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NEW QUESTION: 1
Which technology is used by SnapView Snapshots to retain the original data of a source LUN?
A. Journal
B. Redirect on First Write
C. Copy on First Write
D. SavVol
Answer: C

NEW QUESTION: 2
CloudFormation의 JSON 템플릿을 사용하여 스택 설정을 시도해 보았습니다. 약 5 또는 6을 설정했으나 이제는이 스택에 대해 요금이 부과되는지 궁금해하기 시작합니다.
스택 리소스에 관한 AWS의 청구 정책은 무엇입니까?
A. 트래픽을 가져 오지 않으면 스택 리소스에 대해 요금이 부과되지 않습니다.
B. 운영중인 시간 동안 스택 리소스 비용이 청구됩니다 (스택을 즉시 삭제 한 경우에도 마찬가지 임)
C. 운영 시간 동안 스택 리소스에 대해 요금이 부과됩니다 (단, 60 분 이내에 스택을 삭제 한 경우는 제외).
D. 운영 시간 동안 스택 리소스에 대해 요금이 부과됩니다 (30 분 이내에 스택을 삭제 한 경우는 제외).
Answer: B
Explanation:
설명
스택은 단일 단위로 관리 할 수있는 AWS 리소스의 모음입니다. 즉, 스택을 생성, 업데이트 또는 삭제하여 리소스 모음을 생성, 업데이트 또는 삭제할 수 있습니다. 스택의 모든 리소스는 스택의 AWS CloudFormation 템플릿에 의해 정의됩니다. 예를 들어 스택에는 웹 서버, 데이터베이스 및 네트워킹 규칙과 같이 웹 응용 프로그램을 실행하는 데 필요한 모든 리소스가 포함될 수 있습니다. 웹 응용 프로그램이 더 이상 필요하지 않으면 스택을 삭제하면 관련된 모든 자원이 삭제됩니다. 스택을 즉시 삭제 한 경우에도 운영중인 스택 리소스에 대해 요금이 부과됩니다.
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/stacks.html

NEW QUESTION: 3
You need to use the Python language to build a sampling strategy for the global penalty detection models.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: import pytorch as deeplearninglib
Box 2: ..DistributedSampler(Sampler)..
DistributedSampler(Sampler):
Sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with class:`torch.nn.parallel.DistributedDataParallel`. In such case, each process can pass a DistributedSampler instance as a DataLoader sampler, and load a subset of the original dataset that is exclusive to it.
Scenario: Sampling must guarantee mutual and collective exclusively between local and global segmentation models that share the same features.
Box 3: optimizer = deeplearninglib.train. GradientDescentOptimizer(learning_rate=0.10) Incorrect Answers: ..SGD..
Scenario: All penalty detection models show inference phases using a Stochastic Gradient Descent (SGD) are running too slow.
Box 4: .. nn.parallel.DistributedDataParallel..
DistributedSampler(Sampler): The sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with :class:`torch.nn.parallel.DistributedDataParallel`.
References:
https://github.com/pytorch/pytorch/blob/master/torch/utils/data/distributed.py