6.1 Release

.gitlab-ci.yml

@@ -98,7 +98,7 @@ test_py37_pytorch:
     WHEEL_PATH: build/dist/*cp37*10_15*
 
 test_py37_tf1:
-  <<: *test_macos_pkg
+  <<: *test_macos_pkg_with_reqs
   tags:
     - macos12
   dependencies:
@@ -107,9 +107,10 @@ test_py37_tf1:
     PYTHON: "3.7"
     TEST_PACKAGE: coremltools.converters.mil.frontend.tensorflow
     WHEEL_PATH: build/dist/*cp37*10_15*
+    REQUIREMENTS: reqs/test_tf1.pip
 
 test_py37_tf2:
-  <<: *test_macos_pkg_with_reqs
+  <<: *test_macos_pkg
   tags:
     - macos12
   dependencies:
@@ -118,7 +119,6 @@ test_py37_tf2:
     PYTHON: "3.7"
     TEST_PACKAGE: coremltools.converters.mil.frontend.tensorflow2
     WHEEL_PATH: build/dist/*cp37*10_15*
-    REQUIREMENTS: reqs/test_tf2.pip
 
 test_py37_mil:
   <<: *test_macos_pkg

coremltools/__init__.py

@@ -24,13 +24,10 @@
 from enum import Enum as _Enum
 from logging import getLogger as _getLogger
 
-
-# Backup root logger handlers
-_root_logger = _getLogger()
-_root_logger_handlers_backup = _root_logger.handlers.copy()
-
 from .version import __version__
 
+_logger = _getLogger(__name__)
+
 # This is the basic Core ML specification format understood by iOS 11.0
 SPECIFICATION_VERSION = 1
 
@@ -63,6 +60,9 @@
 # New versions for iOS 16.0
 _SPECIFICATION_VERSION_IOS_16 = 7
 
+# New versions for iOS 17.0
+_SPECIFICATION_VERSION_IOS_17 = 8
+
 class ComputeUnit(_Enum):
     '''
     The set of processing-unit configurations the model can use to make predictions.
@@ -79,6 +79,7 @@ class ComputeUnit(_Enum):
     _SPECIFICATION_VERSION_IOS_14: "CoreML4",
     _SPECIFICATION_VERSION_IOS_15: "CoreML5",
     _SPECIFICATION_VERSION_IOS_16: "CoreML6",
+    _SPECIFICATION_VERSION_IOS_17: "CoreML7",
 }
 
 # Default specification version for each backend
@@ -122,9 +123,3 @@ class ComputeUnit(_Enum):
 
 if _ENABLE_PROFILING:
     _sys.setprofile(_profiler)
-
-# Restore root logger handlers
-_root_logger = _getLogger()
-_coreml_logger = _getLogger(__name__)
-_coreml_logger.handlers = _root_logger.handlers.copy()
-_root_logger.handlers = _root_logger_handlers_backup

coremltools/_deps/__init__.py

@@ -7,12 +7,14 @@
 List of all external dependancies for this package. Imported as
 optional includes
 """
-from distutils.version import StrictVersion as _StrictVersion
-import logging as _logging
-from packaging import version
 import platform as _platform
 import re as _re
 import sys as _sys
+from distutils.version import StrictVersion as _StrictVersion
+
+from packaging import version
+
+from coremltools import _logger as logger
 
 
 def _get_version(version):
@@ -24,7 +26,7 @@ def _get_version(version):
 
 def _warn_if_above_max_supported_version(package_name, package_version, max_supported_version):
     if _get_version(package_version) > _StrictVersion(max_supported_version):
-        _logging.warning(
+        logger.warning(
             "%s version %s has not been tested with coremltools. You may run into unexpected errors. "
             "%s %s is the most recent version that has been tested."
             % (package_name, package_version, package_name, max_supported_version)
@@ -64,7 +66,7 @@ def __get_sklearn_version(version):
         _SKLEARN_MIN_VERSION
     ) or _SKLEARN_VERSION > _StrictVersion(_SKLEARN_MAX_VERSION):
         _HAS_SKLEARN = False
-        _logging.warning(
+        logger.warning(
             (
                 "scikit-learn version %s is not supported. Minimum required version: %s. "
                 "Maximum required version: %s. "
@@ -100,7 +102,7 @@ def __get_sklearn_version(version):
 _TF_1_MIN_VERSION = "1.12.0"
 _TF_1_MAX_VERSION = "1.15.4"
 _TF_2_MIN_VERSION = "2.1.0"
-_TF_2_MAX_VERSION = "2.8.0"
+_TF_2_MAX_VERSION = "2.10.0"
 
 try:
     import tensorflow
@@ -116,7 +118,7 @@ def __get_sklearn_version(version):
 
     if _HAS_TF_1:
         if tf_ver < _StrictVersion(_TF_1_MIN_VERSION):
-            _logging.warning(
+            logger.warning(
                 (
                     "TensorFlow version %s is not supported. Minimum required version: %s ."
                     "TensorFlow conversion will be disabled."
@@ -126,7 +128,7 @@ def __get_sklearn_version(version):
         _warn_if_above_max_supported_version("TensorFlow", tensorflow.__version__, _TF_1_MAX_VERSION)
     elif _HAS_TF_2:
         if tf_ver < _StrictVersion(_TF_2_MIN_VERSION):
-            _logging.warn(
+            logger.warning(
                 (
                     "TensorFlow version %s is not supported. Minimum required version: %s ."
                     "TensorFlow conversion will be disabled."

coremltools/converters/_converters_entry.py

@@ -6,49 +6,42 @@
 import collections
 import gc
 import os
-import warnings
 
 from coremltools import (
-    ComputeUnit as _ComputeUnit,
-    __version__ as _ct_version,
-    _LOWEST_ALLOWED_SPECIFICATION_VERSION_FOR_NEURALNETWORK,
     _LOWEST_ALLOWED_SPECIFICATION_VERSION_FOR_MILPROGRAM,
-)
-from coremltools.converters.mil.mil.passes.quantization_passes import (
-    AbstractQuantizationPass,
-    ComputePrecision as precision,
-    FP16ComputePrecision
-)
-from coremltools.converters.mil.input_types import (
-    ClassifierConfig,
-    ImageType,
-    InputType,
-    TensorType,
-)
+    _LOWEST_ALLOWED_SPECIFICATION_VERSION_FOR_NEURALNETWORK)
+from coremltools import ComputeUnit as _ComputeUnit
+from coremltools import __version__ as _ct_version
+from coremltools._deps import _HAS_TF_1, _HAS_TF_2, _HAS_TORCH
+from coremltools.converters._profile_utils import _profile
+from coremltools.converters.mil._deployment_compatibility import (
+    AvailableTarget, check_deployment_compatibility)
 from coremltools.converters.mil.converter import mil_convert
+from coremltools.converters.mil.input_types import (ClassifierConfig,
+                                                    ImageType, InputType,
+                                                    TensorType)
 from coremltools.converters.mil.mil import Program, types
-from coremltools._deps import _HAS_TORCH, _HAS_TF_1, _HAS_TF_2
-from coremltools.converters._profile_utils import _profile
-
-from coremltools.models import _METADATA_VERSION, _METADATA_SOURCE
+from coremltools.converters.mil.mil.passes.quantization_passes import \
+    ComputePrecision as precision
+from coremltools.converters.mil.mil.passes.quantization_passes import \
+    FP16ComputePrecision
+from coremltools.models import _METADATA_SOURCE, _METADATA_VERSION
 from coremltools.models.utils import _MLPACKAGE_EXTENSION
-from coremltools.converters.mil._deployment_compatibility import (
-    AvailableTarget,
-    check_deployment_compatibility,
-)
 
 if _HAS_TF_1:
     import tensorflow as tf
+
     from coremltools.converters.mil.frontend.tensorflow.load import TF1Loader
 if _HAS_TF_2:
     import tensorflow as tf
+
     from coremltools.converters.mil.frontend.tensorflow2.load import TF2Loader
 
 if _HAS_TORCH:
     import torch
-    from coremltools.converters.mil.frontend.torch.load import (
-        _torchscript_from_model as pytorch_load,
-    )
+
+    from coremltools.converters.mil.frontend.torch.load import \
+        _torchscript_from_model as pytorch_load
 
 @_profile
 def convert(

coremltools/converters/libsvm/__init__.py

@@ -4,10 +4,8 @@
 # found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
 
 
-from . import _libsvm_converter
-from . import _libsvm_util
-
 from ..._deps import _HAS_LIBSVM
+from . import _libsvm_converter, _libsvm_util
 
 if _HAS_LIBSVM:
     from libsvm import svmutil as _svmutil

coremltools/converters/libsvm/_libsvm_converter.py

@@ -3,10 +3,11 @@
 # Use of this source code is governed by a BSD-3-clause license that can be
 # found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
 
+from coremltools import __version__ as ct_version
+from coremltools.models import _METADATA_SOURCE, _METADATA_VERSION
+
 from ... import SPECIFICATION_VERSION
 from ..._deps import _HAS_LIBSVM
-from coremltools import __version__ as ct_version
-from coremltools.models import _METADATA_VERSION, _METADATA_SOURCE
 
 
 def _infer_min_num_features(model):
@@ -55,10 +56,9 @@ def convert(libsvm_model, feature_names, target, input_length, probability):
         raise RuntimeError("libsvm not found. libsvm conversion API is disabled.")
 
     from libsvm import svm as _svm
-    from ...proto import SVM_pb2
-    from ...proto import Model_pb2
-    from ...proto import FeatureTypes_pb2
+
     from ...models import MLModel
+    from ...proto import Model_pb2
 
     svm_type_enum = libsvm_model.param.svm_type
 

coremltools/converters/libsvm/_libsvm_util.py

@@ -28,9 +28,10 @@ def load_model(model_path):
     if not (_HAS_LIBSVM):
         raise RuntimeError("libsvm not found. libsvm conversion API is disabled.")
 
-    from svmutil import svm_load_model  # From libsvm
     import os
 
+    from svmutil import svm_load_model  # From libsvm
+
     if not os.path.exists(model_path):
         raise IOError("Expected a valid file path. %s does not exist" % model_path)
     return svm_load_model(model_path)

coremltools/converters/mil/__init__.py

@@ -3,44 +3,14 @@
 #  Use of this source code is governed by a BSD-3-clause license that can be
 #  found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
 
-from .mil import (
-    Block,
-    builder,
-    Builder,
-    curr_block,
-    DefaultInputs,
-    Function,
-    get_existing_symbol,
-    get_new_symbol,
-    get_new_variadic_symbol,
-    InputSpec,
-    InternalVar,
-    ListInputType,
-    ListVar,
-    mil_list,
-    Operation,
-    Placeholder,
-    Program,
-    register_op,
-    SPACES,
-    SUPPORT_FLOAT_TYPES,
-    SUPPORT_INT_TYPES,
-    Symbol,
-    TupleInputType,
-    Var,
-)
 
-from .frontend.torch import register_torch_op
-
-from .input_types import (
-    ClassifierConfig,
-    ColorLayout,
-    InputType,
-    TensorType,
-    ImageType,
-    RangeDim,
-    Shape,
-    EnumeratedShapes,
-)
-
-from coremltools.converters.mil.frontend.tensorflow.tf_op_registry import register_tf_op
+from .mil import (SPACES, SUPPORT_FLOAT_TYPES, SUPPORT_INT_TYPES, Block,
+                  Builder, DefaultInputs, Function, InputSpec, InternalVar,
+                  ListInputType, ListVar, Operation, Placeholder, Program,
+                  Symbol, TupleInputType, Var, builder, curr_block,
+                  get_existing_symbol, get_new_symbol, get_new_variadic_symbol,
+                  mil_list, register_op)
+from .input_types import (ClassifierConfig, ColorLayout, EnumeratedShapes,
+                          ImageType, InputType, RangeDim, Shape, TensorType)
+from .frontend.tensorflow.tf_op_registry import register_tf_op
+from .frontend.torch import register_torch_op

coremltools/converters/mil/_deployment_compatibility.py

@@ -5,12 +5,11 @@
 
 from enum import IntEnum
 
-from coremltools import (
-    _SPECIFICATION_VERSION_IOS_13,
-    _SPECIFICATION_VERSION_IOS_14,
-    _SPECIFICATION_VERSION_IOS_15,
-    _SPECIFICATION_VERSION_IOS_16,
-)
+from coremltools import (_SPECIFICATION_VERSION_IOS_13,
+                         _SPECIFICATION_VERSION_IOS_14,
+                         _SPECIFICATION_VERSION_IOS_15,
+                         _SPECIFICATION_VERSION_IOS_16,
+                         _SPECIFICATION_VERSION_IOS_17)
 
 
 class AvailableTarget(IntEnum):
@@ -19,6 +18,7 @@ class AvailableTarget(IntEnum):
     iOS14 = _SPECIFICATION_VERSION_IOS_14
     iOS15 = _SPECIFICATION_VERSION_IOS_15
     iOS16 = _SPECIFICATION_VERSION_IOS_16
+    iOS17 = _SPECIFICATION_VERSION_IOS_17
 
     # macOS versions (aliases of iOS versions)
     macOS15 = _SPECIFICATION_VERSION_IOS_13
@@ -28,18 +28,21 @@ class AvailableTarget(IntEnum):
     macOS11 = _SPECIFICATION_VERSION_IOS_14
     macOS12 = _SPECIFICATION_VERSION_IOS_15
     macOS13 = _SPECIFICATION_VERSION_IOS_16
+    macOS14 = _SPECIFICATION_VERSION_IOS_17
 
     # watchOS versions (aliases of iOS versions)
     watchOS6 = _SPECIFICATION_VERSION_IOS_13
     watchOS7 = _SPECIFICATION_VERSION_IOS_14
     watchOS8 = _SPECIFICATION_VERSION_IOS_15
     watchOS9 = _SPECIFICATION_VERSION_IOS_16
+    watchOS10 = _SPECIFICATION_VERSION_IOS_17
 
     # tvOS versions (aliases of iOS versions)
     tvOS13 = _SPECIFICATION_VERSION_IOS_13
     tvOS14 = _SPECIFICATION_VERSION_IOS_14
     tvOS15 = _SPECIFICATION_VERSION_IOS_15
     tvOS16 = _SPECIFICATION_VERSION_IOS_16
+    tvOS17 = _SPECIFICATION_VERSION_IOS_17
 
     # customized __str__
     def __str__(self):

coremltools/converters/mil/backend/backend_helper.py

@@ -4,9 +4,11 @@
 #  found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
 
 from coremltools.converters.mil.input_types import ColorLayout
-from coremltools.converters.mil.mil.passes.name_sanitization_utils import NameSanitizer
+from coremltools.converters.mil.mil.passes.name_sanitization_utils import \
+    NameSanitizer
 from coremltools.proto import FeatureTypes_pb2 as ft
 
+
 def _get_probability_var_for_classifier(prog, classifier_config):
     '''
     Return the var which will be used to construct the dictionary for the classifier.

coremltools/converters/mil/backend/mil/helper.py

@@ -7,17 +7,15 @@
 
 import numpy as np
 
-from coremltools.converters.mil.mil import types
-from coremltools.converters.mil.mil.types import builtin_to_proto_types
-from coremltools.models.utils import _WEIGHTS_DIR_NAME, _WEIGHTS_FILE_NAME
 import coremltools.proto.FeatureTypes_pb2 as ft
 import coremltools.proto.MIL_pb2 as pm
-from coremltools.converters.mil.mil.types import (
-    type_to_builtin_type,
-    numpy_type_to_builtin_type,
-    builtin_to_string
-)
+from coremltools.converters.mil.mil import types
+from coremltools.converters.mil.mil.types import (builtin_to_proto_types,
+                                                  builtin_to_string,
+                                                  numpy_type_to_builtin_type,
+                                                  type_to_builtin_type)
 from coremltools.converters.mil.mil.types.type_mapping import np_val_to_py_type
+from coremltools.models.utils import _WEIGHTS_DIR_NAME, _WEIGHTS_FILE_NAME
 
 
 def create_valuetype_scalar(data_type):