From 5791dc7595cce39be384a052c60106e9eb8d9ccf Mon Sep 17 00:00:00 2001 From: Simon Caby Date: Tue, 4 May 2021 14:14:48 +0200 Subject: [PATCH 1/3] for credential test --- examples/mnist/reservoir.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/mnist/reservoir.py b/examples/mnist/reservoir.py index 4c5ef80b8..76dd33fa0 100644 --- a/examples/mnist/reservoir.py +++ b/examples/mnist/reservoir.py @@ -185,7 +185,7 @@ def forward(self, x): optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) # Training the Model -print("\n Training the read out") +print("\n Training the read out ") pbar = tqdm(enumerate(range(n_epochs))) for epoch, _ in pbar: avg_loss = 0 From 7cf2d9a34feddcdeb6e846183d231de41fc9aa27 Mon Sep 17 00:00:00 2001 From: Simon Caby Date: Tue, 4 May 2021 14:24:35 +0200 Subject: [PATCH 2/3] fro ssh test --- examples/mnist/reservoir.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/mnist/reservoir.py b/examples/mnist/reservoir.py index 76dd33fa0..4096b94a9 100644 --- a/examples/mnist/reservoir.py +++ b/examples/mnist/reservoir.py @@ -185,7 +185,7 @@ def forward(self, x): optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) # Training the Model -print("\n Training the read out ") +print("\n Training the read out ") pbar = tqdm(enumerate(range(n_epochs))) for epoch, _ in pbar: avg_loss = 0 From 81722e6ff8029c242fc2c4b8994124c801ce3ab7 Mon Sep 17 00:00:00 2001 From: Simon Caby Date: Fri, 18 Jun 2021 10:07:27 +0200 Subject: [PATCH 3/3] add DelayEncoder --- bindsnet/encoding/encoders.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/bindsnet/encoding/encoders.py b/bindsnet/encoding/encoders.py index 111e939fd..6d11e4e48 100644 --- a/bindsnet/encoding/encoders.py +++ b/bindsnet/encoding/encoders.py @@ -115,3 +115,18 @@ def __init__(self, time: int, dt: float = 1.0, **kwargs): super().__init__(time, dt=dt, **kwargs) self.enc = encodings.rank_order + + +class DelayEncoder(Encoder): + def __init__(self, time: int, dt: float = 1.0, **kwargs): + # language=rst + """ + Creates a callable DelayEncoder which encodes as defined in + :code:`bindsnet.encoding.delay` + + :param time: Length of delay spike train per input variable. + :param dt: Simulation time step. + """ + super().__init__(time, dt=dt, **kwargs) + + self.enc = encodings.delay \ No newline at end of file