Got error while trying to train with 32x32 MNIST
python main.py --data mnist_32x32
Traceback (most recent call last): File "/mnt/working/quantum-diffusion/src/main.py", line 175, in <module> train() File "/mnt/workinge/quantum-diffusion/src/main.py", line 103, in train batch_loss, _ = diff(x=x, y=y, T=args.tau, verbose=True) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/mnt/working/quantum-diffusion/src/models.py", line 63, in forward return self.run_training_step_noise(x, **kwargs) File "/mnt/working/quantum-diffusion/src/models.py", line 136, in run_training_step_noise predicted_noise = self.net.forward(x=batches_noisy) File "/mnt/working/quantum-diffusion/src/nn/qdense.py", line 53, in forward x = self.qnode(x) File "/usr/local/lib/python3.10/dist-packages/pennylane/qnode.py", line 842, in __call__ self.construct(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/pennylane/qnode.py", line 751, in construct self._tape = make_qscript(self.func)(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pennylane/tape/qscript.py", line 1371, in wrapper result = fn(*args, **kwargs) File "/mnt/working/quantum-diffusion/src/nn/qdense.py", line 36, in _circuit qml.AmplitudeEmbedding( File "/usr/local/lib/python3.10/dist-packages/pennylane/templates/embeddings/amplitude.py", line 128, in __init__ features = self._preprocess(features, wires, pad_with, normalize) File "/usr/local/lib/python3.10/dist-packages/pennylane/templates/embeddings/amplitude.py", line 205, in _preprocess raise ValueError( ValueError: Features must be of length 64 or smaller to be padded; got length 1024.
Seems like dimension errs
Got error while trying to train with 32x32 MNIST
python main.py --data mnist_32x32
Traceback (most recent call last): File "/mnt/working/quantum-diffusion/src/main.py", line 175, in <module> train() File "/mnt/workinge/quantum-diffusion/src/main.py", line 103, in train batch_loss, _ = diff(x=x, y=y, T=args.tau, verbose=True) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/mnt/working/quantum-diffusion/src/models.py", line 63, in forward return self.run_training_step_noise(x, **kwargs) File "/mnt/working/quantum-diffusion/src/models.py", line 136, in run_training_step_noise predicted_noise = self.net.forward(x=batches_noisy) File "/mnt/working/quantum-diffusion/src/nn/qdense.py", line 53, in forward x = self.qnode(x) File "/usr/local/lib/python3.10/dist-packages/pennylane/qnode.py", line 842, in __call__ self.construct(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/pennylane/qnode.py", line 751, in construct self._tape = make_qscript(self.func)(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pennylane/tape/qscript.py", line 1371, in wrapper result = fn(*args, **kwargs) File "/mnt/working/quantum-diffusion/src/nn/qdense.py", line 36, in _circuit qml.AmplitudeEmbedding( File "/usr/local/lib/python3.10/dist-packages/pennylane/templates/embeddings/amplitude.py", line 128, in __init__ features = self._preprocess(features, wires, pad_with, normalize) File "/usr/local/lib/python3.10/dist-packages/pennylane/templates/embeddings/amplitude.py", line 205, in _preprocess raise ValueError( ValueError: Features must be of length 64 or smaller to be padded; got length 1024.Seems like dimension errs