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225 lines
13 KiB
225 lines
13 KiB
import functools, struct
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from tinygrad.device import Compiled, Allocator, Compiler, BufferSpec
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from tinygrad.renderer.wgsl import WGSLRenderer
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from tinygrad.helpers import round_up, suppress_finalizing
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from tinygrad.runtime.autogen import webgpu
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from typing import List, Any, TypeAlias
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import ctypes
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import os
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WGPUDevPtr: TypeAlias = webgpu.WGPUDevice # type: ignore
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WGPUBufPtr: TypeAlias = webgpu.WGPUBuffer # type: ignore
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backend_types = {v: k for k, v in webgpu.WGPUBackendType__enumvalues.items() }
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instance = webgpu.wgpuCreateInstance(webgpu.WGPUInstanceDescriptor(features = webgpu.WGPUInstanceFeatures(timedWaitAnyEnable = True)))
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def to_c_string(_str:str) -> ctypes.Array: return ctypes.create_string_buffer(_str.encode('utf-8'))
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def from_wgpu_str(string_view:webgpu.struct_WGPUStringView) -> str: return ctypes.string_at(string_view.data, string_view.length).decode("utf-8")
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def to_wgpu_str(_str:str) -> webgpu.struct_WGPUStringView:
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return webgpu.WGPUStringView(data=ctypes.cast(ctypes.pointer(to_c_string(_str)), ctypes.POINTER(ctypes.c_char)), length=len(_str))
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def _wait(future:webgpu.struct_WGPUFuture):
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assert webgpu.wgpuInstanceWaitAny(instance, 1, webgpu.WGPUFutureWaitInfo(future=future), 2**64-1) == webgpu.WGPUWaitStatus_Success, "Future failed"
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def write_buffer(device:WGPUDevPtr, buf:WGPUBufPtr, offset:int, src:memoryview|bytearray|bytes):
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src = bytearray(src)
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webgpu.wgpuQueueWriteBuffer(webgpu.wgpuDeviceGetQueue(device), buf, offset, (ctypes.c_uint8 * len(src)).from_buffer(src), len(src))
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def _run(async_fun, cb_info_type, cb_type, status_enum, res_idx:int|None, msg_idx:int|None, *params):
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result: List[Any] = []
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def cb(*params):
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result[:] = params
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if msg_idx: result[msg_idx] = from_wgpu_str(result[msg_idx])
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cb_info = cb_info_type(nextInChain=None, mode=webgpu.WGPUCallbackMode_WaitAnyOnly, callback=cb_type(cb))
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_wait(async_fun(*params, cb_info))
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if result[0] != 1: raise RuntimeError(f"[{status_enum[result[0]] if status_enum else 'ERROR'}]{result[msg_idx] if msg_idx else ''}")
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return result[res_idx] if res_idx else None
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def copy_buffer_to_buffer(dev:WGPUDevPtr, src:WGPUBufPtr, src_offset:int, dst:WGPUBufPtr, dst_offset:int, size:int):
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encoder = webgpu.wgpuDeviceCreateCommandEncoder(dev, webgpu.WGPUCommandEncoderDescriptor())
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webgpu.wgpuCommandEncoderCopyBufferToBuffer(encoder, src, src_offset, dst, dst_offset, size)
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cb = webgpu.wgpuCommandEncoderFinish(encoder, webgpu.WGPUCommandBufferDescriptor())
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webgpu.wgpuQueueSubmit(webgpu.wgpuDeviceGetQueue(dev), 1, (webgpu.WGPUCommandBuffer*1)(cb))
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webgpu.wgpuCommandBufferRelease(cb)
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webgpu.wgpuCommandEncoderRelease(encoder)
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def read_buffer(dev:WGPUDevPtr, buf:WGPUBufPtr) -> memoryview:
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size = webgpu.wgpuBufferGetSize(buf)
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tmp_buffer = webgpu.wgpuDeviceCreateBuffer(dev, webgpu.WGPUBufferDescriptor(size=size,
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usage=webgpu.WGPUBufferUsage_CopyDst | webgpu.WGPUBufferUsage_MapRead, mappedAtCreation=False))
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copy_buffer_to_buffer(dev, buf, 0, tmp_buffer, 0, size)
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_run(webgpu.wgpuBufferMapAsync2, webgpu.WGPUBufferMapCallbackInfo2, webgpu.WGPUBufferMapCallback2, webgpu.WGPUBufferMapAsyncStatus__enumvalues,
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None, 0, tmp_buffer, webgpu.WGPUMapMode_Read, 0, size)
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void_ptr = ctypes.cast(webgpu.wgpuBufferGetConstMappedRange(tmp_buffer, 0, size), ctypes.c_void_p)
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buf_copy = bytearray((ctypes.c_uint8 * size).from_address(void_ptr.value))
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webgpu.wgpuBufferUnmap(tmp_buffer)
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webgpu.wgpuBufferDestroy(tmp_buffer)
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return memoryview(buf_copy).cast("B")
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def pop_error(device:WGPUDevPtr) -> str:
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return _run(webgpu.wgpuDevicePopErrorScopeF, webgpu.WGPUPopErrorScopeCallbackInfo, webgpu.WGPUPopErrorScopeCallback, None, 2, 2, device)
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def create_uniform(wgpu_device:WGPUDevPtr, val:int|float) -> WGPUBufPtr:
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buf = webgpu.wgpuDeviceCreateBuffer(wgpu_device,
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webgpu.WGPUBufferDescriptor(size=4, usage=webgpu.WGPUBufferUsage_Uniform | webgpu.WGPUBufferUsage_CopyDst))
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write_buffer(wgpu_device, buf, 0, val.to_bytes(4, "little") if isinstance(val, int) else struct.pack('<f', val))
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return buf
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class WebGPUProgram:
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def __init__(self, dev:tuple[WGPUDevPtr, bool], name:str, lib:bytes):
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(self.dev, self.timestamp_supported) = dev
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# Creating shader module
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shader = webgpu.WGPUShaderModuleWGSLDescriptor(code=to_wgpu_str(lib.decode()),
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chain=webgpu.WGPUChainedStruct(sType=webgpu.WGPUSType_ShaderSourceWGSL))
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module = webgpu.WGPUShaderModuleDescriptor()
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module.nextInChain = ctypes.cast(ctypes.pointer(shader), ctypes.POINTER(webgpu.struct_WGPUChainedStruct))
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# Check compiler error
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webgpu.wgpuDevicePushErrorScope(self.dev, webgpu.WGPUErrorFilter_Validation)
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shader_module = webgpu.wgpuDeviceCreateShaderModule(self.dev, module)
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if err := pop_error(self.dev): raise RuntimeError(f"Shader compilation failed: {err}")
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self.name, self.lib, self.prg = name, lib, shader_module
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def __call__(self, *bufs:WGPUBufPtr, global_size:tuple[int,int,int]=(1,1,1), local_size:tuple[int,int,int]=(1,1,1),
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vals:tuple[int, ...]=(), wait=False) -> float|None:
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wait = wait and self.timestamp_supported
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tmp_bufs = [*bufs]
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buf_patch = False
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# WebGPU does not allow using the same buffer for input and output
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for i in range(1, len(bufs)):
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if ctypes.addressof(bufs[i]) == ctypes.addressof(bufs[0]):
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tmp_bufs[0] = webgpu.wgpuDeviceCreateBuffer(self.dev,
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webgpu.WGPUBufferDescriptor(size=webgpu.wgpuBufferGetSize(bufs[0]), usage=webgpu.wgpuBufferGetUsage(bufs[0])))
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buf_patch = True
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# Creating bind group layout
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binding_layouts = [webgpu.WGPUBindGroupLayoutEntry(binding=0, visibility= webgpu.WGPUShaderStage_Compute,
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buffer=webgpu.WGPUBufferBindingLayout(type=webgpu.WGPUBufferBindingType_Uniform))]
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binding_layouts += [webgpu.WGPUBindGroupLayoutEntry(binding=i+1, visibility=webgpu.WGPUShaderStage_Compute,
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buffer=webgpu.WGPUBufferBindingLayout(type=webgpu.WGPUBufferBindingType_Uniform if i >= len(tmp_bufs)
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else webgpu.WGPUBufferBindingType_Storage)) for i in range(len(tmp_bufs)+len(vals))]
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bl_arr_type = webgpu.WGPUBindGroupLayoutEntry * len(binding_layouts)
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webgpu.wgpuDevicePushErrorScope(self.dev, webgpu.WGPUErrorFilter_Validation)
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bind_group_layouts = [webgpu.wgpuDeviceCreateBindGroupLayout(self.dev, webgpu.WGPUBindGroupLayoutDescriptor(
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entryCount=len(binding_layouts), entries=ctypes.cast(bl_arr_type(*binding_layouts), ctypes.POINTER(webgpu.WGPUBindGroupLayoutEntry))))]
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if bg_layout_err := pop_error(self.dev): raise RuntimeError(f"Error creating bind group layout: {bg_layout_err}")
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# Creating pipeline layout
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pipeline_layout_desc = webgpu.WGPUPipelineLayoutDescriptor(bindGroupLayoutCount=len(bind_group_layouts),
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bindGroupLayouts = (webgpu.WGPUBindGroupLayout * len(bind_group_layouts))(*bind_group_layouts))
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webgpu.wgpuDevicePushErrorScope(self.dev, webgpu.WGPUErrorFilter_Validation)
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pipeline_layout = webgpu.wgpuDeviceCreatePipelineLayout(self.dev, pipeline_layout_desc)
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if pipe_err := pop_error(self.dev): raise RuntimeError(f"Error creating pipeline layout: {pipe_err}")
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# Creating bind group
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bindings = [webgpu.WGPUBindGroupEntry(binding=0, buffer=create_uniform(self.dev, float('inf')), offset=0, size=4)]
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bindings += [webgpu.WGPUBindGroupEntry(binding=i+1, buffer=create_uniform(self.dev, x) if i >= len(tmp_bufs) else x, offset=0,
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size=4 if i >= len(tmp_bufs) else webgpu.wgpuBufferGetSize(x)) for i,x in enumerate(tuple(tmp_bufs)+vals)]
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bg_arr_type = webgpu.WGPUBindGroupEntry * len(bindings)
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bind_group_desc = webgpu.WGPUBindGroupDescriptor(layout=bind_group_layouts[0], entryCount=len(bindings), entries=bg_arr_type(*bindings))
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webgpu.wgpuDevicePushErrorScope(self.dev, webgpu.WGPUErrorFilter_Validation)
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bind_group = webgpu.wgpuDeviceCreateBindGroup(self.dev, bind_group_desc)
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if bind_err := pop_error(self.dev): raise RuntimeError(f"Error creating bind group: {bind_err}")
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# Creating compute pipeline
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compute_desc = webgpu.WGPUComputePipelineDescriptor(layout=pipeline_layout,
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compute=webgpu.WGPUComputeState(module=self.prg, entryPoint=to_wgpu_str(self.name)))
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pipeline_result = _run(webgpu.wgpuDeviceCreateComputePipelineAsync2, webgpu.WGPUCreateComputePipelineAsyncCallbackInfo2,
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webgpu.WGPUCreateComputePipelineAsyncCallback2, webgpu.WGPUCreatePipelineAsyncStatus__enumvalues, 1, None, self.dev, compute_desc)
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command_encoder = webgpu.wgpuDeviceCreateCommandEncoder(self.dev, webgpu.WGPUCommandEncoderDescriptor())
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comp_pass_desc = webgpu.WGPUComputePassDescriptor(nextInChain=None)
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if wait:
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query_set = webgpu.wgpuDeviceCreateQuerySet(self.dev, webgpu.WGPUQuerySetDescriptor(type=webgpu.WGPUQueryType_Timestamp, count=2))
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query_buf = webgpu.wgpuDeviceCreateBuffer(self.dev,
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webgpu.WGPUBufferDescriptor(size=16, usage=webgpu.WGPUBufferUsage_QueryResolve | webgpu.WGPUBufferUsage_CopySrc))
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comp_pass_desc.timestampWrites = ctypes.pointer(webgpu.WGPUComputePassTimestampWrites(
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querySet=query_set, beginningOfPassWriteIndex=0, endOfPassWriteIndex=1))
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# Begin compute pass
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compute_pass = webgpu.wgpuCommandEncoderBeginComputePass(command_encoder, comp_pass_desc)
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webgpu.wgpuComputePassEncoderSetPipeline(compute_pass, pipeline_result)
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webgpu.wgpuComputePassEncoderSetBindGroup(compute_pass, 0, bind_group, 0, None)
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webgpu.wgpuComputePassEncoderDispatchWorkgroups(compute_pass, *global_size)
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webgpu.wgpuComputePassEncoderEnd(compute_pass)
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if wait: webgpu.wgpuCommandEncoderResolveQuerySet(command_encoder, query_set, 0, 2, query_buf, 0)
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cmd_buf = webgpu.wgpuCommandEncoderFinish(command_encoder, webgpu.WGPUCommandBufferDescriptor())
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webgpu.wgpuQueueSubmit(webgpu.wgpuDeviceGetQueue(self.dev), 1, (webgpu.WGPUCommandBuffer*1)(cmd_buf))
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if buf_patch:
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copy_buffer_to_buffer(self.dev, tmp_bufs[0], 0, bufs[0], 0, webgpu.wgpuBufferGetSize(bufs[0]))
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webgpu.wgpuBufferDestroy(tmp_bufs[0])
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if wait:
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time = ((timestamps:=read_buffer(self.dev, query_buf).cast("Q").tolist())[1] - timestamps[0]) / 1e9
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webgpu.wgpuBufferDestroy(query_buf)
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webgpu.wgpuQuerySetDestroy(query_set)
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return time
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return None
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class WebGpuAllocator(Allocator['WGPUDevPtr']):
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def _alloc(self, size:int, options:BufferSpec) -> WGPUBufPtr:
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# WebGPU buffers have to be 4-byte aligned
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return webgpu.wgpuDeviceCreateBuffer(self.dev, webgpu.WGPUBufferDescriptor(size=round_up(size, 4),
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usage=webgpu.WGPUBufferUsage_Storage | webgpu.WGPUBufferUsage_CopyDst | webgpu.WGPUBufferUsage_CopySrc))
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def _copyin(self, dest:WGPUBufPtr, src:memoryview):
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if src.nbytes % 4:
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padded_src = bytearray(round_up(src.nbytes, 4))
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padded_src[:src.nbytes] = src
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write_buffer(self.dev, dest, 0, padded_src if src.nbytes % 4 else src)
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def _copyout(self, dest:memoryview, src:WGPUBufPtr):
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buffer_data = read_buffer(self.dev, src)
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dest[:] = buffer_data[:dest.nbytes] if webgpu.wgpuBufferGetSize(src) > dest.nbytes else buffer_data
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@suppress_finalizing
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def _free(self, opaque:WGPUBufPtr, options:BufferSpec): webgpu.wgpuBufferDestroy(opaque)
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class WebGpuDevice(Compiled):
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def __init__(self, device:str):
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# Requesting an adapter
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adapter_res = _run(webgpu.wgpuInstanceRequestAdapterF, webgpu.WGPURequestAdapterCallbackInfo, webgpu.WGPURequestAdapterCallback,
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webgpu.WGPURequestAdapterStatus__enumvalues, 1, 2, instance,
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webgpu.WGPURequestAdapterOptions(powerPreference=webgpu.WGPUPowerPreference_HighPerformance,
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backendType=backend_types.get(os.getenv("WEBGPU_BACKEND", ""), 0)))
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# Get supported features
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supported_features = webgpu.WGPUSupportedFeatures()
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webgpu.wgpuAdapterGetFeatures(adapter_res, supported_features)
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supported = [supported_features.features[i] for i in range(supported_features.featureCount)]
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features = [feat for feat in [webgpu.WGPUFeatureName_TimestampQuery, webgpu.WGPUFeatureName_ShaderF16] if feat in supported]
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dev_desc = webgpu.WGPUDeviceDescriptor(requiredFeatureCount=len(features),requiredFeatures=(webgpu.WGPUFeatureName * len(features))(*features))
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# Limits
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supported_limits = webgpu.WGPUSupportedLimits()
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webgpu.wgpuAdapterGetLimits(adapter_res, ctypes.cast(ctypes.pointer(supported_limits),ctypes.POINTER(webgpu.struct_WGPUSupportedLimits)))
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limits = webgpu.WGPURequiredLimits(limits=supported_limits.limits)
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dev_desc.requiredLimits = ctypes.cast(ctypes.pointer(limits),ctypes.POINTER(webgpu.struct_WGPURequiredLimits))
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# Requesting a device
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device_res = _run(webgpu.wgpuAdapterRequestDeviceF, webgpu.WGPURequestDeviceCallbackInfo, webgpu.WGPURequestDeviceCallback,
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webgpu.WGPURequestDeviceStatus__enumvalues, 1, 2, adapter_res, dev_desc)
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super().__init__(device, WebGpuAllocator(device_res), [(WGSLRenderer, Compiler)],
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functools.partial(WebGPUProgram, (device_res, webgpu.WGPUFeatureName_TimestampQuery in supported)))
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def synchronize(self):
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_run(webgpu.wgpuQueueOnSubmittedWorkDone2, webgpu.WGPUQueueWorkDoneCallbackInfo2, webgpu.WGPUQueueWorkDoneCallback2,
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webgpu.WGPUQueueWorkDoneStatus__enumvalues, None, None, webgpu.wgpuDeviceGetQueue(self.runtime.args[0][0]))
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