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3e5ecfe363
Reorder the doc modules into something closer to alphabetical order. Add missing functions from jax.scipy.linalg and jax.scipy.signal to the docs.
64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import functools
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from absl import logging
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from jax._src.lib import xla_bridge
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from jax._src.lib import xla_client
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from jax._src.lib import xla_extension
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_service = None
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def initialize(coordinator_address: str, num_processes: int, process_id: int):
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"""Initialize distributed system for topology discovery.
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Currently, calling ``initialize`` sets up the multi-host GPU backend, and
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is not required for CPU or TPU backends.
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Args:
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coordinator_address: IP address and port of the coordinator. The choice of
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port does not matter, so long as the port is available on the coordinator
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and all processes agree on the port.
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num_processes: Number of processes.
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process_id: Id of the current process.
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Example:
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Suppose there are two GPU hosts, and host 0 is the designated coordinator
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with address ``10.0.0.1:1234``. To initialize the GPU cluster, run the
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following commands before anything else.
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On host 0:
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>>> jax.distributed.initialize('10.0.0.1:1234', 2, 0) # doctest: +SKIP
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On host 1:
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>>> jax.distributed.initialize('10.0.0.1:1234', 2, 1) # doctest: +SKIP
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"""
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if process_id == 0:
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global _service
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assert _service is None, 'initialize should be called once only'
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logging.info('Starting JAX distributed service on %s', coordinator_address)
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_service = xla_extension.get_distributed_runtime_service(coordinator_address,
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num_processes)
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client = xla_extension.get_distributed_runtime_client(coordinator_address,
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process_id)
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logging.info('Connecting to JAX distributed service on %s', coordinator_address)
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client.connect()
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factory = functools.partial(xla_client.make_gpu_client, client, process_id)
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xla_bridge.register_backend_factory('gpu', factory, priority=300)
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