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NEW QUESTION: 1
A. Option B
B. Option D
C. Option C
D. Option A
Answer: C
NEW QUESTION: 2
Which option can a network specialist use to configure connected route redistribution inside
VRF "TEST" on Cisco IOS XR and allow only the prefix 10.10.10.0/24?
A. route-policy ALLOW-CONN
if source in PERMIT_PREFIX then
pass
else
drop
end-policy
prefix-set PERMIT_PREFIX
10.10.10.0/24
end-set
router bgp 65000
vrf TEST
rd 65000:10000
address-family ipv4 unicast
redistribute connected route-policy ALLOW-CONN
B. route-policy ALLOW-CONN
if destination in PERMIT_PREFIX then
pass
else
drop
end-policy
prefix-set PERMIT_PREFIX
10.10.10.0/24
end-set
router bgp 65000
vrf TEST
rd 65000:10000
address-family ipv4 unicast
redistribute connected route-policy ALLOW-CONN
C. route-policy ALLOW-CONN
if route-type is local and destination in PERMIT_PREFIX then
pass
else
drop
end-policy
prefix-set PERMIT_PREFIX
10.10.10.0/24
end-set
router bgp 65000
vrf TEST
rd 65000:10000
address-family ipv4 unicast
redistribute connected route-policy ALLOW-CONN
D. route-policy ALLOW-CONN
if protocol is connected and source in PERMIT_PREFIX then
pass
else
drop
end-policy
prefix-set PERMIT_PREFIX
10.10.10.0/24
end-set
router bgp 65000
vrf TEST
rd 65000:10000
address-family ipv4 unicast
redistribute connected route-policy ALLOW-CONN"
Answer: B
NEW QUESTION: 3
実験の実行が完了した後、Runオブジェクトのget_metricsメソッドを使用して返すことができるrow_countという名前のメトリックとして行数を記録する必要があります。どのコードを使用する必要がありますか？
A. run.log_table('row_count', rows)
B. run.log_row('row_count', rows)
C. run.upload_file('row_count', './data.csv')
D. run.tag('row_count', rows)
E. run.log('row_count', rows)
Answer: E
Explanation:
Log a numerical or string value to the run with the given name using log(name, value, description=''). Logging a metric to a run causes that metric to be stored in the run record in the experiment. You can log the same metric multiple times within a run, the result being considered a vector of that metric.
Example: run.log("accuracy", 0.95)
Incorrect Answers:
E: Using log_row(name, description=None, **kwargs) creates a metric with multiple columns as described in kwargs. Each named parameter generates a column with the value specified. log_row can be called once to log an arbitrary tuple, or multiple times in a loop to generate a complete table.
Example: run.log_row("Y over X", x=1, y=0.4)
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run