helper functions

hopfield4py.hamming(A: tensorflow.python.framework.ops.Tensor, B: tensorflow.python.framework.ops.Tensor) → tensorflow.python.framework.ops.Tensor

Hamming distance sum(abs((A-B)))/lenght(A)

A and be must have the same shape

Parameters

• A – first tensor

• B – second tensor

hopfield4py.get_prediction(sample: tensorflow.python.framework.ops.Tensor, data_tensor: tensorflow.python.framework.ops.Tensor, model: hopfield4py.hopfield.Hopfield) → tensorflow.python.framework.ops.Tensor

Get the nearest memory

Parameters

• sample – sample to reconstruct

• data_tensor – tensor with memories

• model – model used to infer

Returns

argmin of the element of data_tensor nearest to sample

hopfield4py.get_predicted_labels(classes: list, samples: tensorflow.python.framework.ops.Tensor, data_tensor: tensorflow.python.framework.ops.Tensor, model: hopfield4py.hopfield.Hopfield) → list

Get the classes predicted for each sample

Parameters

• classes – list of classes names with shape (nclasses,)

• samples – samples to reconstruct with shape (nsamples, nspins)

• data_tensor – tensor with memories (nclasses, nspins)

Returns

tensor with list of classes

hopfield4py.get_all_prediction(samples: tensorflow.python.framework.ops.Tensor, data_tensor: tensorflow.python.framework.ops.Tensor, model: hopfield4py.hopfield.Hopfield) → tensorflow.python.framework.ops.Tensor

Get the nearest memory

Parameters

• samples – samples to reconstruct

• data_tensor – tensor with memories

• model – model used to infer

Returns

tensor with list of argmin of the element of data_tensor nearest to each sample