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Fix root cause of bug reported in PR #1412 #1417

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merged 2 commits into from
Aug 14, 2024
Merged

Fix root cause of bug reported in PR #1412 #1417

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6994580
fix `MeasurementOurcomes`
renatomello Aug 8, 2024
ad3eb17
Merge branch 'master' into fix-complex-samples
renatomello Aug 14, 2024
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2 changes: 0 additions & 2 deletions src/qibo/backends/numpy.py
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Expand Up @@ -645,9 +645,7 @@ def aggregate_shots(self, shots):
return self.cast(shots, dtype=shots[0].dtype)

def samples_to_binary(self, samples, nqubits):
### This is faster just staying @ NumPy.
qrange = np.arange(nqubits - 1, -1, -1, dtype=np.int32)
samples = self.to_numpy(samples)
return np.mod(np.right_shift(samples[:, None], qrange), 2)
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Aren't all the other operations in here still NumPy? Or is Torch automatically converting NumPy calls?

I expected self.np. usage, but instead there is np. everywhere...

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@renatomello renatomello Aug 8, 2024 •
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I tried self.np and it creates other issues because torch.arange and torch.right_shift work slightly differently

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But is np.right_shift() able to work on Torch tensors? (i.e. taking Torch tensors as input and returning them as output)

I see it could be vaguely possible, but it's still good to know, because I wouldn't have been confident to say it's actually able.

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In [6]: import numpy as np
   ...: import torch
   ...: 
   ...: x = torch.Tensor(torch.arange(10))
   ...: qrange = np.arange(10 - 1, -1, -1, dtype=np.int32)
   ...: type(np.right_shift(x[:, None], qrange))
Out[6]: torch.Tensor

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Nice, thanks :)

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@alecandido alecandido Aug 8, 2024 •
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It seems that by now this starts being reliable

https://numpy.org/doc/stable/user/basics.interoperability.html#operating-on-foreign-objects-without-converting
https://numpy.org/neps/nep-0018-array-function-protocol.html#nep18

(ok, most likely since a while, but it is for sure framework-dependent, I should take the time of assessing which ones are fully supporting it)


def samples_to_decimal(self, samples, nqubits):
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11 changes: 6 additions & 5 deletions src/qibo/measurements.py
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Expand Up @@ -167,11 +167,12 @@ def samples(self, binary=True, registers=False):
# calculate samples for the whole circuit so that
# individual register samples are registered here
self.circuit.final_state.samples()

if binary:
return self._samples
else:
qubits = self.measurement_gate.target_qubits
return self.backend.samples_to_decimal(self._samples, len(qubits))

qubits = self.measurement_gate.target_qubits
return self.backend.samples_to_decimal(self._samples, len(qubits))

def frequencies(self, binary=True, registers=False):
"""Returns the frequencies of measured samples.
Expand All @@ -198,8 +199,8 @@ def frequencies(self, binary=True, registers=False):
if binary:
qubits = self.measurement_gate.target_qubits
return frequencies_to_binary(self._frequencies, len(qubits))
else:
return self._frequencies

return self._frequencies

def apply_bitflips(self, p0, p1=None): # pragma: no cover
return apply_bitflips(self, p0, p1)
7 changes: 1 addition & 6 deletions src/qibo/result.py
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Expand Up @@ -325,12 +325,7 @@ def samples(self, binary: bool = True, registers: bool = False):
if self._samples is None:
if self.measurements[0].result.has_samples():
self._samples = self.backend.np.concatenate(
[
self.backend.cast(
gate.result.samples(), dtype=self.backend.np.int32
)
for gate in self.measurements
],
[gate.result.samples() for gate in self.measurements],
axis=1,
)
else:
Expand Down