pybio -> bioimageio

.circleci/config.yml

@@ -135,8 +135,8 @@ jobs:
             . /opt/conda/etc/profile.d/conda.sh
             conda activate tiktorch-server-env
             ./scripts/conda_build.sh conda-recipe-client
-            ./scripts/conda_build.sh pybio-core-recipe
-            ./scripts/conda_build.sh pybio-torch-recipe
+            ./scripts/conda_build.sh bioimageio-core-recipe
+            ./scripts/conda_build.sh bioimageio-torch-recipe
             ./scripts/conda_build.sh conda-recipe
             ./scripts/conda_build.sh conda-recipe-cpu
 

pybio-core-recipe/meta.yaml

@@ -28,14 +28,14 @@ requirements:
 
 test:
   imports:
-    - pybio.spec
+    - bioimageio.spec
 
 about:
   home: https://github.com/bioimage-io/python-bioimage-io
   license: MIT
   license_family: MIT
   license_file: LICENSE
-  summary: 'Tools for parsing pybio model specification'
+  summary: 'Tools for parsing bioimageio model specification'
 
   doc_url: https://github.com/bioimage-io/python-bioimage-io
   dev_url: https://github.com/bioimage-io/python-bioimage-io

pybio-torch-recipe/meta.yaml

@@ -27,15 +27,15 @@ requirements:
 
 test:
   imports:
-    - pybio.torch
-    - pybio.torch.training
+    - bioimageio.torch
+    - bioimageio.torch.training
 
 about:
   home: https://github.com/bioimage-io/pytorch-bioimage-io
   license: MIT
   license_family: MIT
   license_file: LICENSE
-  summary: 'Pytorch related components of pybio'
+  summary: 'Pytorch related components of bioimageio'
 
   doc_url: https://github.com/bioimage-io/pytorch-bioimage-io
   dev_url: https://github.com/bioimage-io/pytorch-bioimage-io

setup.py

@@ -30,8 +30,8 @@
         "numpy",
         "pyyaml",
         "torch",
-        "pybio.core @ git+ssh://[email protected]/bioimage-io/python-bioimage-io#egg=pybio.core",
-        "pybio.torch @ git+ssh://[email protected]/bioimage-io/pytorch-bioimage-io#egg=pybio.torch",
+        "bioimageio.core @ git+ssh://[email protected]/bioimage-io/python-bioimage-io#egg=bioimageio.core",
+        "bioimageio.torch @ git+ssh://[email protected]/bioimage-io/pytorch-bioimage-io#egg=bioimageio.torch",
     ],
     entry_points={"console_scripts": ["tiktorch=tiktorch.server.base:main"]},
     # extras_require={"test": ["pytest"]},

tests/conftest.py

@@ -15,11 +15,11 @@
 import pytest
 
 TEST_DATA = "data"
-TEST_PYBIO_ZIPFOLDER = "unet2d"
-TEST_PYBIO_ONNX = "unet2d_onnx"
-TEST_PYBIO_DUMMY = "dummy"
-TEST_PYBIO_TENSORFLOW_DUMMY = "dummy_tensorflow"
-TEST_PYBIO_TORCHSCRIPT = "unet2d_torchscript"
+TEST_BIOIMAGEIO_ZIPFOLDER = "unet2d"
+TEST_BIOIMAGEIO_ONNX = "unet2d_onnx"
+TEST_BIOIMAGEIO_DUMMY = "dummy"
+TEST_BIOIMAGEIO_TENSORFLOW_DUMMY = "dummy_tensorflow"
+TEST_BIOIMAGEIO_TORCHSCRIPT = "unet2d_torchscript"
 
 NNModel = namedtuple("NNModel", ["model", "state"])
 
@@ -82,8 +82,8 @@ def assert_threads_cleanup():
 
 
 @pytest.fixture
-def pybio_model_bytes(data_path):
-    zip_folder = data_path / TEST_PYBIO_ZIPFOLDER
+def bioimageio_model_bytes(data_path):
+    zip_folder = data_path / TEST_BIOIMAGEIO_ZIPFOLDER
     data = io.BytesIO()
     with ZipFile(data, mode="w") as zip_model:
         for f_path in zip_folder.iterdir():
@@ -97,18 +97,18 @@ def pybio_model_bytes(data_path):
 
 
 @pytest.fixture
-def pybio_model_zipfile(pybio_model_bytes):
-    with ZipFile(pybio_model_bytes, mode="r") as zf:
+def bioimageio_model_zipfile(bioimageio_model_bytes):
+    with ZipFile(bioimageio_model_bytes, mode="r") as zf:
         yield zf
 
 
 @pytest.fixture
-def pybio_dummy_model_filepath(data_path, tmpdir):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_DUMMY
+def bioimageio_dummy_model_filepath(data_path, tmpdir):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_DUMMY
     path = tmpdir / "dummy_model.zip"
 
     with ZipFile(path, mode="w") as zip_model:
-        for f_path in pybio_net_dir.iterdir():
+        for f_path in bioimageio_net_dir.iterdir():
             if str(f_path.name).startswith("__"):
                 continue
 
@@ -119,11 +119,11 @@ def pybio_dummy_model_filepath(data_path, tmpdir):
 
 
 @pytest.fixture
-def pybio_dummy_model_bytes(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_DUMMY
+def bioimageio_dummy_model_bytes(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_DUMMY
     data = io.BytesIO()
     with ZipFile(data, mode="w") as zip_model:
-        for f_path in pybio_net_dir.iterdir():
+        for f_path in bioimageio_net_dir.iterdir():
             if str(f_path.name).startswith("__"):
                 continue
 
@@ -156,22 +156,22 @@ def _archive(path_to_archive):
 
 
 @pytest.fixture
-def pybio_dummy_tensorflow_model_bytes(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_TENSORFLOW_DUMMY
-    return archive(pybio_net_dir)
+def bioimageio_dummy_tensorflow_model_bytes(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_TENSORFLOW_DUMMY
+    return archive(bioimageio_net_dir)
 
 
 @pytest.fixture
-def pybio_unet2d_onnx_bytes(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_ONNX
-    return archive(pybio_net_dir)
+def bioimageio_unet2d_onnx_bytes(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_ONNX
+    return archive(bioimageio_net_dir)
 
 
 @pytest.fixture
-def pybio_unet2d_onnx_test_data(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_ONNX
-    test_input = pybio_net_dir / "test_input.npy"
-    test_output = pybio_net_dir / "test_output.npy"
+def bioimageio_unet2d_onnx_test_data(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_ONNX
+    test_input = bioimageio_net_dir / "test_input.npy"
+    test_output = bioimageio_net_dir / "test_output.npy"
     return {"test_input": test_input, "test_output": test_output}
 
 
@@ -184,19 +184,14 @@ def npy_zeros_file(tmpdir):
 
 
 @pytest.fixture
-def pybio_unet2d_torchscript_bytes(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_TORCHSCRIPT
-    return archive(pybio_net_dir)
+def bioimageio_unet2d_torchscript_bytes(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_TORCHSCRIPT
+    return archive(bioimageio_net_dir)
 
 
 @pytest.fixture
-def pybio_unet2d_torchscript_test_data(data_path):
-    pybio_net_dir = Path(data_path) / TEST_PYBIO_TORCHSCRIPT
-    test_input = pybio_net_dir / "test_input.npy"
-    test_output = pybio_net_dir / "test_output.npy"
+def bioimageio_unet2d_torchscript_test_data(data_path):
+    bioimageio_net_dir = Path(data_path) / TEST_BIOIMAGEIO_TORCHSCRIPT
+    test_input = bioimageio_net_dir / "test_input.npy"
+    test_output = bioimageio_net_dir / "test_output.npy"
     return {"test_input": test_input, "test_output": test_output}
-
-
-@pytest.fixture
-def cache_path(tmp_path):
-    return Path(getenv("PYBIO_CACHE_PATH", tmp_path))

tests/data/unet2d_onnx/UNet2DNucleiBroad.model.yaml

@@ -57,7 +57,7 @@ outputs:
 
 language: python
 framework: pytorch
-source: pybio.torch.models.unet2d.UNet2d
+source: bioimageio.torch.models.unet2d.UNet2d
 kwargs: {input_channels: 1, output_channels: 1}
 dependencies: conda:../environment.yaml
 

tests/data/unet2d_torchscript/UNet2DNucleiBroad.model.yaml

@@ -50,7 +50,7 @@ outputs:
 
 language: python
 framework: pytorch
-source: pybio.torch.models.unet2d.UNet2d
+source: bioimageio.torch.models.unet2d.UNet2d
 kwargs: {input_channels: 1, output_channels: 1}
 dependencies: conda:../environment.yaml
 

tests/test_server/test_grpc/test_inference_servicer.py

@@ -44,13 +44,13 @@ def method_requiring_session(self, request, grpc_stub):
         method_name, req = request.param
         return getattr(grpc_stub, method_name), req
 
-    def test_model_session_creation(self, grpc_stub, pybio_model_bytes):
-        model = grpc_stub.CreateModelSession(valid_model_request(pybio_model_bytes))
+    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, pybio_dummy_model_bytes):
-        id_ = data_store.put(pybio_dummy_model_bytes.getvalue())
+    def test_model_session_creation_using_upload_id(self, grpc_stub, data_store, bioimageio_dummy_model_bytes):
+        id_ = data_store.put(bioimageio_dummy_model_bytes.getvalue())
 
         rq = inference_pb2.CreateModelSessionRequest(model_uri=f"upload://{id_}", deviceIds=["cpu"])
         model = grpc_stub.CreateModelSession(rq)
@@ -103,28 +103,28 @@ def test_if_model_create_fails_devices_are_released(self, grpc_stub):
         if model:
             grpc_stub.CloseModelSession(model)
 
-    def test_use_device(self, grpc_stub, pybio_model_bytes):
+    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(pybio_model_bytes, device_ids=["cpu"]))
+        model = 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, pybio_model_bytes):
-        model = grpc_stub.CreateModelSession(valid_model_request(pybio_model_bytes, device_ids=["cpu"]))
+    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"]))
         with pytest.raises(grpc.RpcError):
-            model = grpc_stub.CreateModelSession(valid_model_request(pybio_model_bytes, device_ids=["cpu"]))
+            model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes, device_ids=["cpu"]))
 
         grpc_stub.CloseModelSession(model)
 
-    def test_closing_session_releases_devices(self, grpc_stub, pybio_model_bytes):
-        model = grpc_stub.CreateModelSession(valid_model_request(pybio_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"]))
 
         device_by_id = self._query_devices(grpc_stub)
         assert "cpu" in device_by_id
@@ -138,8 +138,8 @@ def test_closing_session_releases_devices(self, grpc_stub, pybio_model_bytes):
 
 
 class TestGetLogs:
-    def test_returns_ack_message(self, pybio_model_bytes, grpc_stub):
-        model = grpc_stub.CreateModelSession(valid_model_request(pybio_model_bytes))
+    def test_returns_ack_message(self, bioimageio_model_bytes, grpc_stub):
+        model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_model_bytes))
         resp = grpc_stub.GetLogs(inference_pb2.Empty())
         record = next(resp)
         assert inference_pb2.LogEntry.Level.INFO == record.level
@@ -154,8 +154,8 @@ def test_call_fails_with_unknown_model_session_id(self, grpc_stub):
         assert grpc.StatusCode.FAILED_PRECONDITION == e.value.code()
         assert "model-session with id myid1 doesn't exist" in e.value.details()
 
-    def test_call_predict(self, grpc_stub, pybio_dummy_model_bytes):
-        model = grpc_stub.CreateModelSession(valid_model_request(pybio_dummy_model_bytes))
+    def test_call_predict(self, grpc_stub, bioimageio_dummy_model_bytes):
+        model = grpc_stub.CreateModelSession(valid_model_request(bioimageio_dummy_model_bytes))
 
         arr = xr.DataArray(np.arange(32 * 32).reshape(1, 32, 32), dims=("c", "x", "y"))
         expected = arr + 1

tests/test_server/test_predict.py

@@ -19,13 +19,13 @@ def npy_zeros_file(tmpdir):
     return path
 
 
-def test_running_predict_with_valid_arguments(testdir, pybio_dummy_model_filepath, npy_zeros_file, output_path):
+def test_running_predict_with_valid_arguments(testdir, bioimageio_dummy_model_filepath, npy_zeros_file, output_path):
     result = testdir.run(
         "python",
         "-m",
         "tiktorch.server.predict",
         "--model",
-        pybio_dummy_model_filepath,
+        bioimageio_dummy_model_filepath,
         npy_zeros_file,
         "--output",
         output_path,
@@ -41,20 +41,20 @@ def test_running_predict_fails_when_model_unspecified(testdir, npy_zeros_file, o
     assert result.ret != 0
 
 
-def test_running_predict_fails_when_no_images_specified(testdir, pybio_dummy_model_filepath, output_path):
+def test_running_predict_fails_when_no_images_specified(testdir, bioimageio_dummy_model_filepath, output_path):
     result = testdir.run(
-        "python", "-m", "tiktorch.server.predict", "--model", pybio_dummy_model_filepath, "--output", output_path
+        "python", "-m", "tiktorch.server.predict", "--model", bioimageio_dummy_model_filepath, "--output", output_path
     )
     assert result.ret != 0
 
 
-def test_running_predict_fails_when_invalid_image_specified(testdir, pybio_dummy_model_filepath, output_path):
+def test_running_predict_fails_when_invalid_image_specified(testdir, bioimageio_dummy_model_filepath, output_path):
     result = testdir.run(
         "python",
         "-m",
         "tiktorch.server.predict",
         "--model",
-        pybio_dummy_model_filepath,
+        bioimageio_dummy_model_filepath,
         "nonexisting",
         "--output",
         output_path,
@@ -77,9 +77,9 @@ def test_running_predict_fails_without_when_model_file_does_not_exist(testdir, t
 
 
 def test_running_predict_failes_when_output_is_unspecified(
-    testdir, pybio_dummy_model_filepath, npy_zeros_file, output_path
+    testdir, bioimageio_dummy_model_filepath, npy_zeros_file, output_path
 ):
     result = testdir.run(
-        "python", "-m", "tiktorch.server.predict", "--model", pybio_dummy_model_filepath, npy_zeros_file
+        "python", "-m", "tiktorch.server.predict", "--model", bioimageio_dummy_model_filepath, npy_zeros_file
     )
     assert result.ret != 0

tests/test_server/test_prediction_pipeline/test_prediction_pipeline.py

@@ -7,31 +7,33 @@
 from tiktorch.server.reader import eval_model_zip
 
 
-def test_eval_onnx_model_zip_predict(pybio_unet2d_onnx_bytes, pybio_unet2d_onnx_test_data, cache_path):
-    with ZipFile(pybio_unet2d_onnx_bytes) as zf:
+def test_eval_onnx_model_zip_predict(bioimageio_unet2d_onnx_bytes, bioimageio_unet2d_onnx_test_data):
+    with ZipFile(bioimageio_unet2d_onnx_bytes) as zf:
         adapter = eval_model_zip(zf, devices=["cpu"], preserve_batch_dim=True)
-        test_input = xarray.DataArray(np.load(pybio_unet2d_onnx_test_data["test_input"]), dims=("b", "c", "x", "y"))
+        test_input = xarray.DataArray(
+            np.load(bioimageio_unet2d_onnx_test_data["test_input"]), dims=("b", "c", "x", "y")
+        )
         # TODO: Figure out why test output doesn't match result
         adapter.forward(test_input)
 
 
 def test_eval_torchscript_model_zip_predict(
-    pybio_unet2d_torchscript_bytes, pybio_unet2d_torchscript_test_data, cache_path
+    bioimageio_unet2d_torchscript_bytes, bioimageio_unet2d_torchscript_test_data
 ):
-    with ZipFile(pybio_unet2d_torchscript_bytes) as zf:
+    with ZipFile(bioimageio_unet2d_torchscript_bytes) as zf:
         pipeline = eval_model_zip(zf, devices=["cpu"], preserve_batch_dim=True)
         test_input = xarray.DataArray(
-            np.load(pybio_unet2d_torchscript_test_data["test_input"]).astype(np.float32), dims=("b", "c", "x", "y")
+            np.load(bioimageio_unet2d_torchscript_test_data["test_input"]).astype(np.float32), dims=("b", "c", "x", "y")
         )
-        test_output = np.load(pybio_unet2d_torchscript_test_data["test_output"])
+        test_output = np.load(bioimageio_unet2d_torchscript_test_data["test_output"])
         result = pipeline.forward(test_input)
         assert_array_almost_equal(result.data, test_output, decimal=4)
 
 
 def test_eval_model_zip_metadata_no_batch_dim(
-    pybio_unet2d_torchscript_bytes, pybio_unet2d_torchscript_test_data, cache_path
+    bioimageio_unet2d_torchscript_bytes, bioimageio_unet2d_torchscript_test_data
 ):
-    with ZipFile(pybio_unet2d_torchscript_bytes) as zf:
+    with ZipFile(bioimageio_unet2d_torchscript_bytes) as zf:
         pipeline = eval_model_zip(zf, devices=["cpu"], preserve_batch_dim=False)
         assert pipeline.name == "UNet 2D Nuclei Broad"
         assert pipeline.input_axes == "cyx"
@@ -40,8 +42,8 @@ def test_eval_model_zip_metadata_no_batch_dim(
         assert pipeline.halo == [("c", 0), ("y", 32), ("x", 32)]
 
 
-def test_eval_model_zip(pybio_model_bytes, cache_path):
-    with ZipFile(pybio_model_bytes) as zf:
+def test_eval_model_zip(bioimageio_model_bytes):
+    with ZipFile(bioimageio_model_bytes) as zf:
         pipeline = eval_model_zip(zf, devices=["cpu"], preserve_batch_dim=True)
 
     assert pipeline.input_axes == "bcyx"
@@ -51,9 +53,9 @@ def test_eval_model_zip(pybio_model_bytes, cache_path):
 
 
 def test_eval_model_zip_metadata_with_batch_dim(
-    pybio_unet2d_torchscript_bytes, pybio_unet2d_torchscript_test_data, cache_path
+    bioimageio_unet2d_torchscript_bytes, bioimageio_unet2d_torchscript_test_data
 ):
-    with ZipFile(pybio_unet2d_torchscript_bytes) as zf:
+    with ZipFile(bioimageio_unet2d_torchscript_bytes) as zf:
         pipeline = eval_model_zip(zf, devices=["cpu"], preserve_batch_dim=True)
         assert pipeline.input_axes == "bcyx"
         assert pipeline.output_axes == "bcyx"