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https://github.com/mudler/LocalAI.git
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a026277ab9
* feat(mlx-distributed): add new MLX-distributed backend Add new MLX distributed backend with support for both TCP and RDMA for model sharding. This implementation ties in the discovery implementation already in place, and re-uses the same P2P mechanism for the TCP MLX-distributed inferencing. The Auto-parallel implementation is inspired by Exo's ones (who have been added to acknowledgement for the great work!) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * expose a CLI to facilitate backend starting Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: make manual rank0 configurable via model configs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add missing features from mlx backend Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Apply suggestion from @mudler Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
88 lines
3.0 KiB
Python
88 lines
3.0 KiB
Python
import unittest
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import subprocess
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import time
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import grpc
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import backend_pb2
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import backend_pb2_grpc
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class TestBackendServicer(unittest.TestCase):
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def setUp(self):
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self.service = subprocess.Popen(
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["python", "backend.py", "--addr", "localhost:50051"]
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)
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time.sleep(10)
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def tearDown(self) -> None:
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self.service.terminate()
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self.service.wait()
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def test_server_startup(self):
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.Health(backend_pb2.HealthMessage())
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self.assertEqual(response.message, b'OK')
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except Exception as err:
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print(err)
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self.fail("Server failed to start")
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finally:
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self.tearDown()
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def test_load_model(self):
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="mlx-community/Llama-3.2-1B-Instruct-4bit"))
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self.assertTrue(response.success)
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self.assertEqual(response.message, "Model loaded successfully")
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except Exception as err:
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print(err)
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self.fail("LoadModel service failed")
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finally:
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self.tearDown()
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def test_text(self):
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="mlx-community/Llama-3.2-1B-Instruct-4bit"))
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self.assertTrue(response.success)
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req = backend_pb2.PredictOptions(Prompt="The capital of France is")
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resp = stub.Predict(req)
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self.assertIsNotNone(resp.message)
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except Exception as err:
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print(err)
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self.fail("text service failed")
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finally:
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self.tearDown()
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def test_sampling_params(self):
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try:
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self.setUp()
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with grpc.insecure_channel("localhost:50051") as channel:
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stub = backend_pb2_grpc.BackendStub(channel)
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response = stub.LoadModel(backend_pb2.ModelOptions(Model="mlx-community/Llama-3.2-1B-Instruct-4bit"))
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self.assertTrue(response.success)
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req = backend_pb2.PredictOptions(
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Prompt="The capital of France is",
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TopP=0.8,
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Tokens=50,
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Temperature=0.7,
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TopK=40,
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MinP=0.05,
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Seed=42,
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)
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resp = stub.Predict(req)
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self.assertIsNotNone(resp.message)
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except Exception as err:
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print(err)
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self.fail("sampling params service failed")
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finally:
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self.tearDown()
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