python CombineGlobally().with_fanout() cause duplicate combine results for sliding windows

not only there are more than 1 result per window, results for each window got duplicated as well.

here is some code I made to reproduce the issue, just run it with and without `*.with_fanout*`

if running with Dataflow runner, add appropriate `*gs://path/*` in `*WriteToText*`

 
```

import apache_beam as beam
from apache_beam.transforms import window
from apache_beam.utils.timestamp import Timestamp

class ListFn(beam.CombineFn):
def create_accumulator(self):
return []

def add_input(self, mutable_accumulator, element):
return mutable_accumulator + [element]

def merge_accumulators(self, accumulators):
res = []
for accu in accumulators:
res = res + accu
return res

def extract_output(self, accumulator):
return accumulator

p = beam.Pipeline()

(
p
| beam.Create([
window.TimestampedValue(1, Timestamp(seconds=1596216396)),

window.TimestampedValue(2, Timestamp(seconds=1596216397)),
window.TimestampedValue(3, Timestamp(seconds=1596216398)),

window.TimestampedValue(4, Timestamp(seconds=1596216399)),
window.TimestampedValue(5, Timestamp(seconds=1596216400)),

window.TimestampedValue(6, Timestamp(seconds=1596216402)),
window.TimestampedValue(7, Timestamp(seconds=1596216403)),

window.TimestampedValue(8, Timestamp(seconds=1596216405))])
| beam.WindowInto(window.SlidingWindows(10, 5))
| beam.CombineGlobally(ListFn()).without_defaults().with_fanout(5)
| beam.Map(repr)

| beam.io.WriteToText("py-test-result", file_name_suffix='.json', num_shards=1))

p.run()

```

Imported from Jira [BEAM-10617](https://issues.apache.org/jira/browse/BEAM-10617). Original Jira may contain additional context.
Reported by: leiyiz.