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2c363b5f0b* cpu tests pass * torch works * works * metal works * fix ops_disk * metal jit works * fix openpilot * llvm and clang work * fix webgpu * docs are rly broken * LRU works on metal * delete comment * revert name to ._buf. LRU only on Compiled * changes * allocator * allocator, getting closer * lru alloc * LRUAllocator * all pass * metal * cuda * test examples * linearizer * test fixes * fix custom + clean realize * fix hip * skip tests * fix tests * fix size=0 * fix MOCKHIP * fix thneed * copy better * simple * old style metal copy * fix thneed * np reshape * give cuda a device
40 lines
2.5 KiB
Python
40 lines
2.5 KiB
Python
import functools
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from wgpu.utils.device import get_default_device
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from tinygrad.helpers import dtypes, DType
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from tinygrad.device import Compiled, Allocator
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from tinygrad.codegen.kernel import LinearizerOptions
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from tinygrad.renderer.cstyle import uops_to_cstyle
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from tinygrad.renderer.wgsl import WGSLLanguage
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import wgpu
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wgpu_device = get_default_device()
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class WebGPUProgram:
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def __init__(self, name: str, prg: str, bufs:int=0, vars:int=0): self.name,self.prg = name,wgpu_device.create_shader_module(code=prg)
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def __call__(self, *bufs, global_size, local_size, wait=False):
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assert len(bufs) <= 8, "WEBGPU only supports 8 buffers"
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binding_layouts = [{"binding": i, "visibility": wgpu.ShaderStage.COMPUTE, "buffer": {"type": wgpu.BufferBindingType.storage}} for i in range(len(bufs))]
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bindings = [{"binding": i, "resource": {"buffer": x, "offset": 0, "size": x.size}} for i, x in enumerate(bufs)]
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bind_group_layout = wgpu_device.create_bind_group_layout(entries=binding_layouts)
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pipeline_layout = wgpu_device.create_pipeline_layout(bind_group_layouts=[bind_group_layout])
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bind_group = wgpu_device.create_bind_group(layout=bind_group_layout, entries=bindings)
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compute_pipeline = wgpu_device.create_compute_pipeline(layout=pipeline_layout,compute={"module": self.prg, "entry_point": self.name},)
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command_encoder = wgpu_device.create_command_encoder()
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compute_pass = command_encoder.begin_compute_pass()
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compute_pass.set_pipeline(compute_pipeline)
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compute_pass.set_bind_group(0, bind_group, [], 0, 999999) # last 2 not used
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compute_pass.dispatch_workgroups(*global_size) # x y z
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compute_pass.end()
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wgpu_device.queue.submit([command_encoder.finish()])
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class WebGpuAllocator(Allocator):
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def _alloc(self, size: int, dtype: DType):
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assert dtype not in [dtypes.int8,dtypes.uint8,dtypes.int64,dtypes.uint64,dtypes.double], f"dtype {dtype} not supported on WEBGPU"
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return wgpu_device.create_buffer(size=size*dtype.itemsize, usage=wgpu.BufferUsage.STORAGE | wgpu.BufferUsage.COPY_DST | wgpu.BufferUsage.COPY_SRC)
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def copyin(self, dest, src: memoryview): wgpu_device.queue.write_buffer(dest, 0, src)
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def copyout(self, dest, src: memoryview): dest[:] = wgpu_device.queue.read_buffer(src, 0) # TODO: remove this copy
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class WebGpuDevice(Compiled):
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def __init__(self, device:str):
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super().__init__(WebGpuAllocator(), LinearizerOptions(device="WEBGPU", supports_float4=False, local_max=[256, 256, 64], global_max=[65535, 65535, 65535]),
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functools.partial(uops_to_cstyle, WGSLLanguage()), lambda x: x, WebGPUProgram)
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