More Elegant Fail for Cases with No Quadratic Biases

**Current Problem**
When no quadratic biases are present in a penaltymodel, return an error that is more comprehensible to the end user. (Note: end user is likely to be calling the penaltymodel from `stitch(..)` and may not be able to understand the error from so deep in the penaltymodel stack)

```
import dwavebinarycsp as dbc
csp = dbc.ConstraintSatisfactionProblem(dbc.BINARY)
csp.add_constraint(lambda x: x>0, ['a'])
bqm = dbc.stitch(new_csp, min_classical_gap=3)
```
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
in
----> 1 new_bqm = dbc.stitch(new_csp, min_classical_gap=3)

~/envs/ocean3/lib/python3.7/site-packages/dwavebinarycsp/compilers/stitcher.py in stitch(csp, min_classical_gap, max_graph_size)
177 # try to use the penaltymodel ecosystem
178 try:
--> 179 pmodel = pm.get_penalty_model(spec)
180 except pm.ImpossiblePenaltyModel:
181 # hopefully adding more variables will make it possible

~/envs/ocean3/lib/python3.7/site-packages/penaltymodel/core/interface.py in get_penalty_model(specification)
68 # asynchronously
69 for cache in iter_caches():
---> 70 cache(pm)
71
72 return pm

~/envs/ocean3/lib/python3.7/site-packages/penaltymodel/cache/interface.py in cache_penalty_model(penalty_model, database)
94 # load into the database
95 with conn as cur:
---> 96 insert_penalty_model(cur, penalty_model)
97
98 # close the connection

~/envs/ocean3/lib/python3.7/site-packages/penaltymodel/cache/database_manager.py in insert_penalty_model(cur, penalty_model)
478 insert_graph(cur, nodelist, edgelist, encoded_data)
479 insert_feasible_configurations(cur, penalty_model.feasible_configurations, encoded_data)
--> 480 insert_ising_model(cur, nodelist, edgelist, linear, quadratic, offset, encoded_data)
481
482 encoded_data['decision_variables'] = json.dumps(penalty_model.decision_variables, separators=(',', ':'))

~/envs/ocean3/lib/python3.7/site-packages/penaltymodel/cache/database_manager.py in insert_ising_model(cur, nodelist, edgelist, linear, quadratic, offset, encoded_data)
277 encoded_data['offset'] = offset
278 if 'max_quadratic_bias' not in encoded_data:
--> 279 encoded_data['max_quadratic_bias'] = max(itervalues(quadratic))
280 if 'min_quadratic_bias' not in encoded_data:
281 encoded_data['min_quadratic_bias'] = min(itervalues(quadratic))

ValueError: max() arg is an empty sequence

```
**Proposed Solution**
Catch the case when no quadratics are provided.