I have read the threads on how to load a posterior. Accordingly, I am re-initializing my model. But I am then not able to perform posterior predictions with that loaded trace. Am I doing something wrong?

I am sampling a posterior:

```
with pm.Model() as model:
#priors
#...
#operations
#...
posterior = pm.sample(draws=10000, chains=4, cores=1, n_init=2000)
pm.save_trace(posterior, path)
```

Then, in a notebook I want to work on visualizations:

```
with pm.Model() as model:
#priors
#...
#operations
#...
posterior = pm.load_trace(path)
posterior_pred = pm.sample_posterior_predictive(posterior)
```

This gives me the error `TypeError: zip argument #1 must support iteration`

. I am attaching the full error.

```
~/.ve/project_test/lib/python3.7/site-packages/pymc3/sampling.py in
sample_posterior_predictive(trace, samples, model, vars, size, random_seed, progressbar)
1108 param = trace[idx % len_trace]
1109
-> 1110 values = draw_values(vars, point=param, size=size)
1111 for k, v in zip(vars, values):
1112 ppc_trace[k.name].append(v)
~/.ve/project_test/lib/python3.7/site-packages/pymc3/distributions/distribution.py in draw_values(params, point, size)
389 point=point,
390 givens=temp_givens,
--> 391 size=size)
392 givens[next_.name] = (next_, value)
393 drawn[(next_, size)] = value
~/.ve/project_test/lib/python3.7/site-packages/pymc3/distributions/distribution.py in _draw_value(param, point, givens, size)
506 with _DrawValuesContextBlocker():
507 val = np.atleast_1d(dist_tmp.random(point=point,
--> 508 size=None))
509 # Sometimes point may change the size of val but not the
510 # distribution's shape
~/.ve/project_test/lib/python3.7/site-packages/pymc3/distributions/continuous.py in random(self, point, size)
452 """
453 mu, tau, _ = draw_values([self.mu, self.tau, self.sigma],
--> 454 point=point, size=size)
455 return generate_samples(stats.norm.rvs, loc=mu, scale=tau**-0.5,
456 dist_shape=self.shape,
~/.ve/project_test/lib/python3.7/site-packages/pymc3/distributions/distribution.py in draw_values(params, point, size)
420 point=point,
421 givens=givens.values(),
--> 422 size=size)
423 evaluated[param_idx] = drawn[(param, size)] = value
424 givens[param.name] = (param, value)
~/.ve/project_test/lib/python3.7/site-packages/pymc3/distributions/distribution.py in _draw_value(param, point, givens, size)
545 not all(var.dshape == getattr(val, 'shape', tuple())
546 for var, val in zip(input_vars, input_vals))):
--> 547 output = np.array([func(*v) for v in zip(*input_vals)])
548 elif (size is not None and any((val.ndim > var.ndim)
549 for var, val in zip(input_vars, input_vals))):
TypeError: zip argument #1 must support iteration
```