NO SNOW: fix bug in xml read when custom schema is non structtype.

[sfc-gh-yuwang]

1. Which Jira issue is this PR addressing? Make sure that there is an accompanying issue to your PR.

   Fixes SNOW-NNNNNNN

2. Fill out the following pre-review checklist:

   • I am adding a new automated test(s) to verify correctness of my new code
     • If this test skips Local Testing mode, I'm requesting review from @snowflakedb/local-testing
   • I am adding new logging messages
   • I am adding a new telemetry message
   • I am adding new credentials
   • I am adding a new dependency
   • If this is a new feature/behavior, I'm adding the Local Testing parity changes.
   • I acknowledge that I have ensured my changes to be thread-safe. Follow the link for more information: Thread-safe Developer Guidelines
   • If adding any arguments to public Snowpark APIs or creating new public Snowpark APIs, I acknowledge that I have ensured my changes include AST support. Follow the link for more information: AST Support Guidelines

3. Please describe how your code solves the related issue.

when reading a xml file like this:
<test>
<num>1</num>
<str1>NULL</str1>
<str2></str2>
<str3 id="empty">xxx</str3>
</test>

with code:
test_schema = StructType([
StructField("num", IntegerType(), True),
StructField("str1", StringType(), True),
StructField("str2", StringType(), True),
StructField("str3", StringType(), True),
])

df = (
spark.read
.option("rowTag", "test")
.schema(test_schema)
.xml("<file path>")
)
print(df.collect())

pyspark give you:
[Row(num=1, str1='NULL', str2='', str3='xxx')]
while currently snowpark would give you:
[Row(num=1, str1='NULL', str2='', str3='{"_VALUE": "xxx", "_id": "empty"}']

indicating that current xml custom schema does not process element with attributes + schema is not structtype correctly. this PR is meant to fix this bug

[sfc-gh-aling]

nit: please move to 1.46.0