Quick Cleanup

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 1.0.0
+current_version = 1.0.1
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\.(?P<release>[a-z]+)(?P<build>\d+))?

docs/conf.py

@@ -1,7 +1,7 @@
 project = 'redisai-py'
 copyright = '2020, RedisLabs'
 author = 'RedisLabs'
-release = '1.0.0'
+release = '1.0.1'
 extensions = ['sphinx.ext.autodoc',
               'sphinx.ext.autosummary',
               'sphinx.ext.extlinks',

redisai/__init__.py

@@ -1,3 +1,3 @@
 from .client import Client
 
-__version__ = '1.0.0'
+__version__ = '1.0.1'

redisai/client.py

@@ -62,8 +62,8 @@ def tensorget(self,
         self.commands.extend(args)
         self.commands.append("|>")
         self.result_processors.append(partial(utils.tensorget_postprocessor,
-                                              as_numpy,
-                                              meta_only))
+                                              as_numpy=as_numpy,
+                                              meta_only=meta_only))
         return self
 
     def modelrun(self,
@@ -407,7 +407,7 @@ def tensorget(self,
         """
         args = builder.tensorget(key, as_numpy, meta_only)
         res = self.execute_command(*args)
-        return utils.tensorget_postprocessor(as_numpy, meta_only, res)
+        return utils.tensorget_postprocessor(res, as_numpy, meta_only)
 
     def scriptset(self, key: AnyStr, device: str, script: str, tag: AnyStr = None) -> str:
         """

redisai/command_builder.py

@@ -15,6 +15,10 @@ def modelset(self, name: AnyStr, backend: str, device: str, data: ByteString,
                  batch: int, minbatch: int, tag: AnyStr,
                  inputs: Union[AnyStr, List[AnyStr]],
                  outputs: Union[AnyStr, List[AnyStr]]) -> Sequence:
+        if device.upper() not in utils.allowed_devices:
+            raise ValueError(f"Device not allowed. Use any from {utils.allowed_devices}")
+        if backend.upper() not in utils.allowed_backends:
+            raise ValueError(f"Backend not allowed. Use any from {utils.allowed_backends}")
         args = ['AI.MODELSET', name, backend, device]
 
         if batch is not None:
@@ -87,6 +91,8 @@ def tensorget(self,
         return args
 
     def scriptset(self, name: AnyStr, device: str, script: str, tag: AnyStr = None) -> Sequence:
+        if device.upper() not in utils.allowed_devices:
+            raise ValueError(f"Device not allowed. Use any from {utils.allowed_devices}")
         args = ['AI.SCRIPTSET', name, device]
         if tag:
             args += ['TAG', tag]

redisai/utils.py

@@ -16,9 +16,12 @@
     'uint32': 'UINT32',
     'uint64': 'UINT64'}
 
+allowed_devices = {'CPU', 'GPU'}
+allowed_backends = {'TF', 'TFLITE', 'TORCH', 'ONNX'}
+
 
 def numpy2blob(tensor: np.ndarray) -> tuple:
-    """ Convert the numpy input from user to `Tensor` """
+    """Convert the numpy input from user to `Tensor`."""
     try:
         dtype = dtype_dict[str(tensor.dtype)]
     except KeyError:
@@ -29,7 +32,7 @@ def numpy2blob(tensor: np.ndarray) -> tuple:
 
 
 def blob2numpy(value: ByteString, shape: Union[list, tuple], dtype: str) -> np.ndarray:
-    """ Convert `BLOB` result from RedisAI to `np.ndarray` """
+    """Convert `BLOB` result from RedisAI to `np.ndarray`."""
     mm = {
         'FLOAT': 'float32',
         'DOUBLE': 'float64'
@@ -40,6 +43,7 @@ def blob2numpy(value: ByteString, shape: Union[list, tuple], dtype: str) -> np.n
 
 
 def list2dict(lst):
+    """Convert the list from RedisAI to a dict."""
     if len(lst) % 2 != 0:
         raise RuntimeError("Can't unpack the list: {}".format(lst))
     out = {}
@@ -55,10 +59,8 @@ def list2dict(lst):
 def recursive_bytetransform(arr: List[AnyStr], target: Callable) -> list:
     """
     Recurse value, replacing each element of b'' with the appropriate element.
-    Function returns the same array after inplace operation which updates `arr`
 
-    :param target: Type of tensor | array
-    :param arr: The array with b'' numbers or recursive array of b''
+    Function returns the same array after inplace operation which updates `arr`
     """
     for ix in range(len(arr)):
         obj = arr[ix]
@@ -70,10 +72,16 @@ def recursive_bytetransform(arr: List[AnyStr], target: Callable) -> list:
 
 
 def listify(inp: Union[str, Sequence[str]]) -> Sequence[str]:
+    """Wrap the ``inp`` with a list if it's not a list already."""
     return (inp,) if not isinstance(inp, (list, tuple)) else inp
 
 
-def tensorget_postprocessor(as_numpy, meta_only, rai_result):
+def tensorget_postprocessor(rai_result, as_numpy, meta_only):
+    """Process the tensorget output.
+
+    If ``as_numpy`` is True, it'll be converted to a numpy array. The required
+    information such as datatype and shape must be in ``rai_result`` itself.
+    """
     rai_result = list2dict(rai_result)
     if meta_only:
         return rai_result

setup.py

@@ -7,16 +7,16 @@
 
 setup(
     name='redisai',
-    version='1.0.0',
+    version='1.0.1',
     description='RedisAI Python Client',
     long_description=long_description,
-    long_description_content_type='text/markdown',
+    long_description_content_type='text/x-rst',
     url='http://github.com/RedisAI/redisai-py',
     author='RedisLabs',
     author_email='oss@redislabs.com',
     packages=find_packages(),
     install_requires=['redis', 'hiredis', 'numpy'],
-    python_requires='>=3.2',
+    python_requires='>=3.6',
     classifiers=[
         'Development Status :: 4 - Beta',
         'Intended Audience :: Developers',
@@ -26,7 +26,6 @@
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',
-        'Topic :: Database',
-        'Topic :: Software Development :: Testing'
+        'Topic :: Database'
     ]
 )

test/test.py

@@ -106,6 +106,18 @@ def test_numpy_tensor(self):
         with self.assertRaises(TypeError):
             con.tensorset('trying', stringarr)
 
+    def test_modelset_errors(self):
+        model_path = os.path.join(MODEL_DIR, 'graph.pb')
+        model_pb = load_model(model_path)
+        con = self.get_client()
+        with self.assertRaises(ValueError):
+            con.modelset('m', 'tf', 'wrongdevice', model_pb,
+                         inputs=['a', 'b'], outputs=['mul'], tag='v1.0')
+        with self.assertRaises(ValueError):
+            con.modelset('m', 'wrongbackend', 'cpu', model_pb,
+                         inputs=['a', 'b'], outputs=['mul'], tag='v1.0')
+
+
     def test_modelget_meta(self):
         model_path = os.path.join(MODEL_DIR, 'graph.pb')
         model_pb = load_model(model_path)