Small refactor for OpenCL context creation
* added SPPF module from yolov8
* added conv_block, bottleneck modules
* cleaned modules
* c2f example
* spf changes
* C2f
* fixed and tested bottleneck
* improved detect class
* tested spf and conv
* checked c2f
* DFL structure
* fixed dfl
* added dist2bbox function
* added dist2bbox function
* added and tested make_anchors function for the head
* keeping functions above
* creating the detection head
* fixing head
* untested blocks a. scale_boxes b. clip_boxes c. xywh2xyxy d. box_iou
* head works
* structure fixx
* added darknet (backbone)
* yolov8 neck, and intialize bias function while detection
* fixed spacing
* yolov8 class, init bias, and fixed c2f
* forward pass almost working
* fixed net structure
* init bias not needed, forward pass working
* load weights boilerplate
* load weights done?
* all variants loading!
* post process: clip_boxes, scale_boxes, xywh2xyxy, and box_iou(untested)
* fix scale_boxes
* box_iou fixed and tested
* created the pre nms function
* fix nms
* fixed load weights, apparently the latest commit broke something, excluding num_batches_tracked
* added letterbox and pre_tranform for pre_process function
* fixed letterbox, pre_transform and added preprocess function
* custom NMS done, integrated prepare_boxes and nms, improved box_iou
* added postprocess function till parsing
* added draw_bounding_boxes_and_save function
* testing full flow
* using fetch for class names
* fixed make_anchors + all tinygrad now
* added command line arguments, weight downloading
* single image for now only
* made draw boxes more efficient
* made NMS functions efficient
* made compute_transform better
* v8 working now, inference is done
* prints objects detected in console now
* fixed image loading (pre processing)
* batch post processing
* created initial tests
* fixes bounding box thickness AND added get_detected_classes_with_frequency function
* cleaning for testing
* two tests
* added url option for image, removed need for specifiying arguments
* tests complete, but lots on things are printed on screen by ultralytics
* remove parse arguments
* fixed weight location
* fixed colours of classes, and black font when high brightness
* minor changes
* TODOs for later
* removed use of torch, using .npz weights
* fixed tests
* one path for fetch
* preprocess now in tinygrad, plus test fix for that
* updated tests
* fix tests
* no class labels needed
* Add files via upload
* Update showcase.md
* Update showcase.md
* added safe tensors as weights, and tests fix for that
* safe tensors test
* using safe_load
* using tinygrad functions now to load weights
* update tests
---------
Co-authored-by: r3sist-uniq <amanmatreja@gmail.com>
Co-authored-by: r3sist <72573738+r3sist-uniq@users.noreply.github.com>
