efee1712aa
* fix.. speed_limit error... * draw tpms settings. * fix.. traffic light stopping only.. * fix.. waze cam * fix.. waze... * add setting (Enable comma connect ) * auto detect LFA2 * fix.. cruisespeed1 * vff2 driving model. * fix.. * agnos 12.3 * fix.. * ff * ff * test * ff * fix.. drawTurnInfo.. * Update drive_helpers.py * fix.. support eng voice eng sounds fix settings... english fix.. mph.. fix.. roadlimit speed bug.. * new vff model.. 250608 * fix soundd.. * fix safe exit speed.. * fix.. sounds. * fix.. radar timeStep.. * KerryGold model * Update drive_helpers.py * fix.. model. * fix.. * fix.. * Revert "fix.." This reverts commit b09ec459afb855c533d47fd7e8a1a6b1a09466e7. * Revert "fix.." This reverts commit 290bec6b83a4554ca232d531a911edccf94a2156. * fix esim * add more acc table. 10kph * kg update.. * fix cruisebutton mode3 * test atc..cond. * fix.. canfd * fix.. angle control limit
73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
import gc
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from tinygrad import Tensor, UOp, Device
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from tinygrad.shape.shapetracker import views_to_indexed_uops
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from tinygrad.engine.realize import method_cache, get_kernel
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def uops_allocated(): return sum([isinstance(x, UOp) for x in gc.get_objects()])
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def print_uops():
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for x in gc.get_objects():
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if isinstance(x, UOp): print(x)
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def start(): pass
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def single_tensor(): Tensor([2])
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def two_plus_two(): Tensor([2])+Tensor([2])
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def two_plus_two_schedule(): (Tensor([2])+Tensor([2])).schedule()
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def two_plus_two_kernel():
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si = (Tensor([2])+Tensor([2])).schedule()[-1]
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get_kernel(Device.default.renderer, si.ast)
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def two_plus_two_linearize():
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si = (Tensor([2])+Tensor([2])).schedule()[-1]
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k = get_kernel(Device.default.renderer, si.ast)
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k.get_optimized_ast()
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#k.linearize()
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def two_plus_two_realize(): (Tensor([2])+Tensor([2])).realize()
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def two_plus_two_item(): (Tensor([2])+Tensor([2])).item()
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def gradient_test():
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x = Tensor.eye(3, requires_grad=True)
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y = Tensor([[2.0,0,-2.0]], requires_grad=True)
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z = y.matmul(x).sum()
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z.backward()
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def realized_eye():
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Tensor.eye(3, requires_grad=True).realize()
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def realized_list():
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Tensor([[2.0,0,-2.0]], requires_grad=True).realize()
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def kernel_matmul():
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x = Tensor.eye(3, requires_grad=True)
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y = Tensor([[2.0,0,-2.0]], requires_grad=True)
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z = y.matmul(x)
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si = z.schedule()[-1]
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get_kernel(Device.default.renderer, si.ast)
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def realized_matmul():
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x = Tensor.eye(3, requires_grad=True)
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y = Tensor([[2.0,0,-2.0]], requires_grad=True)
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z = y.matmul(x)
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Tensor.realize(z)
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def realized_gradient():
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x = Tensor.eye(3, requires_grad=True)
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y = Tensor([[2.0,0,-2.0]], requires_grad=True)
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z = y.matmul(x).sum()
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z.backward()
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Tensor.realize(x, y, z, x.grad, y.grad)
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tests = [start, single_tensor, two_plus_two, two_plus_two_schedule, two_plus_two_kernel,
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two_plus_two_linearize, two_plus_two_realize, two_plus_two_item, gradient_test,
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realized_eye, realized_list, kernel_matmul, realized_matmul, realized_gradient]
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if __name__ == "__main__":
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gc.disable()
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start_uops = uops_allocated()
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# there's a few consts created as default values
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print_uops()
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for t in tests:
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t()
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# these caches will keep uops alive
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method_cache.clear()
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views_to_indexed_uops.cache_clear()
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new_uops = uops_allocated()
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gc.collect()
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new_uops_gc = uops_allocated()
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print(f"{t.__name__:30s}: {new_uops:3d} -> {new_uops_gc:3d}")
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assert new_uops == start_uops
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#print_uops()
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