[BUG] dask_cudf from_delayed throws exception when meta is included in the from_delayed

Exception:

```
Columns: [_col10, _col5, _col0, _col12, visit_date]
Index: [], 'from_delayed')
kwargs: {}
Exception: "ValueError('Metadata mismatch found in `from_delayed`.\\n\\nExpected partition of type `pandas.core.frame.DataFrame` but got `cudf.core.dataframe.DataFrame`')"
```

Reproducer:
```
import cudf
import numpy as np
from dask.dataframe import from_delayed
from dask.delayed import delayed
import numpy as np
import cudf
from dask.distributed import Client
from dask_cuda import LocalCUDACluster
import dask_cudf

df = cudf.DataFrame()
for i in range(100):
df[f'_col{i}'] = np.random.randint(20, size=100)

df.to_orc('test1.orc')
df.to_orc('test0.orc')

files = [(('a',), 'test0.orc'), (('a',), 'test1.orc')]
print(files)

def rd(f, cols, meta=None):
if partitions:
cols = list(set(cols) - set([x[0] for x in partitions]))
if type(f).__name__ == 'str':
f = ((), f)
df = cudf.read_orc(f[1], columns=cols, use_index=False)
if partitions:
for i, col in enumerate(partitions):
df[col[0]] = f[0][i]
df[col[0]] = df[col[0]].astype(col[1])
if meta:
return df[list(meta.keys())]
else:
return df

partitions =[('visit_date', 'str')]
cols = ['_col0', '_col12', '_col10', '_col5']
meta = dict(rd(files[0], cols, meta=None).dtypes)
for i in partitions:
meta[i[0]] = i[1]

print(meta)

def main():
c=Client(LocalCUDACluster())
dfs=[delayed(rd)(f, cols=cols, meta=meta) for f in files[:2]]
xx = dask_cudf.from_delayed(dfs, meta=meta)
print(xx.compute())

if __name__ == "__main__":
main()
```

this issue is very similar to issue here: https://github.com/dask/dask/issues/8528

the difference is from_delayed with meta, throws another exception "The columns in the computed data do not match the columns in the provided metadata" even though both dfs have same columns and dtypes.
since we provide the meta here, we run into different issue.