New logging system

Author: Xeratec

Deeploy/AbstractDataTypes.py

@@ -42,6 +42,8 @@
 _DeeployType = TypeVar("_DeeployType", _PointerType, _ImmediateType, _StructType)
 _PythonType = TypeVar("_PythonType", str, int, float, Dict[str, "_PythonType"], Iterable["_PythonType"])
 
+from Deeploy.Logging import DEFAULT_LOGGER as log
+
 
 class _ClassPropertyDescriptor(object):
 
@@ -275,8 +277,8 @@ def partialOrderUpcast(cls, otherCls: Type[Immediate]) -> bool:
     @classmethod
     def checkValue(cls, value: Union[float, Iterable[float], np.ndarray], ctxt: Optional[_NetworkContext] = None):
         """
-        This method tries to manually cast standard python's standard immediate float precision values 
-        (64 bits) to an arbitrary FP representation and check if the new representation is close enough 
+        This method tries to manually cast standard python's standard immediate float precision values
+        (64 bits) to an arbitrary FP representation and check if the new representation is close enough
         to the original value.
         """
         _val_list = []
@@ -337,7 +339,7 @@ def checkValue(cls, value: Optional[str], ctxt: Optional[_NetworkContext] = None
             return False
 
         if value is None or value == "NULL":
-            print("WARNING: Setting pointer value to NULL - Referenced data is invalid!")
+            log.warning("Setting pointer value to NULL - Referenced data is invalid!")
             return True
 
         reference = ctxt.lookup(value)

Deeploy/CommonExtensions/NetworkDeployers/SignPropDeployer.py

@@ -28,7 +28,8 @@
 import onnx_graphsurgeon as gs
 
 from Deeploy.AbstractDataTypes import Pointer
-from Deeploy.DeeployTypes import DeploymentPlatform, NetworkDeployer, TopologyOptimizer
+from Deeploy.DeeployTypes import CodeGenVerbosity, DeploymentPlatform, NetworkDeployer, TopologyOptimizer, _NoVerbosity
+from Deeploy.Logging import DEFAULT_LOGGER as log
 
 
 class SignPropDeployer(NetworkDeployer):
@@ -62,3 +63,36 @@ def _createIOBindings(self, ctxt, graph):
             nb.nLevels = (2**data_type.referencedType.typeWidth)
 
         return ctxt
+
+    def generateFunction(self, verbose: CodeGenVerbosity = _NoVerbosity) -> str:
+        """Helper function to prepare deployment and return generated function code
+
+        """
+
+        if not self.prepared:
+            self.prepare(verbose = verbose)
+
+        log.info("=" * 80)
+        log.info("Deeploy Code Generation")
+        log.info("=" * 80)
+
+        log.info('Input:')
+        for name in self.inputTypes.keys():
+            buf = self.ctxt.lookup(name)
+            log.info(
+                f" - '{name}': Type: {buf._type.referencedType.typeName}, nLevels: {buf.nLevels}, Signed: {buf._signed}, Offset: {self.inputOffsets[name]}"
+            )
+
+        log.info('Output:')
+        for buf in self.outputs():
+            log.info(
+                f" - '{buf.name}': Type: {buf._type.referencedType.typeName}, nLevels: {buf.nLevels}, Signed: {buf._signed}"
+            )
+
+        log.info("-" * 80)
+        num_ops = self.numberOfOps(verbose = True)
+        log.info("-" * 80)
+        log.info(f"Number of Ops.                : {num_ops}")
+        log.info(f"Model Parameters              : {self.getParameterSize()}")
+
+        return self.generateInferenceCode()

Deeploy/CommonExtensions/OptimizationPasses/PassClasses.py

@@ -30,6 +30,7 @@
 import onnx_graphsurgeon as gs
 
 from Deeploy.DeeployTypes import NetworkContext
+from Deeploy.Logging import DEFAULT_LOGGER as log
 
 from .Matchers import Match, NonBranchingMatcher, SubgraphMatcher
 
@@ -152,7 +153,7 @@ def remove_subpass(self, name):
         try:
             del self._subpasses[name]
         except KeyError:
-            print(f"No subpass with name {name}, cannot remove!")
+            log.error(f"No subpass with name {name}, cannot remove!")
         except AttributeError:
             raise AttributeError("Cannot remove sub-pass before calling Pass.__init__!")
 

Deeploy/CommonExtensions/TypeCheckers/SignPropTypeChecker.py

@@ -29,6 +29,7 @@
 
 from Deeploy.AbstractDataTypes import IntegerImmediate
 from Deeploy.DeeployTypes import ConstantBuffer, NetworkContext, NodeTypeChecker, OperatorRepresentation, VariableBuffer
+from Deeploy.Logging import DEFAULT_LOGGER as log
 
 
 class SignPropTypeChecker(NodeTypeChecker):
@@ -73,8 +74,8 @@ def typeInferOutput(self, ctxt: NetworkContext, node: gs.Node,
 
                 if issubclass(obj._type.referencedType,
                               IntegerImmediate) and not obj._type.checkNumLevels(nLevel, sign):
-                    print(
-                        f"[WARNING] {obj.name} has {nLevel} levels, but {obj._type.referencedType.typeName} only supports {obj._type.referencedType.nLevels} levels."
+                    log.warning(
+                        f"{obj.name} has {nLevel} levels, but {obj._type.referencedType.typeName} only supports {obj._type.referencedType.nLevels} levels."
                     )
 
         return ctxt