wehub-resource-sync
258 lines
11 KiB
Python
258 lines
11 KiB
Python
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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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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# http://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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# =============================================================================
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"""Tests for the functional saver."""
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import os
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import time
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from tensorflow.python.checkpoint import checkpoint
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from tensorflow.python.checkpoint import checkpoint_options
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from tensorflow.python.checkpoint import functional_saver
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from tensorflow.python.checkpoint import graph_view
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from tensorflow.python.eager import context
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from tensorflow.python.eager import remote
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from tensorflow.python.eager import test
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from tensorflow.python.eager import wrap_function
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from tensorflow.python.framework import config
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import ops
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from tensorflow.python.framework import test_util
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from tensorflow.python.module import module
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from tensorflow.python.ops import gen_io_ops
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from tensorflow.python.ops import resource_variable_ops
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from tensorflow.python.platform import gfile
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from tensorflow.python.training import server_lib
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from tensorflow.python.training.saving import saveable_object_util
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LOCALHOST = "/job:localhost/replica:0/task:0/device:CPU:0"
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class SaverTest(test.TestCase):
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def setUp(self):
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super(SaverTest, self).setUp()
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cpus = config.list_physical_devices("CPU")
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# Set 3 virtual CPUs
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config.set_logical_device_configuration(cpus[0], [
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context.LogicalDeviceConfiguration(),
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context.LogicalDeviceConfiguration(),
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context.LogicalDeviceConfiguration()
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])
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self.local_options = checkpoint_options.CheckpointOptions(
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experimental_io_device=LOCALHOST)
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def _get_tensors_by_task(self, root):
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serialized_tensors, _, _, _ = (
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checkpoint.TrackableSaver(graph_view.ObjectGraphView(root))
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._gather_serialized_tensors(None))
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tensors_by_task = {}
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for tensor_dict in serialized_tensors.values():
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for checkpoint_key, maybe_tensor in tensor_dict.items():
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if not isinstance(maybe_tensor, dict):
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maybe_tensor = {"": maybe_tensor}
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for slice_spec, tensor in maybe_tensor.items():
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tensor_task = saveable_object_util.set_cpu0(tensor.device)
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(tensors_by_task
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.setdefault(tensor_task, {})
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.setdefault(checkpoint_key, {})[slice_spec]) = tensor
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return tensors_by_task
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@test_util.run_in_graph_and_eager_modes
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def test_resource_variable(self):
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v1 = resource_variable_ops.ResourceVariable(2.)
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self.evaluate(v1.initializer)
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saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v1, "x"))
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prefix = os.path.join(self.get_temp_dir(), "ckpt")
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self.evaluate(saver.save(constant_op.constant(prefix)))
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self.assertEqual(2, len(gfile.Glob(prefix + "*")))
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self.evaluate(v1.assign(1.))
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self.evaluate(saver.restore(prefix))
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self.assertEqual(2., self.evaluate(v1))
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v2 = resource_variable_ops.ResourceVariable(3.)
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self.evaluate(v2.initializer)
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second_saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v2, "x"))
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self.evaluate(second_saver.restore(prefix))
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self.assertEqual(2., self.evaluate(v2))
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@test_util.run_in_graph_and_eager_modes
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def test_resource_variable_use_localhost(self):
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v1 = resource_variable_ops.ResourceVariable(2.)
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self.evaluate(v1.initializer)
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saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v1, "x"))
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prefix = os.path.join(self.get_temp_dir(), "ckpt")
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self.evaluate(saver.save(constant_op.constant(prefix), self.local_options))
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self.assertEqual(2, len(gfile.Glob(prefix + "*")))
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self.evaluate(v1.assign(1.))
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self.evaluate(saver.restore(prefix, self.local_options))
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self.assertEqual(2., self.evaluate(v1))
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v2 = resource_variable_ops.ResourceVariable(3.)
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self.evaluate(v2.initializer)
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second_saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v2, "x"))
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self.evaluate(second_saver.restore(prefix, self.local_options))
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self.assertEqual(2., self.evaluate(v2))
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# In graph mode, verify that the save and restore ops were set to run on
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# localhost.
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if not context.executing_eagerly():
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for op in ops.get_default_graph().get_operations():
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if op.type in ("SaveV2", "RestoreV2"):
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self.assertEqual(LOCALHOST, op.device)
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def test_to_proto(self):
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v1 = resource_variable_ops.ResourceVariable(2.)
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saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v1, "x"))
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prefix = os.path.join(self.get_temp_dir(), "ckpt")
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proto_accumulator = []
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wrapped = wrap_function.wrap_function(
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lambda: proto_accumulator.append(saver.to_proto()), signature=())
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self.assertEqual(1, len(proto_accumulator))
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proto = proto_accumulator[0]
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save = wrapped.prune(
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feeds=wrapped.graph.get_tensor_by_name(proto.filename_tensor_name),
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fetches=wrapped.graph.get_tensor_by_name(proto.save_tensor_name))
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restore = wrapped.prune(
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feeds=wrapped.graph.get_tensor_by_name(proto.filename_tensor_name),
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fetches=wrapped.graph.get_operation_by_name(proto.restore_op_name))
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save_path = save(constant_op.constant(prefix))
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v1.assign(1.)
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restore(constant_op.constant(save_path))
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self.assertEqual(2., self.evaluate(v1))
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v2 = resource_variable_ops.ResourceVariable(3.)
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second_saver = functional_saver.MultiDeviceSaver.from_saveables(
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saveable_object_util.saveable_objects_for_op(v2, "x"))
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second_saver.restore(save_path)
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self.assertEqual(2., self.evaluate(v2))
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@test_util.disable_tfrt("b/171765113: server is not supported in TFRT yet.")
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def test_checkpoint_is_sharded_by_task(self):
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servers = [server_lib.Server.create_local_server() for _ in range(3)]
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cluster_spec = server_lib.ClusterSpec({
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"worker": [s.target[len("grpc://"):] for s in servers]})
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remote.connect_to_cluster(cluster_spec)
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with ops.device("/job:worker/task:0/cpu:0"):
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v0 = resource_variable_ops.ResourceVariable(0.)
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with ops.device("/job:worker/task:1/cpu:0"):
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v1 = resource_variable_ops.ResourceVariable(1.)
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with ops.device("/job:worker/task:2/cpu:0"):
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v2 = resource_variable_ops.ResourceVariable(2.)
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self.evaluate([v0.initializer, v1.initializer, v2.initializer])
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saver = functional_saver.MultiDeviceSaver.from_saveables(
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list(saveable_object_util.saveable_objects_for_op(v0, "v0")) +
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list(saveable_object_util.saveable_objects_for_op(v1, "v1")) +
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list(saveable_object_util.saveable_objects_for_op(v2, "v2")))
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prefix = os.path.join(self.get_temp_dir(), "ckpt")
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self.evaluate(saver.save(constant_op.constant(prefix)))
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self.assertEqual(4, len(gfile.Glob(prefix + "*")))
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self.evaluate(v0.assign(-1.))
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self.evaluate(v1.assign(-1.))
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self.evaluate(v2.assign(-1.))
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self.evaluate(saver.restore(constant_op.constant(prefix)))
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self.assertEqual(0., self.evaluate(v0))
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self.assertEqual(1., self.evaluate(v1))
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self.assertEqual(2., self.evaluate(v2))
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@test_util.run_in_graph_and_eager_modes
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def test_checkpoint_multi_device_using_localhost(self):
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with ops.device("cpu:0"):
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v0 = resource_variable_ops.ResourceVariable(0.)
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with ops.device("cpu:1"):
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v1 = resource_variable_ops.ResourceVariable(1.)
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with ops.device("cpu:2"):
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v2 = resource_variable_ops.ResourceVariable(2.)
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self.evaluate([v0.initializer, v1.initializer, v2.initializer])
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saver = functional_saver.MultiDeviceSaver.from_saveables(
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list(saveable_object_util.saveable_objects_for_op(v0, "v0")) +
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list(saveable_object_util.saveable_objects_for_op(v1, "v1")) +
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list(saveable_object_util.saveable_objects_for_op(v2, "v2")))
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prefix = os.path.join(self.get_temp_dir(), "ckpt")
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self.evaluate(saver.save(constant_op.constant(prefix), self.local_options))
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self.assertEqual(2, len(gfile.Glob(prefix + "*")))
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self.evaluate(v0.assign(-1.))
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self.evaluate(v1.assign(-1.))
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self.evaluate(v2.assign(-1.))
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self.evaluate(
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saver.restore(constant_op.constant(prefix), self.local_options))
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self.assertEqual(0., self.evaluate(v0))
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self.assertEqual(1., self.evaluate(v1))
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self.assertEqual(2., self.evaluate(v2))
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# In graph mode, verify that the save and restore ops were set to run on
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# localhost.
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if not context.executing_eagerly():
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for op in ops.get_default_graph().get_operations():
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if op.type in ("SaveV2", "RestoreV2", "MergeV2Checkpoints"):
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self.assertEqual(LOCALHOST, op.device)
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def test_single_task_save_singlehost_multidevice(self):
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root = module.Module()
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with ops.device("cpu:0"):
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v0 = resource_variable_ops.ResourceVariable(0.)
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with ops.device("cpu:1"):
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v1 = resource_variable_ops.ResourceVariable(1.)
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with ops.device("cpu:2"):
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v2 = resource_variable_ops.ResourceVariable(2.)
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root.v0 = v0
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root.v1 = v1
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root.v2 = v2
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tensors_by_task = self._get_tensors_by_task(root)
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var_names = [
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"v0/.ATTRIBUTES/VARIABLE_VALUE",
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"v1/.ATTRIBUTES/VARIABLE_VALUE",
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"v2/.ATTRIBUTES/VARIABLE_VALUE"
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]
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vars_numpy = [v0.numpy(), v1.numpy(), v2.numpy()]
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tmp_dir = self.get_temp_dir()
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for device in ["cpu:0", "cpu:1", "cpu:2"]:
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for shard, (_, tensor_slice_dict) in enumerate(
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sorted(tensors_by_task.items())[1:]):
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with ops.device(device):
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shard_prefix = gen_io_ops.sharded_filename(
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os.path.join(tmp_dir, str(shard)), shard, 3)
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functional_saver._single_task_save(
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shard_prefix, tensor_slice_dict)
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start_time = time.time()
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max_save_time = start_time + 5 # seconds
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while not (gfile.ListDirectory(tmp_dir) or time.time() > max_save_time):
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pass # eager execution is lovely
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self.assertNotEmpty(gfile.ListDirectory(tmp_dir))
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with ops.device(device):
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restored_dict = functional_saver._single_task_restore(
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shard_prefix, tensor_slice_dict)
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self.evaluate(restored_dict)
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self.assertEqual(
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restored_dict[var_names[shard]][""].numpy(),
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vars_numpy[shard])
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if __name__ == "__main__":
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ops.enable_eager_execution()
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test.main()
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