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NEW QUESTION: 1
結果について正しい説明はどれですか？
A. コストとリスクを削減することにより、サービスプロバイダーの価値を共創します。
B. サービス消費者に提供される成果物です。
C. 出力に基づいてサービスプロバイダーに製品を提供します。
D. サービス利用者が望ましい結果を達成できるようにします。
Answer: D

NEW QUESTION: 2
Your network contains two servers named Server1 and Server2 that run Windows Server 2008 R2. Server1 and
Server2 are nodes in a failover cluster named Cluster1. The network contains two servers named Server3 and Server4
that run Windows Server 2012 R2. Server3 and Server4 are nodes in a failover cluster named Cluster2.
You need to move all of the applications and the services from Cluster1 to Cluster2.
What should you do first from Failover Cluster Manager?
A. On a server in Cluster1, configure Cluster-Aware Updating.
B. On a server in Cluster2, click Move Core Cluster Resources, and then click Best Possible Node.
C. On a server in Cluster2, click Move Core Cluster Resources, and then click Select Node...
D. On a server in Cluster2, click Migrate Roles.
Answer: D
Explanation:
http://blogs.msdn.com/b/clustering/archive/2012/06/25/10323434.aspx

NEW QUESTION: 3
For accessibility assistance, which of the following programs is an on-screen keyboard?
A. atkb
B. GOK
C. xkb
D. xOSK
Answer: B

NEW QUESTION: 4
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

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