Traceback (most recent call last):


 "bug.py", line 256, in <module>

botst()


 "bug.py", line 210, in botst

decider.decision_process(x, xstd, ndec=400, lr=1e-1)


 "bug.py", line 186, in decision_process

x, xstd, ximp = self.decide(x, xstd, lr=lr)


 "bug.py", line 174, in decide

500


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/optim/optimize.py", line 170, in optimize_acqf

fixed_features=fixed_features,


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/gen.py", line 123, in gen_candidates_scipy

options={k: v for k, v in options.items() if k != "method"},


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/scipy/optimize/_minimize.py", line 600, in minimize

callback=callback, **options)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/scipy/optimize/lbfgsb.py", line 335, in _minimize_lbfgsb

f, g = func_and_grad(x)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/scipy/optimize/lbfgsb.py", line 285, in func_and_grad

f = fun(x, *args)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py", line 326, in function_wrapper

return function(*(wrapper_args + args))


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py", line 64, in __call__

fg = self.fun(x, *args)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/gen.py", line 110, in f

loss = -acquisition_function(X_fix).sum()


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 541, in __call__

result = self.forward(*input, **kwargs)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/utils/transforms.py", line 141, in decorated

return method(cls, X)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/acquisition/analytic.py", line 231, in forward

posterior = self._get_posterior(X=X)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/acquisition/analytic.py", line 62, in _get_posterior

posterior = self.model.posterior(X)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/botorch/models/gpytorch.py", line 255, in posterior

mvn = self(X)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/gpytorch/models/approximate_gp.py", line 81, in __call__

return self.variational_strategy(inputs, prior=prior)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/gpytorch/variational/variational_strategy.py", line 165, in __call__

return super().__call__(x, prior=prior)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/gpytorch/variational/_variational_strategy.py", line 127, in __call__

variational_inducing_covar=variational_dist_u.lazy_covariance_matrix,


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/gpytorch/module.py", line 24, in __call__

outputs = self.forward(*inputs, **kwargs)


 "/home/cisprague/anaconda3/lib/python3.7/site-packages/gpytorch/variational/variational_strategy.py", line 100, in forward

interp_term = torch.triangular_solve(induc_data_covar.double(), L, upper=False)[0].to(full_inputs.dtype)
RuntimeError: The size of tensor a (2) must match the size of tensor b (500) at non-singleton dimension 0

Traceback (most recent call last):


 "/home/virtuoso_irfan/tacotron/datasets/datafeeder.py", line 74, in run

self._enqueue_next_group()


 "/home/virtuoso_irfan/tacotron/datasets/datafeeder.py", line 96, in _enqueue_next_group

self._session.run(self._enqueue_op, feed_dict=feed_dict)


 "/home/virtuoso_irfan/tacotron/.t1/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 929, in run

run_metadata_ptr)


 "/home/virtuoso_irfan/tacotron/.t1/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1075, in _run

raise RuntimeError('Attempted to use a closed Session.')
RuntimeError: Attempted to use a closed Session.
