issue on unashable csr matrix nb "Introduction_to_RC"

[AlArths]

Hi,
we are using the "Introduction_to_RC". However we encounter this issue :
"TypeError Traceback (most recent call last)
in
6 proba=density, seed=seed)
7
----> 8 reservoir = ESN(leak_rate, W, Win, ridge=regularization)

~\anaconda3\lib\site-packages\reservoirpy\nodes\esn.py in init(self, reservoir_method, learning_method, reservoir, readout, feedback, Win_bias, Wout_bias, workers, backend, name, **kwargs)
107
108 if readout is None:
--> 109 if learning_method not in _LEARNING_METHODS:
110 raise ValueError(msg.format(learning_method, "readout",
111 list(_LEARNING_METHODS.keys())))

TypeError: unhashable type: 'csr_matrix' "

For the cell :
"Win = mat_gen.generate_input_weights(units, 1, input_scaling=input_scaling,
proba=input_connectivity, input_bias=True,
seed=seed)

W = mat_gen.generate_internal_weights(units, sr=spectral_radius,
proba=density, seed=seed)

reservoir = ESN(leak_rate, W, Win, ridge=regularization)"

We are using Python 3.8.8.

HELP

Regards

[nTrouvain]

Hello, thank you very much for your report ! Does the error still happens if you use keywords arguments ?
Also, what version of ReservoirPy are you using ?

reservoir = ESN(lr=leak_rate, W=W, Win=Win, ridge=regularization)

[c006]

That worked for me.

Windows 10
JupyterLab : Version 3.2.1
ReservoirPy : version 0.3.0

File
reservoirpy/examples/Introduction to Reservoir Computing/Introduction_to_RC.ipynb

def reset_esn():
    Win = mat_gen.generate_input_weights(
        units,
        1,
        input_scaling=input_scaling,
        proba=input_connectivity,
        input_bias=True,
        seed=seed,
    )

    W = mat_gen.generate_internal_weights(
        units, sr=spectral_radius, proba=density, seed=seed
    )

    reservoir = ESN(lr=leak_rate, W=W, Win=Win, ridge=regularization)
    # reservoir = ESN(leak_rate, W, Win, ridge=regularization)

    return reservoir