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July 12, 2024 21:07
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(torch310) root@b7b12c30e894:/pytorch/xla# cat test_7665.py | |
import torch | |
import torch_xla | |
import torch_xla.experimental.fori_loop | |
from torch._higher_order_ops.while_loop import while_loop | |
import torch_xla.core.xla_model as xm | |
class TPUComputation: | |
def __init__(self): | |
self.device = xm.xla_device() | |
self.init_x = torch.tensor([1], device=self.device) | |
self.init_y = torch.tensor([1], device=self.device) | |
self.init_z = torch.tensor([1], device=self.device) | |
self.iteri = torch.tensor(10, device=self.device) | |
self.quantity = torch.tensor(2, device=self.device) | |
def cond_fn(self, iteri, x, y, z, q=None): | |
return iteri > 0 | |
def body_fn(self, iteri, x, y, z, q=None): | |
return iteri - 1, x.clone(), y.add(1), z + self.quantity # Problemmatic Line | |
def compute(self): | |
result = while_loop( | |
self.cond_fn, | |
self.body_fn, | |
(self.iteri, self.init_x, self.init_y, self.init_z), | |
) | |
return result | |
if __name__ == "__main__": | |
computation = TPUComputation() | |
result = computation.compute() | |
print(result) | |
(torch310) root@b7b12c30e894:/pytorch/xla# PJRT_DEVICE=TPU python test_7665.py | |
body computation: !!!!!!!!! | |
HloModule PyLoweringContext.20.28, entry_computation_layout={((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}))->(s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0})} | |
%PyLoweringContext.7 (p0.10: s64[], p1.13: s64[], p2.14: s64[1], p3.17: s64[1], p4.22: s64[1]) -> (s64[], s64[], s64[1], s64[1], s64[1]) { | |
%p0.10 = s64[] parameter(0) | |
%constant.9 = s64[] constant(1) | |
%constant.8 = s64[] constant(1) | |
%multiply.11 = s64[] multiply(s64[] %constant.9, s64[] %constant.8) | |
%subtract.12 = s64[] subtract(s64[] %p0.10, s64[] %multiply.11) | |
%p1.13 = s64[] parameter(1) | |
%p2.14 = s64[1]{0} parameter(2) | |
%p3.17 = s64[1]{0} parameter(3) | |
%constant.16 = s64[] constant(1) | |
%constant.15 = s64[] constant(1) | |
%multiply.18 = s64[] multiply(s64[] %constant.16, s64[] %constant.15) | |
%broadcast.19 = s64[1]{0} broadcast(s64[] %multiply.18), dimensions={} | |
%add.20 = s64[1]{0} add(s64[1]{0} %p3.17, s64[1]{0} %broadcast.19) | |
%p4.22 = s64[1]{0} parameter(4) | |
%constant.21 = s64[] constant(1) | |
%multiply.23 = s64[] multiply(s64[] %p1.13, s64[] %constant.21) | |
%broadcast.24 = s64[1]{0} broadcast(s64[] %multiply.23), dimensions={} | |
%add.25 = s64[1]{0} add(s64[1]{0} %p4.22, s64[1]{0} %broadcast.24) | |
ROOT %tuple.26 = (s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) tuple(s64[] %subtract.12, s64[] %p1.13, s64[1]{0} %p2.14, s64[1]{0} %add.20, s64[1]{0} %add.25) | |
} | |
ENTRY %PyLoweringContext.20.28 (in.1: (s64[], s64[], s64[1], s64[1], s64[1])) -> (s64[], s64[], s64[1], s64[1], s64[1]) { | |
%in.1 = (s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) parameter(0) | |
%get-tuple-element.2 = s64[] get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=0 | |
%get-tuple-element.3 = s64[] get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=1 | |
%get-tuple-element.4 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=2 | |
%get-tuple-element.5 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=3 | |
%get-tuple-element.6 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=4 | |
ROOT %call.27 = (s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) call(s64[] %get-tuple-element.2, s64[] %get-tuple-element.3, s64[1]{0} %get-tuple-element.4, s64[1]{0} %get-tuple-element.5, s64[1]{0} %get-tuple-element.6), to_apply=%PyLoweringContext.7 | |
} | |
cond computation: !!!!!!!!! | |
HloModule PyLoweringContext.8.16, entry_computation_layout={((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}))->pred[]} | |
%PyLoweringContext.7 (p0.9: s64[], UnusedArgumentsPlaceholder.11: s64[], UnusedArgumentsPlaceholder.12: s64[1], UnusedArgumentsPlaceholder.13: s64[1], UnusedArgumentsPlaceholder.14: s64[1]) -> pred[] { | |
%p0.9 = s64[] parameter(0) | |
%constant.8 = s64[] constant(0) | |
ROOT %compare.10 = pred[] compare(s64[] %p0.9, s64[] %constant.8), direction=GT | |
%UnusedArgumentsPlaceholder.11 = s64[] parameter(1) | |
%UnusedArgumentsPlaceholder.12 = s64[1]{0} parameter(2) | |
%UnusedArgumentsPlaceholder.13 = s64[1]{0} parameter(3) | |
%UnusedArgumentsPlaceholder.14 = s64[1]{0} parameter(4) | |
} | |
ENTRY %PyLoweringContext.8.16 (in.1: (s64[], s64[], s64[1], s64[1], s64[1])) -> pred[] { | |
%in.1 = (s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) parameter(0) | |
%get-tuple-element.2 = s64[] get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=0 | |
%get-tuple-element.3 = s64[] get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=1 | |
%get-tuple-element.4 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=2 | |
%get-tuple-element.5 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=3 | |
%get-tuple-element.6 = s64[1]{0} get-tuple-element((s64[], s64[], s64[1]{0}, s64[1]{0}, s64[1]{0}) %in.1), index=4 | |
ROOT %call.15 = pred[] call(s64[] %get-tuple-element.2, s64[] %get-tuple-element.3, s64[1]{0} %get-tuple-element.4, s64[1]{0} %get-tuple-element.5, s64[1]{0} %get-tuple-element.6), to_apply=%PyLoweringContext.7 | |
} | |
(FunctionalTensor(lvl=0, value=\ | |
tensor(0, device='xla:0')), FunctionalTensor(lvl=0, value=\ | |
tensor([1], device='xla:0')), FunctionalTensor(lvl=0, value=\ | |
tensor([11], device='xla:0')), FunctionalTensor(lvl=0, value=\ | |
tensor([21], device='xla:0'))) | |
(torch310) root@b7b12c30e894:/pytorch/xla# |
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