Summary:
Convert from PlanDef ProtoBuf into python Plan object by recursively creating
Nets and ExecutionSteps.
Also support running Plan object directly in Session.
Reviewed By: azzolini
Differential Revision: D5608393
fbshipit-source-id: c0ae3b6da743a759af6db3b614a5a3935fe0b34c
Summary:
Advantages of cloning the tasks/execution_steps at runtime:
- Less complexity on the python side: no need to clone nets and add prefixes to blob names
- Faster start-up: we had cases of complex plans that took up to 30min to be created.
- Better isolation: each task cloned at runtime has its own child workspace, preventing false sharing of blobs.
- Opens up possibility for dynamic scheduling: Number of threads per task can be increased on the fly, at runtime.
Reviewed By: dzhulgakov
Differential Revision: D5100730
fbshipit-source-id: 71b83193b135da4e6eaf2536d8fc266528e1fdcc
Summary: These return views in Python 3 which would not do anything in a lot of usages currently present in Caffe2. This diff simply removes (almost) all usages of these two in Caffe2 and sub projects in favor of comprehensions which are also easier to read/understand
Reviewed By: akyrola
Differential Revision: D5142049
fbshipit-source-id: e800631d2df7d0823fed698cae46c486038007dc
Summary: Set up a server node that periodically gathers values of all nodes' perf counters, allowing to publish them at once.
Reviewed By: dzhulgakov
Differential Revision: D4555116
fbshipit-source-id: 8e49ac8353b52b2be82aedf305762478e7fa687a
Summary:
We were running into a problem where a Job could not be pickled. It needs to be pickled in order for the master flow operator to execute it using the session.
This creates a concept of "compiled" Job, that pretty much only stores protobufs with the Jobs to be executed, avoiding any issue with pickling.
Reviewed By: dzhulgakov
Differential Revision: D4554799
fbshipit-source-id: 2ee9877ca49a796d51925e5ec917436e3d930984
Summary:
Previously we had several limitations for a reporter net:
- needed to be a net, not an execution step
- only one allowed per execution step, with a single interval
Now, "reporter nets" become repoter steps and multiple of them can be specified with different timeouts.
Reviewed By: dzhulgakov
Differential Revision: D4583686
fbshipit-source-id: ad7266e16f96e7829fd24dcc1f165f39e9db573d
Summary:
Outline of changes:
- add single-operator support to Caffe2-Flow integration (based on Alisson's suggestions)
- because of above support we can move graph construction to the main workflow body and pass the job to the Flow operator doing running, similarly to the distributed case
- after that it's easy to unify code even more
- there's some trickery required to make sure model exporting doesn't pollute Cluster info (as TaskGroup.to_task() creates new tasks)
Important: this diff changes train_local behavior by introducing queue between preprocessing and trainer (before we did everything on trainer thread). It doesn't seem to impact perf much (even slightly positive), so I guess it's fine. It also allows for better unification.
I'll follow up with a separate diff that moves max_examples gating to multi_reader (including train_local) and then we can enable checkpointing.
Reviewed By: xianjiec
Differential Revision: D4526079
fbshipit-source-id: 8c44044f45e7738e9b13e5b3acfbb994bc5a3d72
Summary:
- NetBuilder now honors its name
- When Nets are created in the context of a NetBuilder, they take NetBuilder's name as prefix
- When a NetBuilder is created in the context of a Task, it takes the Tasks's name.
- pipe() now tries to find a good name based on its processor's, output or input queue's name.
- RPC tries to find a name from its handler's name.
- Better names in DataStream
- net_printer prints the name of Tasks and Steps
- net_printer optionally factors out common prefixes form blob names.
Differential Revision: D4527578
fbshipit-source-id: 5d3d1237c186e9576313c5aa01cc8800a9051217
Summary: This allows to have a task-local report net before the Task is created. To be used in global counter (diff soon)
Reviewed By: dzhulgakov
Differential Revision: D4497771
fbshipit-source-id: 24ec7c8e95466abbd83fbea79b58717d81201857
Summary: See distributed.py for example of usage
Reviewed By: xianjiec
Differential Revision: D4467723
fbshipit-source-id: c74f71bebaa1751098379838d3da55945aac62bd
