Merge pull request #218 from thodkatz/fix-eof

Proper test cleanup and resolve EOF Error

.circleci/config.yml

@@ -2,7 +2,7 @@ version: 2
 jobs:
   checkout_code:
     docker:
-      - image: condaforge/mambaforge
+      - image: condaforge/miniforge3
     working_directory: ~/repo
     steps:
       - checkout
@@ -18,41 +18,37 @@ jobs:
       TIKTORCH_ENV_NAME: tiktorch-server-env
       TIKTORCH_ENV_PREFIX: /opt/conda/envs/tiktorch-server-env
     docker:
-      - image: condaforge/mambaforge
+      - image: condaforge/miniforge3
     working_directory: ~/repo
     steps:
       - restore_cache:
           keys:
             - v1-repo-{{ .Environment.CIRCLE_SHA1 }}
       - restore_cache:
           keys:
-            - v11-dependencies-{{ checksum "environment.yml" }}
-
+            - v11-dependencies-{{ .Environment.CIRCLE_SHA1 }}
       - run: conda config --set channel_priority strict
-      - run: mamba update -n base -c conda-forge --update-all
-      - run: mamba install -c conda-forge conda-build make boa
+      - run: conda update -n base -c conda-forge --update-all
+      - run: conda install -c conda-forge conda-build make boa
       - run: |
-          if [ ! -d ${TIKTORCH_ENV_PREFIX} ]; then
               echo "Creating new environment ${TIKTORCH_ENV_NAME}"
               make devenv
-          fi
-
       - save_cache:
           paths:
             - /opt/conda/envs
-          key: v11-dependencies-{{ checksum "environment.yml" }}
+          key: v11-dependencies-{{ .Environment.CIRCLE_SHA1 }}
 
   pre_commit_check:
     docker:
-      - image: condaforge/mambaforge
+      - image: condaforge/miniforge3
     working_directory: ~/repo
     steps:
       - restore_cache:
           keys:
             - v1-repo-{{ .Environment.CIRCLE_SHA1 }}
       - restore_cache:
           keys:
-            - v11-dependencies-{{ checksum "environment.yml" }}
+            - v11-dependencies-{{ .Environment.CIRCLE_SHA1 }}
 
       - run:
           name: run pre-commit
@@ -63,15 +59,15 @@ jobs:
 
   tests:
     docker:
-      - image: condaforge/mambaforge
+      - image: condaforge/miniforge3
     working_directory: ~/repo
     steps:
       - restore_cache:
           keys:
             - v1-repo-{{ .Environment.CIRCLE_SHA1 }}
       - restore_cache:
           keys:
-            - v11-dependencies-{{ checksum "environment.yml" }}
+            - v11-dependencies-{{ .Environment.CIRCLE_SHA1 }}
 
       - run:
           name: run tests
@@ -83,15 +79,15 @@ jobs:
 
   build_conda_packages:
     docker:
-      - image: condaforge/mambaforge
+      - image: condaforge/miniforge3
     working_directory: ~/repo
     steps:
       - restore_cache:
           keys:
             - v1-repo-{{ .Environment.CIRCLE_SHA1 }}
 
-      - run: mamba config --set channel_priority strict
-      - run: mamba install -c conda-forge conda-build anaconda-client boa
+      - run: conda config --set channel_priority strict
+      - run: conda install -c conda-forge conda-build anaconda-client boa
       - run:
           name: build packages
           command: |

Makefile

@@ -1,18 +1,7 @@
 SHELL=/bin/bash
 ROOT_DIR:=$(shell dirname $(realpath $(firstword $(MAKEFILE_LIST))))
 TIKTORCH_ENV_NAME ?= tiktorch-server-env
-
-sample_model:
-	cd tests/data/dummy && zip -r $(ROOT_DIR)/dummy.tmodel ./*
-
-unet2d:
-	cd tests/data/unet2d && zip -r $(ROOT_DIR)/unet2d.tmodel ./*
-
-unet2d_onnx:
-	cd tests/data/unet2d_onnx && zip -r $(ROOT_DIR)/onnx.tmodel ./*
-
-dummy_tf:
-	cd tests/data/dummy_tensorflow && zip -r $(ROOT_DIR)/dummy_tf.tmodel ./*
+SUBMODULES = ./vendor/core-bioimage-io-python ./vendor/spec-bioimage-io
 
 protos:
 	python -m grpc_tools.protoc -I./proto --python_out=tiktorch/proto/ --grpc_python_out=tiktorch/proto/ ./proto/*.proto
@@ -21,18 +10,23 @@ protos:
 version:
 	python -c "import sys; print(sys.version)"
 
-
 devenv:
 	. $$(conda info --base)/etc/profile.d/conda.sh
 	mamba env create --file environment.yml --name $(TIKTORCH_ENV_NAME)
-	conda run -n $(TIKTORCH_ENV_NAME) pip install . ./vendor/core-bioimage-io-python ./vendor/spec-bioimage-io
+	make install_submodules
 
 run_server:
 	. $$(conda info --base)/etc/profile.d/conda.sh; conda activate $(TIKTORCH_ENV_NAME); python -m tiktorch.server
 
+install_submodules:
+	@echo "Installing submodules $(SUBMODULES)"
+	@for package in $(SUBMODULES) ; do \
+		echo $$package ; \
+		conda run -n $(TIKTORCH_ENV_NAME) pip install -e $$package ; \
+	done
 
 remove_devenv:
 	conda env remove --yes --name $(TIKTORCH_ENV_NAME)
 
 
-.PHONY: protos version sample_model devenv remove_devenv dummy_tf
+.PHONY: *

tests/test_server/test_grpc/test_inference_servicer.py

@@ -27,6 +27,12 @@ def grpc_servicer(data_store):
     return inference_servicer.InferenceServicer(TorchDevicePool(), SessionManager(), data_store)
 
 
+@pytest.fixture(autouse=True)
+def clean(grpc_servicer):
+    yield
+    grpc_servicer.close_all_sessions()
+
+
 @pytest.fixture(scope="module")
 def grpc_stub_cls(grpc_channel):
     return inference_pb2_grpc.InferenceStub
@@ -47,15 +53,13 @@ def method_requiring_session(self, request, grpc_stub):
     def test_model_session_creation(self, grpc_stub, bioimageio_model_bytes):
         model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes))
         assert model.id
-        grpc_stub.CloseModelSession(model)
 
     def test_model_session_creation_using_upload_id(self, grpc_stub, data_store, bioimageio_dummy_explicit_model_bytes):
         id_ = data_store.put(bioimageio_dummy_explicit_model_bytes.getvalue())
 
         rq = inference_pb2.CreateModelSessionRequest(model_uri=f"upload://{id_}", deviceIds=["cpu"])
         model = grpc_stub.CreateModelSession(rq)
         assert model.id
-        grpc_stub.CloseModelSession(model)
 
     def test_model_session_creation_using_random_uri(self, grpc_stub):
         rq = inference_pb2.CreateModelSessionRequest(model_uri="randomSchema://", deviceIds=["cpu"])
@@ -92,36 +96,28 @@ def test_if_model_create_fails_devices_are_released(self, grpc_stub):
             model_blob=inference_pb2.Blob(content=b""), deviceIds=["cpu"]
         )
 
-        model = None
         with pytest.raises(Exception):
-            model = grpc_stub.CreateModelSession(model_req)
+            grpc_stub.CreateModelSession(model_req)
 
         device_by_id = self._query_devices(grpc_stub)
         assert "cpu" in device_by_id
         assert inference_pb2.Device.Status.AVAILABLE == device_by_id["cpu"].status
 
-        if model:
-            grpc_stub.CloseModelSession(model)
-
     def test_use_device(self, grpc_stub, bioimageio_model_bytes):
         device_by_id = self._query_devices(grpc_stub)
         assert "cpu" in device_by_id
         assert inference_pb2.Device.Status.AVAILABLE == device_by_id["cpu"].status
 
-        model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
+        grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
 
         device_by_id = self._query_devices(grpc_stub)
         assert "cpu" in device_by_id
         assert inference_pb2.Device.Status.IN_USE == device_by_id["cpu"].status
 
-        grpc_stub.CloseModelSession(model)
-
     def test_using_same_device_fails(self, grpc_stub, bioimageio_model_bytes):
-        model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
+        grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
         with pytest.raises(grpc.RpcError):
-            model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
-
-        grpc_stub.CloseModelSession(model)
+            grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
 
     def test_closing_session_releases_devices(self, grpc_stub, bioimageio_model_bytes):
         model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
@@ -163,8 +159,6 @@ def test_call_predict_valid_explicit(self, grpc_stub, bioimageio_dummy_explicit_
         input_tensors = [converters.xarray_to_pb_tensor(input_tensor_id, arr)]
         res = grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
 
-        grpc_stub.CloseModelSession(model)
-
         assert len(res.tensors) == 1
         assert res.tensors[0].tensorId == output_tensor_id
         assert_array_equal(expected, converters.pb_tensor_to_numpy(res.tensors[0]))
@@ -175,7 +169,6 @@ def test_call_predict_invalid_shape_explicit(self, grpc_stub, bioimageio_dummy_e
         input_tensors = [converters.xarray_to_pb_tensor("input", arr)]
         with pytest.raises(grpc.RpcError):
             grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
-        grpc_stub.CloseModelSession(model)
 
     @pytest.mark.parametrize(
         "shape",
@@ -187,7 +180,6 @@ def test_call_predict_invalid_shape_parameterized(self, grpc_stub, shape, bioima
         input_tensors = [converters.xarray_to_pb_tensor("param", arr)]
         with pytest.raises(grpc.RpcError):
             grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
-        grpc_stub.CloseModelSession(model)
 
     def test_call_predict_invalid_tensor_ids(self, grpc_stub, bioimageio_dummy_model):
         model_bytes, _ = bioimageio_dummy_model
@@ -197,7 +189,6 @@ def test_call_predict_invalid_tensor_ids(self, grpc_stub, bioimageio_dummy_model
         with pytest.raises(grpc.RpcError) as error:
             grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
         assert error.value.details().startswith("Exception calling application: Spec invalidTensorName doesn't exist")
-        grpc_stub.CloseModelSession(model)
 
     def test_call_predict_invalid_axes(self, grpc_stub, bioimageio_dummy_model):
         model_bytes, tensor_id = bioimageio_dummy_model
@@ -207,15 +198,13 @@ def test_call_predict_invalid_axes(self, grpc_stub, bioimageio_dummy_model):
         with pytest.raises(grpc.RpcError) as error:
             grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
         assert error.value.details().startswith("Exception calling application: Incompatible axes")
-        grpc_stub.CloseModelSession(model)
 
     @pytest.mark.parametrize("shape", [(1, 1, 64, 64), (1, 1, 66, 65), (1, 1, 68, 66), (1, 1, 70, 67)])
     def test_call_predict_valid_shape_parameterized(self, grpc_stub, shape, bioimageio_dummy_param_model_bytes):
         model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_dummy_param_model_bytes))
         arr = xr.DataArray(np.arange(np.prod(shape)).reshape(*shape), dims=("b", "c", "x", "y"))
         input_tensors = [converters.xarray_to_pb_tensor("param", arr)]
         grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
-        grpc_stub.CloseModelSession(model)
 
     @pytest.mark.skip
     def test_call_predict_tf(self, grpc_stub, bioimageio_dummy_tensorflow_model_bytes):
@@ -227,8 +216,6 @@ def test_call_predict_tf(self, grpc_stub, bioimageio_dummy_tensorflow_model_byte
         input_tensors = [converters.xarray_to_pb_tensor(input_tensor_id, arr)]
         res = grpc_stub.Predict(inference_pb2.PredictRequest(modelSessionId=model.id, tensors=input_tensors))
 
-        grpc_stub.CloseModelSession(model)
-
         assert len(res.tensors) == 1
         assert res.tensors[0].tensorId == output_tensor_id
         assert_array_equal(expected, converters.pb_tensor_to_numpy(res.tensors[0]))

tiktorch/rpc/mp.py

@@ -270,7 +270,8 @@ def __init__(self, api, conn: Connection):
         self._logger = None
         self._conn = conn
         self._results_queue = queue.Queue()
-        self._start_result_sender(conn)
+        self._start_result_sender = threading.Thread(target=self._sender, name="MPResultSender")
+        self._start_result_sender.start()
 
     @property
     def logger(self):
@@ -281,20 +282,17 @@ def logger(self):
     def _send(self, msg):
         self._results_queue.put(msg)
 
-    def _start_result_sender(self, conn):
-        def _sender():
-            while True:
-                try:
-                    result = self._results_queue.get()
-                    if result is self._sentinel:
-                        break
-
-                    conn.send(result)
-                except Exception:
-                    self.logger.exception("Error in result sender")
+    def _sender(self):
+        while True:
+            try:
+                result = self._results_queue.get()
+                if result is self._sentinel:
+                    self.logger.debug("[MPServer] result sender thread stopped")
+                    break
 
-        t = threading.Thread(target=_sender, name="MPResultSender")
-        t.start()
+                self._conn.send(result)
+            except Exception:
+                self.logger.exception("Error in result sender")
 
     def _send_result(self, fut):
         if fut.cancelled():
@@ -317,7 +315,7 @@ def _make_future(self):
         return f
 
     def _call_method(self, call: MethodCall):
-        self.logger.debug("[id: %s] Recieved '%s' method call", call.id, call.method_name)
+        self.logger.debug("[id: %s] Received '%s' method call", call.id, call.method_name)
         fut = self._make_future()
         self._futures.put(call.id, fut)
 
@@ -341,7 +339,7 @@ def _call_method(self, call: MethodCall):
         return fut
 
     def _cancel_request(self, cancel: Cancellation):
-        self.logger.debug("[id: %s] Recieved cancel request", cancel.id)
+        self.logger.debug("[id: %s] Received cancel request", cancel.id)
         fut = self._futures.pop_id(cancel.id)
         if fut:
             fut.cancel()
@@ -373,3 +371,7 @@ def listen(self):
                 break
             except Exception:
                 self.logger.error("Error in main loop", exc_info=1)
+
+        self._start_result_sender.join()
+        self._conn.close()
+        self.logger.debug("Closing connection")