# Copyright 2018 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Device-related support functions.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.python.eager import context from tensorflow.python.framework import config from tensorflow.python.framework import device as tf_device from tensorflow.python.framework import ops def canonicalize(d, default=None): """Canonicalize device string. If d has missing components, the rest would be deduced from the `default` argument or from '/replica:0/task:0/device:CPU:0'. For example: If d = '/cpu:0', default='/job:worker/task:1', it returns '/job:worker/replica:0/task:1/device:CPU:0'. If d = '/cpu:0', default='/job:worker', it returns '/job:worker/replica:0/task:0/device:CPU:0'. If d = '/gpu:0', default=None, it returns '/replica:0/task:0/device:GPU:0'. Note: This uses "job:localhost" as the default if executing eagerly. Args: d: a device string or tf.config.LogicalDevice default: a string for default device if d doesn't have all components. Returns: a canonicalized device string. """ if isinstance(d, context.LogicalDevice): d = tf_device.DeviceSpec.from_string(d.name) else: d = tf_device.DeviceSpec.from_string(d) assert d.device_type is None or d.device_type == d.device_type.upper(), ( "Device type '%s' must be all-caps." % (d.device_type,)) # Fill in missing device fields using defaults. result = tf_device.DeviceSpec( replica=0, task=0, device_type="CPU", device_index=0) if ops.executing_eagerly_outside_functions(): # Try to deduce job, replica and task in case it's in a multi worker setup. # TODO(b/151452748): Using list_logical_devices is not always safe since it # may return remote devices as well, but we're already doing this elsewhere. host_cpu = tf_device.DeviceSpec.from_string( config.list_logical_devices("CPU")[0].name) if host_cpu.job: result = result.make_merged_spec(host_cpu) else: # The default job is localhost if eager execution is enabled result = result.replace(job="localhost") if default: # Overrides any defaults with values from the default device if given. result = result.make_merged_spec( tf_device.DeviceSpec.from_string(default)) # Apply `d` last, so that it's values take precedence over the defaults. result = result.make_merged_spec(d) return result.to_string() def resolve(d): """Canonicalize `d` with current device as default.""" return canonicalize(d, default=current()) class _FakeNodeDef(object): """A fake NodeDef for _FakeOperation.""" __slots__ = ["op", "name"] def __init__(self): self.op = "" self.name = "" class _FakeOperation(object): """A fake Operation object to pass to device functions.""" def __init__(self): self.device = "" self.type = "" self.name = "" self.node_def = _FakeNodeDef() def _set_device(self, device): self.device = ops._device_string(device) # pylint: disable=protected-access def _set_device_from_string(self, device_str): self.device = device_str def current(): """Return a string (not canonicalized) for the current device.""" # TODO(josh11b): Work out how this function interacts with ops.colocate_with. if ops.executing_eagerly_outside_functions(): d = context.context().device_name else: op = _FakeOperation() ops.get_default_graph()._apply_device_functions(op) # pylint: disable=protected-access d = op.device return d def get_host_for_device(device): """Returns the corresponding host device for the given device.""" spec = tf_device.DeviceSpec.from_string(device) return tf_device.DeviceSpec( job=spec.job, replica=spec.replica, task=spec.task, device_type="CPU", device_index=0).to_string() def local_devices_from_num_gpus(num_gpus): """Returns device strings for local GPUs or CPU.""" return (tuple("/device:GPU:%d" % i for i in range(num_gpus)) or ("/device:CPU:0",))