def testParameterOverrides(self):
os.environ['TF_CONFIG'] = """
{
"cluster": {
"ps": ["ps0:2222", "ps1:2222"],
"worker": ["worker0:2222", "worker1:2222", "worker2:2222"]
},
"rpc_layer": "grpc",
"task": {
"type": "ps",
"index": 1
}
}
"""
cluster_resolver = TFConfigClusterResolver(task_type='ps',
task_index=0,
num_accelerators=8)
self.assertEqual('grpc://ps0:2222', cluster_resolver.master())
self.assertEqual('ps', cluster_resolver.task_type)
self.assertEqual(0, cluster_resolver.task_index)
self.assertEqual(8, cluster_resolver.num_accelerators())
cluster_resolver.task_type = 'worker'
cluster_resolver.task_index = 1
cluster_resolver.rpc_layer = 'test'
self.assertEqual('test://worker1:2222', cluster_resolver.master())
self.assertEqual('worker', cluster_resolver.task_type)
self.assertEqual(1, cluster_resolver.task_index)
self.assertEqual('test', cluster_resolver.rpc_layer)
def testNumAcceleratorsFilterTasksByEnvVar(self, mock_list_devices,
mock_eager_list_devices):
os.environ['TF_CONFIG'] = """
{
"cluster": {
"worker1": ["w10:2222"],
"worker2": ["w21:2222", "w22:2222", "w23:2222", "w24:2222"]
},
"rpc_layer": "grpc",
"task": {
"type": "worker1",
"index": "0"
}
}
"""
devices = [
LogicalDevice('/job:worker1/task:0/device:TPU:0', 'TPU'),
LogicalDevice('/job:worker1/task:0/device:TPU:1', 'TPU'),
LogicalDevice('/job:worker1/task:0/device:GPU:0', 'GPU'),
LogicalDevice('/job:worker1/task:0/device:GPU:1', 'GPU'),
LogicalDevice('/job:worker2/task:1/device:TPU:2', 'TPU'),
LogicalDevice('/job:worker2/task:2/device:TPU:3', 'TPU'),
LogicalDevice('/job:worker2/task:3/device:GPU:2', 'GPU'),
LogicalDevice('/job:worker2/task:4/device:GPU:3', 'GPU'),
]
device_list = [
session._DeviceAttributes(d.name, d.device_type, 1024, 0)
for d in devices
]
mock_eager_list_devices.return_value = devices
mock_list_devices.return_value = device_list
resolver = TFConfigClusterResolver()
# By default we read from TF_CONFIG
self.assertEqual(resolver.num_accelerators(), {'TPU': 2, 'GPU': 2})
# Override still works when we want it to
self.assertEqual(
resolver.num_accelerators(task_type='worker2', task_id=3),
{'GPU': 1})
