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Fix for issue #213 #289

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merged 3 commits into from
Nov 19, 2024
Merged

Fix for issue #213 #289

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f62d372
set quantum device batch size
ankhoa1212 Nov 18, 2024
d054208
import CliffordQuantizer
ankhoa1212 Nov 18, 2024
3f76570
make import lazy
ankhoa1212 Nov 19, 2024
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1 change: 1 addition & 0 deletions examples/clifford_qnn/mnist_clifford_qnn.py
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Expand Up @@ -60,6 +60,7 @@ def forward(self, x, use_qiskit=False):
self.q_device, self.encoder, self.q_layer, self.measure, x
)
else:
self.q_device = tq.QuantumDevice(n_wires=self.n_wires, bsz=bsz)
self.encoder(self.q_device, x)
self.q_layer(self.q_device)
x = self.measure(self.q_device)
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1 change: 1 addition & 0 deletions torchquantum/operator/op_types.py
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Expand Up @@ -7,6 +7,7 @@
from ..macro import C_DTYPE, F_DTYPE
from typing import Iterable, Union, List
from enum import IntEnum
from torchquantum.util.quantization.clifford_quantization import CliffordQuantizer
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Is this import necessary here?

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Oh, wait, I missed your initial comment.

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Can you instead import this lazily, so in the conditional branch where we actually call CliffordQuantizer? Afterward, will merge in!


__all__ = [
"Operator",
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