update target_ios flag to minimum_ios_deployment_target (#512)

Author: bhushan23

README.md

@@ -17,15 +17,15 @@ pip install onnx-coreml==1.0
 ```
 
 Since 1.0 beta 3, the flag `disable_coreml_rank5_mapping` (which was part of beta 2) has been removed and instead replaced by
-the generic argument `target_ios` which can be used to target different versions of Core ML/iOS.
-The argument `target_ios` takes a string specifying the target deployment iOS version e.g. '11.2', '12' and '13'.
+the generic argument `minimum_ios_deployment_target` which can be used to target different versions of Core ML/iOS.
+The argument `minimum_ios_deployment_target` takes a string specifying the target deployment iOS version e.g. '11.2', '12' and '13'.
 By default, the converter uses the value of '12'.
 
 For example:
 
 ```python
 from onnx_coreml import convert
-ml_model = convert(model='my_model.onnx', target_ios='13')  # to use Core ML 3
+ml_model = convert(model='my_model.onnx', minimum_ios_deployment_target='13')  # to use Core ML 3
 ```
 
 ## Installation
@@ -82,7 +82,7 @@ def convert(model,
             predicted_feature_name='classLabel',
             add_custom_layers=False,
             custom_conversion_functions={},
-            target_ios='12')
+            minimum_ios_deployment_target='12')
 ```
 
 The function returns a Core ML model instance that can be saved to a `.mlmodel` file, e.g.:
@@ -162,17 +162,17 @@ __custom_conversion_fuctions__: dict (str: function)
 
 __onnx_coreml_input_shape_map__: dict (str: List[int])
     (Optional)
-    (only used if `target_ios` version is less than '13')
+    (only used if `minimum_ios_deployment_target` version is less than '13')
     A dictionary with keys corresponding to the model input names. Values are a list of integers that specify
     how the shape of the input is mapped to Core ML. Convention used for Core ML shapes is:
     0: Sequence, 1: Batch, 2: channel, 3: height, 4: width.
     For example, an input of rank 2 could be mapped as [3,4] (i.e. H,W) or [1,2] (i.e. B,C) etc.
 
-__target_ios__: str
+__minimum_ios_deployment_target__: str
       Target Deployment iOS version (default: '12')
       Supported values: '11.2', '12', '13'
       Core ML model produced by the converter will be compatible with the iOS version specified in this argument.
-      e.g. if `target_ios` = '12', the converter would only utilize Core ML features released till iOS12
+      e.g. if `minimum_ios_deployment_target` = '12', the converter would only utilize Core ML features released till iOS12
       (equivalently macOS 10.14, watchOS 5 etc).
       Release notes:
       * iOS 11 / Core ML 1: https://github.com/apple/coremltools/releases/tag/v0.8

examples/BERT.ipynb

@@ -1091,7 +1091,7 @@
    ],
    "source": [
     "# Step 2 - Convert from ONNX to CoreML MLModel\n",
-    "mlmodel = convert(model=onnx_model_path, target_ios=\"13\", )\n",
+    "mlmodel = convert(model=onnx_model_path, minimum_ios_deployment_target=\"13\", )\n",
     "mlmodel.save(mlmodel_path)"
    ]
   },
@@ -3139,7 +3139,7 @@
    ],
    "source": [
     "# ONNX to CoreML MLModel\n",
-    "mlmodel = convert(model=onnx_model_path, target_ios=\"13\")\n",
+    "mlmodel = convert(model=onnx_model_path, minimum_ios_deployment_target=\"13\")\n",
     "mlmodel.save(mlmodel_path)"
    ]
   },

examples/README.md

@@ -43,7 +43,7 @@ Converting PyTorch model into CoreML model is a two step process
 2. ONNX to CoreML
     ```
       # Step 2 - ONNX to CoreML model
-      mlmodel = convert(model='./small_model.onnx', target_ios='13')
+      mlmodel = convert(model='./small_model.onnx', minimum_ios_deployment_target='13')
       # Save converted CoreML model
       mlmodel.save('small_model.mlmodel')
     ```

examples/small_example.py

@@ -23,6 +23,6 @@ def forward(self, x):
 torch.onnx.export(model, dummy_input, './small_model.onnx')
 
 # Step 2 - ONNX to CoreML model
-mlmodel = convert(model='./small_model.onnx', target_ios='13')
+mlmodel = convert(model='./small_model.onnx', minimum_ios_deployment_target='13')
 # Save converted CoreML model
 mlmodel.save('small_model.mlmodel')

onnx_coreml/_backend.py

@@ -36,7 +36,7 @@ class CoreMLBackend(Backend):
     def prepare(cls,
                 model,  # type: ModelProto
                 device='CPU',  # type: Text
-                target_ios='12', # type: str
+                minimum_ios_deployment_target='12', # type: str
                 **kwargs  # type: Any
                 ):
         # type: (...) -> CoreMLRep
@@ -45,11 +45,11 @@ def prepare(cls,
             with open('/tmp/node_model.onnx', 'wb') as f:
                 s = model.SerializeToString()
                 f.write(s)
-        coreml_model = convert(model, target_ios=target_ios)
+        coreml_model = convert(model, minimum_ios_deployment_target=minimum_ios_deployment_target)
         if DEBUG:
             coreml_model.save('/tmp/node_model.mlmodel')
         onnx_outputs_info = _get_onnx_outputs_info(model)
-        return CoreMLRep(coreml_model, onnx_outputs_info, device == 'CPU', target_ios=target_ios)
+        return CoreMLRep(coreml_model, onnx_outputs_info, device == 'CPU', minimum_ios_deployment_target=minimum_ios_deployment_target)
 
     @classmethod
     def is_compatible(cls,
@@ -114,7 +114,7 @@ class CoreMLBackendND(Backend):
     def prepare(cls,
                 model,  # type: ModelProto
                 device='CPU',  # type: Text
-                target_ios='13', # type: str
+                minimum_ios_deployment_target='13', # type: str
                 **kwargs  # type: Any
                 ):
         # type: (...) -> CoreMLRep
@@ -123,11 +123,11 @@ def prepare(cls,
             with open('/tmp/node_model.onnx', 'wb') as f:
                 s = model.SerializeToString()
                 f.write(s)
-        coreml_model = convert(model, target_ios=target_ios)
+        coreml_model = convert(model, minimum_ios_deployment_target=minimum_ios_deployment_target)
         if DEBUG:
             coreml_model.save('/tmp/node_model.mlmodel')
         onnx_outputs_info = _get_onnx_outputs_info(model)
-        return CoreMLRep(coreml_model, onnx_outputs_info, device == 'CPU', target_ios=target_ios)
+        return CoreMLRep(coreml_model, onnx_outputs_info, device == 'CPU', minimum_ios_deployment_target=minimum_ios_deployment_target)
 
     @classmethod
     def is_compatible(cls,

onnx_coreml/_backend_rep.py

@@ -35,13 +35,13 @@ def __init__(self,
                  coreml_model,  # type: MLModel
                  onnx_outputs_info,  # type: Dict[Text, EdgeInfo]
                  useCPUOnly=False,  # type: bool
-                 target_ios='12' # type: str
+                 minimum_ios_deployment_target='12' # type: str
                  ):
         # type: (...) -> None
         super(CoreMLRep, self).__init__()
         self.model = coreml_model
         self.useCPUOnly = useCPUOnly
-        self.target_ios = target_ios
+        self.minimum_ios_deployment_target = minimum_ios_deployment_target
 
         spec = coreml_model.get_spec()
         self.input_names = [str(i.name) for i in spec.description.input]
@@ -56,7 +56,7 @@ def run(self,
         super(CoreMLRep, self).run(inputs, **kwargs)
         inputs_ = inputs
         _reshaped = False
-        if not SupportedVersion.is_nd_array_supported(self.target_ios):
+        if not SupportedVersion.is_nd_array_supported(self.minimum_ios_deployment_target):
             for i, input_ in enumerate(inputs_):
                 shape = input_.shape
                 if len(shape) == 4 or len(shape) == 2:
@@ -80,7 +80,7 @@ def run(self,
         prediction = self.model.predict(input_dict, self.useCPUOnly)
         output_values = [prediction[name] for name in self.output_names]
 
-        if not SupportedVersion.is_nd_array_supported(self.target_ios):
+        if not SupportedVersion.is_nd_array_supported(self.minimum_ios_deployment_target):
             for i, output_ in enumerate(output_values):
                 shape = output_.shape
                 #reshape the CoreML output to match Onnx's output shape

onnx_coreml/_error_utils.py

@@ -21,7 +21,7 @@ def __init__(self,
       self.custom_conversion_functions = custom_conversion_functions
       self.custom_layer_nodes = custom_layer_nodes
 
-      self.rerun_suggestion = '\n Please try converting with higher target_ios.\n' \
+      self.rerun_suggestion = '\n Please try converting with higher minimum_ios_deployment_target.\n' \
                               'You can also provide custom function/layer to convert the model.'
 
 

onnx_coreml/converter.py

@@ -49,29 +49,29 @@ class SupportedVersion():
     ND_ARRARY_SUPPORT = IOS_13_VERSION
 
     @staticmethod
-    def ios_support_check(target_ios):
-        return target_ios in SupportedVersion.supported_ios_version
+    def ios_support_check(minimum_ios_deployment_target):
+        return minimum_ios_deployment_target in SupportedVersion.supported_ios_version
 
     @staticmethod
-    def is_nd_array_supported(target_ios):
-        if not SupportedVersion.ios_support_check(target_ios):
-            raise TypeError('{} not supported. Please provide one of target iOS: {}', target_ios, SupportedVersion.supported_ios_version)
+    def is_nd_array_supported(minimum_ios_deployment_target):
+        if not SupportedVersion.ios_support_check(minimum_ios_deployment_target):
+            raise TypeError('{} not supported. Please provide one of target iOS: {}', minimum_ios_deployment_target, SupportedVersion.supported_ios_version)
 
-        target_ios_index = SupportedVersion.supported_ios_version.index(target_ios)
-        return SupportedVersion.ND_ARRARY_SUPPORT <= target_ios_index
+        minimum_ios_deployment_target_index = SupportedVersion.supported_ios_version.index(minimum_ios_deployment_target)
+        return SupportedVersion.ND_ARRARY_SUPPORT <= minimum_ios_deployment_target_index
 
     @staticmethod
     def get_supported_ios():
         return SupportedVersion.supported_ios_version
 
     @staticmethod
-    def get_specification_version(target_ios):
-        if not SupportedVersion.ios_support_check(target_ios):
-            raise TypeError('{} not supported. Please provide one of target iOS: {}', target_ios, SupportedVersion.supported_ios_version)
+    def get_specification_version(minimum_ios_deployment_target):
+        if not SupportedVersion.ios_support_check(minimum_ios_deployment_target):
+            raise TypeError('{} not supported. Please provide one of target iOS: {}', minimum_ios_deployment_target, SupportedVersion.supported_ios_version)
 
-        if target_ios == '11.2':
+        if minimum_ios_deployment_target == '11.2':
             return IOS_11_2_SPEC_VERSION
-        elif target_ios == '12':
+        elif minimum_ios_deployment_target == '12':
             return IOS_12_SPEC_VERSION
         else:
             return IOS_13_SPEC_VERSION            
@@ -219,7 +219,7 @@ def _check_unsupported_ops(nodes, disable_coreml_rank5_mapping=False): # type: (
 
     coreml_3_rerun_message = ''
     if not disable_coreml_rank5_mapping:
-        coreml_3_rerun_message = '\nPlease try converting again with target_ios=13' \
+        coreml_3_rerun_message = '\nPlease try converting again with minimum_ios_deployment_target=13' \
                                  ' and coremltools 3.0 latest beta'
     if len(unsupported_op_types) > 0:
         raise NotImplementedError("Unsupported ONNX ops of type: %s %s" % (
@@ -385,7 +385,7 @@ def convert(model,  # type: Union[onnx.ModelProto, Text]
             add_custom_layers = False,  # type: bool
             custom_conversion_functions = {}, #type: Dict[Text, Any]
             onnx_coreml_input_shape_map = {}, # type: Dict[Text, List[int,...]]
-            target_ios = '12'):
+            minimum_ios_deployment_target = '12'):
     # type: (...) -> MLModel
     """
     Convert ONNX model to CoreML.
@@ -426,12 +426,12 @@ def convert(model,  # type: Union[onnx.ModelProto, Text]
         how the shape of the input is mapped to CoreML. Convention used for CoreML shapes is
         0: Sequence, 1: Batch, 2: channel, 3: height, 4: width.
         For example, an input of rank 2 could be mapped as [3,4] (i.e. H,W) or [1,2] (i.e. B,C) etc.
-        This is ignored if "target_ios" is set to 13.
-    target_ios: str
+        This is ignored if "minimum_ios_deployment_target" is set to 13.
+    minimum_ios_deployment_target: str
         Target Deployment iOS Version (default: '12')
         Supported iOS version options: '11.2', '12', '13'        
         CoreML model produced by the converter will be compatible with the iOS version specified in this argument.
-        e.g. if target_ios = '12', the converter would only utilize CoreML features released till iOS12 (equivalently macOS 10.14, watchOS 5 etc).
+        e.g. if minimum_ios_deployment_target = '12', the converter would only utilize CoreML features released till iOS12 (equivalently macOS 10.14, watchOS 5 etc).
 
         iOS 11.2 (CoreML 0.8) does not support resize_bilinear, crop_resize layers 
          - (Supported features: https://github.com/apple/coremltools/releases/tag/v0.8)
@@ -453,13 +453,13 @@ def convert(model,  # type: Union[onnx.ModelProto, Text]
             "Model must be file path to .onnx file or onnx loaded model"
         )
 
-    if not SupportedVersion.ios_support_check(target_ios):
-        raise TypeError('{} not supported. Please provide one of target iOS: {}', target_ios, SupportedVersion.get_supported_ios())
+    if not SupportedVersion.ios_support_check(minimum_ios_deployment_target):
+        raise TypeError('{} not supported. Please provide one of target iOS: {}', minimum_ios_deployment_target, SupportedVersion.get_supported_ios())
 
 
     global USE_SHAPE_MAPPING
     disable_coreml_rank5_mapping = False
-    if SupportedVersion.is_nd_array_supported(target_ios):
+    if SupportedVersion.is_nd_array_supported(minimum_ios_deployment_target):
         disable_coreml_rank5_mapping = True
 
     if disable_coreml_rank5_mapping:
@@ -551,7 +551,7 @@ def __call__(self, graph):
     builder = NeuralNetworkBuilder(input_features, output_features, mode=mode, disable_rank5_shape_mapping=disable_coreml_rank5_mapping)
 
     # TODO: To be removed once, auto-downgrading of spec version is enabled
-    builder.spec.specificationVersion = SupportedVersion.get_specification_version(target_ios)
+    builder.spec.specificationVersion = SupportedVersion.get_specification_version(minimum_ios_deployment_target)
 
     '''
     Set CoreML input,output types (float, double, int) same as onnx types, if supported
@@ -715,7 +715,7 @@ def _add_informative_description(feature, raise_error=True):
         builder.add_optionals(graph.optional_inputs, graph.optional_outputs)
 
     # Check for specification version and target ios compatibility
-    if target_ios == '11.2' and builder.spec.WhichOneof('Type') == 'neuralNetwork':
+    if minimum_ios_deployment_target == '11.2' and builder.spec.WhichOneof('Type') == 'neuralNetwork':
         nn_spec = builder.spec.neuralNetwork
         for layer in nn_spec.layers:
             if layer.WhichOneof('layer') == 'resizeBilinear' or layer.WhichOneof('layer') == 'cropResize':

tests/_test_utils.py

@@ -120,10 +120,10 @@ def _shape_from_onnx_value_info(v):  # type: (ValueInfoProto) -> Sequence[Tuple[
 def _coreml_forward_model(model,  # type: ModelProto
                           input_dict,  # type: Dict[Text, np._ArrayLike[Any]]
                           output_names,  # type: Sequence[Text]
-                          target_ios='12'
+                          minimum_ios_deployment_target='12'
                           ):
     # type: (...) -> np.ndarray[Any]
-    if not SupportedVersion.is_nd_array_supported(target_ios):
+    if not SupportedVersion.is_nd_array_supported(minimum_ios_deployment_target):
         for k, arr in input_dict.items():
             if len(arr.shape) == 4:
                 input_dict[k] = arr[0]
@@ -137,12 +137,12 @@ def _coreml_forward_model(model,  # type: ModelProto
 def _coreml_forward_onnx_model(model,  # type: ModelProto
                                input_dict,  # type: Dict[Text, np._ArrayLike[Any]]
                                onnx_coreml_input_shape_map = {}, # type: Dict[Text, List[int,...]]
-                               target_ios='12'
+                               minimum_ios_deployment_target='12'
                                ):
     # type: (...) -> np.ndarray[Any]
-    coreml_model = convert(model, onnx_coreml_input_shape_map=onnx_coreml_input_shape_map, target_ios=target_ios)
+    coreml_model = convert(model, onnx_coreml_input_shape_map=onnx_coreml_input_shape_map, minimum_ios_deployment_target=minimum_ios_deployment_target)
     output_names = [o.name for o in model.graph.output]
-    return _coreml_forward_model(coreml_model, input_dict, output_names, target_ios=target_ios)
+    return _coreml_forward_model(coreml_model, input_dict, output_names, minimum_ios_deployment_target=minimum_ios_deployment_target)
 
 
 def _random_array(shape, random_seed=10):  # type: (Tuple[int, ...], Any) -> np._ArrayLike[float]
@@ -225,7 +225,7 @@ def _test_onnx_model(model,  # type: ModelProto
                      decimal=5,  # type: int
                      onnx_coreml_input_shape_map = {}, # type: Dict[Text, List[int,...]]
                      coreml_input_shape = {}, # type: Dict[Text, List[int,...]]
-                     target_ios='12'
+                     minimum_ios_deployment_target='12'
                      ):
     # type: (...) -> None
     if not test_name:
@@ -238,12 +238,12 @@ def _test_onnx_model(model,  # type: ModelProto
     supported_ios_version = ['11.2', '12', '13']
     IOS_13_VERSION = supported_ios_version.index('13')
     for key, value in W.items():
-        if supported_ios_version.index(target_ios) < IOS_13_VERSION and key in coreml_input_shape:
+        if supported_ios_version.index(minimum_ios_deployment_target) < IOS_13_VERSION and key in coreml_input_shape:
             coreml_input_dict[key] = np.reshape(value, coreml_input_shape[key])
         else:
             coreml_input_dict[key] = value
     coreml_outputs = _coreml_forward_onnx_model(model, coreml_input_dict, onnx_coreml_input_shape_map=onnx_coreml_input_shape_map,
-                                                target_ios=target_ios)
+                                                minimum_ios_deployment_target=minimum_ios_deployment_target)
     _assert_outputs(c2_outputs, coreml_outputs, decimal=decimal)
 
 
@@ -255,7 +255,7 @@ def _test_single_node(op_type,  # type: Text
                       test_name = '', # type: Text
                       onnx_coreml_input_shape_map = {}, # type: Dict[Text, List[int,...]]
                       coreml_input_shape = {}, # type: Dict[Text, List[int,...]]
-                      target_ios='12',
+                      minimum_ios_deployment_target='12',
                       **kwargs  # type: Any
                       ):
     # type: (...) -> None
@@ -267,4 +267,4 @@ def _test_single_node(op_type,  # type: Text
     _test_onnx_model(model, test_name=test_name, decimal=decimal,
                      onnx_coreml_input_shape_map=onnx_coreml_input_shape_map,
                      coreml_input_shape = coreml_input_shape,
-                     target_ios=target_ios)
+                     minimum_ios_deployment_target=minimum_ios_deployment_target)

tests/onnx_backend_models_test.py

@@ -15,21 +15,21 @@
 from coremltools.models.utils import macos_version
 
 # Default target iOS
-TARGET_IOS = '13'
+MINIMUM_IOS_DEPLOYMENT_TARGET = '13'
 
 MIN_MACOS_VERSION_10_15 = (10, 15)
 # If MACOS version is less than 10.15
 # Then force testing on CoreML 2.0
 if macos_version() < MIN_MACOS_VERSION_10_15:
-    TARGET_IOS = '12'
+    MINIMUM_IOS_DEPLOYMENT_TARGET = '12'
 
-if not SupportedVersion.ios_support_check(TARGET_IOS):
+if not SupportedVersion.ios_support_check(MINIMUM_IOS_DEPLOYMENT_TARGET):
     raise ValueError(
         "Invalid Target iOS version provided. Valid target iOS: {}".format(supported_ios_version)
     )
 
 # import all test cases at global scope to make them visible to python.unittest
-backend_test = onnx.backend.test.BackendTest(CoreMLBackendND if SupportedVersion.is_nd_array_supported(TARGET_IOS) else CoreMLBackend, __name__)
+backend_test = onnx.backend.test.BackendTest(CoreMLBackendND if SupportedVersion.is_nd_array_supported(MINIMUM_IOS_DEPLOYMENT_TARGET) else CoreMLBackend, __name__)
 
 # Only include the big models tests
 backend_test.include('test_resnet50')