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Avoid DivisionByZero error when TensorNetwork simplifies to a scalar #6586

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Merged
merged 2 commits into from
May 7, 2024
Merged

Avoid DivisionByZero error when TensorNetwork simplifies to a scalar #6586

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d057122
Avoid DivisionByZero error when TensorNetwork simplifies to a scalar
pavoljuhas May 6, 2024
016b758
Add TODO note for reverting temporary workaround
pavoljuhas May 7, 2024
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10 changes: 8 additions & 2 deletions cirq-core/cirq/contrib/quimb/state_vector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -170,8 +170,14 @@ def tensor_expectation_value(
)
else:
tn.rank_simplify(inplace=True)
path_info = tn.contract(get='path-info')
ram_gb = path_info.largest_intermediate * 128 / 8 / 1024 / 1024 / 1024
# Skip path-info evaluation when TensorNetwork consists of scalar Tensors.
# Avoid bug in quimb-1.8.0.
# Ref: https://github.com/jcmgray/quimb/issues/231
if tn.ind_map:
path_info = tn.contract(get='path-info')
ram_gb = path_info.largest_intermediate * 128 / 8 / 1024 / 1024 / 1024
else:
ram_gb = 0
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should we raise an error or log a warning?

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I don't think it is needed. The error happens for a trivial TensorNetwork([Tensor()]) for which the memory requirements will be tiny.
The bug was BTW already fixed upstream, but I think we should still merge this so we support the current quimb-1.8.

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maybe add a TODO to remove this when we upgrade quimb ?

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Sure, done.

if ram_gb > max_ram_gb:
raise MemoryError(f"We estimate that this contraction will take too much RAM! {ram_gb} GB")
e_val = tn.contract(inplace=True)
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