Binops between `dd.Series` and NumPy arrays fail while inferring meta

**Minimal Complete Verifiable Example**:

```python
import dask.dataframe as dd
import numpy as np

arr = np.arange(10)
series = dd.from_array(arr)
series + arr
```
```python
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/dev/dask/dask/dataframe/utils.py in raise_on_meta_error(funcname, udf)
175 try:
--> 176 yield
177 except Exception as e:

~/dev/dask/dask/dataframe/core.py in elemwise(op, *args, **kwargs)
5332 with raise_on_meta_error(funcname(op)):
-> 5333 meta = partial_by_order(*parts, function=op, other=other)
5334

~/dev/dask/dask/utils.py in partial_by_order(*args, **kwargs)
1169 args2.insert(i, arg)
-> 1170 return function(*args2, **kwargs)
1171

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/common.py in new_method(self, other)
64
---> 65 return method(self, other)
66

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/__init__.py in wrapper(left, right)
342 rvalues = extract_array(right, extract_numpy=True)
--> 343 result = arithmetic_op(lvalues, rvalues, op)
344

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/array_ops.py in arithmetic_op(left, right, op)
189 with np.errstate(all="ignore"):
--> 190 res_values = na_arithmetic_op(lvalues, rvalues, op)
191

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/array_ops.py in na_arithmetic_op(left, right, op, is_cmp)
142 try:
--> 143 result = expressions.evaluate(op, left, right)
144 except TypeError:

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/computation/expressions.py in evaluate(op, a, b, use_numexpr)
232 if use_numexpr:
--> 233 return _evaluate(op, op_str, a, b) # type: ignore
234 return _evaluate_standard(op, op_str, a, b)

~/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/computation/expressions.py in _evaluate_standard(op, op_str, a, b)
67 with np.errstate(all="ignore"):
---> 68 return op(a, b)
69

ValueError: operands could not be broadcast together with shapes (2,) (10,)

The above exception was the direct cause of the following exception:

ValueError Traceback (most recent call last)
in
----> 1 series + arr

~/dev/dask/dask/dataframe/core.py in (self, other)
1561 return lambda self, other: elemwise(op, other, self)
1562 else:
-> 1563 return lambda self, other: elemwise(op, self, other)
1564
1565 def rolling(self, window, min_periods=None, center=False, win_type=None, axis=0):

~/dev/dask/dask/dataframe/core.py in elemwise(op, *args, **kwargs)
5331 ]
5332 with raise_on_meta_error(funcname(op)):
-> 5333 meta = partial_by_order(*parts, function=op, other=other)
5334
5335 result = new_dd_object(graph, _name, meta, divisions)

~/miniconda3/envs/dask-dev/lib/python3.8/contextlib.py in __exit__(self, type, value, traceback)
129 value = type()
130 try:
--> 131 self.gen.throw(type, value, traceback)
132 except StopIteration as exc:
133 # Suppress StopIteration *unless* it's the same exception that

~/dev/dask/dask/dataframe/utils.py in raise_on_meta_error(funcname, udf)
195 )
196 msg = msg.format(" in `{0}`".format(funcname) if funcname else "", repr(e), tb)
--> 197 raise ValueError(msg) from e
198
199

ValueError: Metadata inference failed in `add`.

Original error is below:
------------------------
ValueError('operands could not be broadcast together with shapes (2,) (10,) ')

Traceback:
---------
File "/Users/gabe/dev/dask/dask/dataframe/utils.py", line 176, in raise_on_meta_error
yield
File "/Users/gabe/dev/dask/dask/dataframe/core.py", line 5333, in elemwise
meta = partial_by_order(*parts, function=op, other=other)
File "/Users/gabe/dev/dask/dask/utils.py", line 1170, in partial_by_order
return function(*args2, **kwargs)
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/common.py", line 65, in new_method
return method(self, other)
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/__init__.py", line 343, in wrapper
result = arithmetic_op(lvalues, rvalues, op)
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/array_ops.py", line 190, in arithmetic_op
res_values = na_arithmetic_op(lvalues, rvalues, op)
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/ops/array_ops.py", line 143, in na_arithmetic_op
result = expressions.evaluate(op, left, right)
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/computation/expressions.py", line 233, in evaluate
return _evaluate(op, op_str, a, b) # type: ignore
File "/Users/gabe/miniconda3/envs/dask-dev/lib/python3.8/site-packages/pandas/core/computation/expressions.py", line 68, in _evaluate_standard
return op(a, b)
```

**Anything else we need to know?**:

We have a [`_maybe_from_pandas`](https://github.com/dask/dask/blob/56d1891c15320872b815f1ab2f8e41867b231e5e/dask/dataframe/core.py#L5264) coercion for the input arguments—perhaps there should also be an equivalent `_maybe_from_array`? FWIW, this works as expected:
```python
>>> import dask.array as da
>>> darr = da.from_array(arr)
>>> series + darr
Dask Series Structure:
npartitions=1
0 int64
9 ...
dtype: int64
Dask Name: add, 3 tasks
```
So turning any arrays in the inputs into dask arrays might be sufficient.

**Environment**:

- Dask version: 56d1891c15320872b815f1ab2f8e41867b231e5e
- Python version: 3.8.8
- Operating System: macOS
- Install method (conda, pip, source): source