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webgl backend in extra (#3041)

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* WebGL WIP

* 84% of ops passing test

* tests passing 100%

* Cleanup, refactor

* Shave off some lines

* Work on dtypes

* TestOps at 100% again

* Efficient net shaders compile in browser webgl2

* Compile all efficientnet shaders in browser

* Create empty textures for tensor buffers

* Run program. Up next weight loading

* Exported WebGL model working

* Add tests, refactor

* Explicit cast alu for GLSL

* Fix CI tests

* WebGL efficientnet demo

* Compile and run yolov8 in browser

* Fix imports

* Simplify yolo compile

* Fix bool*bool and cast cmplt to float

* More tests

* Do std tests pass on CI?

* Skip std tests on CI

* Remove explicit_cast_alu hack, and solve it in code_for_op

* Move to new dtype-less alloc api

* Remove local size hack: optimize local_size only if device has local

* Remove glsl.py, and move content to cstyle

* dont_use_locals in opts

* Fix dtype tests

* type_map in CStyleLanguage

* Make core changes smaller, cleaner, refactor export_model and demo

* Skip pad_slice

* Simplify: render_const, render_conditional

* solve bool alu for other binops, cleaner ops_webgl

* Fix noopt hack

* Remove some skipIfs

* WebGL image hack

* type_names is a better name

* global_max

* Fix dtype import

* Fix type_names -> type_map

* Fix lint

* Remove webgpu, back to 5k lines (#3040)

* remove webgpu

* max 5000 lines

* revert those to master

* retain that cstyle

---------

Co-authored-by: Ahmed Harmouche <ahmedharmouche92@gmail.com>
This commit is contained in:
George Hotz
2024-01-08 09:29:13 -08:00
committed by GitHub
parent 8cbcd1b342
commit c5a941d466
9 changed files with 596 additions and 15 deletions
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4
test/test_dtype.py
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@@ -13,7 +13,7 @@ core_dtypes = list(DTYPES_DICT.values())
floats = [dt for dt in core_dtypes if dtypes.is_float(dt)]
def is_dtype_supported(dtype: DType, device: str = Device.DEFAULT):
if dtype == dtypes.bfloat16: return False # numpy doesn't support bf16, tested separately in TestBFloat16DType
if device == "WEBGPU": return dtype in [dtypes.float, dtypes.int32, dtypes.uint32]
if device in ["WEBGPU", "WEBGL"]: return dtype in [dtypes.float, dtypes.int32, dtypes.uint32]
if device == "TORCH": return dtype not in [dtypes.uint16, dtypes.uint32, dtypes.uint64]
# for CI GPU, cl_khr_fp16 isn't supported
# for CI LLVM, it segfaults because it can't link to the casting function
@@ -90,6 +90,7 @@ class TestDType(unittest.TestCase):
get_available_cast_dtypes(self.DTYPE)
))
def test_bitcast(self):
if Device.DEFAULT == "WEBGL": raise unittest.SkipTest("no bitcast in WebGL GLSL")
if self.DTYPE == dtypes.bool: raise unittest.SkipTest("no bools in bitcast")
list(map(
lambda dtype:
@@ -160,6 +161,7 @@ class TestUint8Dtype(TestDType):
def test_uint8_to_int8_overflow(self):
_test_op(lambda: Tensor([255, 254, 253, 252], dtype=dtypes.uint8).cast(dtypes.int8), dtypes.int8, [-1, -2, -3, -4])
@unittest.skipIf(Device.DEFAULT == "WEBGL", "No bitcast on WebGL")
class TestBitCast(unittest.TestCase):
def test_shape_change_bitcast(self):
with self.assertRaises(AssertionError):