Legacy checkpoint read, fix checkpoint re-training issue (#434)

.gitignore

@@ -12,6 +12,9 @@ src/aihwkit/simulator/*.so
 # Temporary folder for the example downloads.
 data/
 
+# Folder for cibuildwheel.
+wheelhouse/
+
 ## From https://github.com/github/gitignore/blob/master/Python.gitignore
 
 # Byte-compiled / optimized / DLL files

CHANGELOG.md

@@ -56,6 +56,7 @@ The format is based on [Keep a Changelog], and this project adheres to
 * `WeightModifiers` of the `InferenceRPUConfig` are no longer called
   in the forward pass, but instead in the `post_update_step`
   method to avoid issues with repeated forward calls. (\#423)
+* Fix training `learn_out_scales` issue after checkpoint load. (\#434)
 
 ### Changed
 
@@ -81,7 +82,7 @@ The format is based on [Keep a Changelog], and this project adheres to
 ### Removed
 
 * The `_scaled` versions of the weight getter and setter methods are
-removed (\#423) 
+removed (\#423)
 
 
 ## [0.6.0] - 2022/05/16

CMakeLists.txt

@@ -13,13 +13,13 @@ project(aihwkit C CXX)
 
 # Project options.
 option(BUILD_TEST "Build C++ test binaries" OFF)
-option(USE_CUDA "Build with CUDA support" OFF)
+option(USE_CUDA "Build with CUDA support" $ENV{USE_CUDA})
 option(RPU_DEBUG "Enable debug printing" OFF)
 option(RPU_USE_FASTMOD "Use fast mod" ON)
 option(RPU_USE_FASTRAND "Use fastrand" OFF)
 
 set(RPU_BLAS "OpenBLAS" CACHE STRING "BLAS backend of choice (OpenBLAS, MKL)")
-set(RPU_CUDA_ARCHITECTURES "60" CACHE STRING "Target CUDA architectures")
+set(RPU_CUDA_ARCHITECTURES "60;70;75;80" CACHE STRING "Target CUDA architectures")
 
 # Internal variables.
 set(CUDA_TARGET_PROPERTIES POSITION_INDEPENDENT_CODE ON

requirements.txt

@@ -1,6 +1,5 @@
 # Build dependencies.
 cmake>=3.18
-setuptools<=46.0; python_version < '3.9'
 scikit-build>=0.11.1
 pybind11>=2.6.2
 # Runtime dependencies.

src/aihwkit/VERSION.txt

@@ -1 +1 @@
-0.6.0
+0.6.2

src/aihwkit/cloud/client/entities.py

@@ -19,9 +19,11 @@
 
 from aihwkit.cloud.client.exceptions import ExperimentStatusError
 from aihwkit.cloud.converter.definitions.input_file_pb2 import TrainingInput
+from aihwkit.cloud.converter.definitions.i_input_file_pb2 import InferenceInput
 from aihwkit.cloud.converter.definitions.output_file_pb2 import TrainingOutput
 from aihwkit.cloud.converter.v1.training import BasicTrainingConverter, BasicTrainingResultConverter
-from aihwkit.experiments import BasicTraining
+from aihwkit.cloud.converter.v1.inferencing import BasicInferencingConverter
+# from aihwkit.experiments import BasicTraining, BasicInferencing
 
 
 class CloudJobStatus(Enum):
@@ -62,7 +64,7 @@ class CloudExperiment:
     input_id: Optional[str] = field(repr=False)
     job: Optional[CloudJob] = field(repr=False)
 
-    def get_experiment(self) -> BasicTraining:
+    def get_experiment(self) -> Any:
         """Return a data Experiment.
 
         Returns:
@@ -76,11 +78,16 @@ def get_experiment(self) -> BasicTraining:
 
         input_ = self._api_client.input_get(self.input_id)
 
-        input_proto = TrainingInput()
-        input_proto.ParseFromString(input_)
+        if 'InferenceRPUConfig' in str(input_):
+            input_proto = InferenceInput()
+            input_proto.ParseFromString(input_)
+            proto = BasicInferencingConverter().from_proto(input_proto)
+        else:
+            input_proto = TrainingInput()
+            input_proto.ParseFromString(input_)
+            proto = BasicTrainingConverter().from_proto(input_proto)
 
-        converter = BasicTrainingConverter()
-        return converter.from_proto(input_proto)
+        return proto
 
     def get_result(self) -> list:
         """Return the result of an Experiment.

src/aihwkit/cloud/converter/v1/i_mappings.py

@@ -24,11 +24,13 @@
 
 from aihwkit.simulator.configs import InferenceRPUConfig
 from aihwkit.simulator.presets.web import (
-    WebComposerInferenceRPUConfig, OldWebComposerInferenceRPUConfig
-)
+    WebComposerInferenceRPUConfig, OldWebComposerInferenceRPUConfig)
 from aihwkit.cloud.converter.definitions.i_onnx_common_pb2 import AttributeProto
 from aihwkit.cloud.converter.exceptions import ConversionError
-from aihwkit.nn import AnalogConv2d, AnalogLinear
+from aihwkit.nn import (
+    AnalogConv2d, AnalogConv2dMapped,
+    AnalogLinear, AnalogLinearMapped
+)
 from aihwkit.optim import AnalogSGD
 from aihwkit.cloud.converter.v1.rpu_config_info import RPUconfigInfo
 
@@ -139,10 +141,13 @@ def get_field_value_to_proto(self, source: Any, field: str, default: Any = None)
         if field == 'bias':
             return getattr(source, 'bias', None) is not None
         if field == 'rpu_config':
-            preset_cls = type(source.analog_tile.rpu_config)
+            # preset_cls = type(source.analog_tile.rpu_config)
+            analog_tile = next(source.analog_tiles())
+            preset_cls = type(analog_tile.rpu_config)
             if preset_cls not in Mappings.presets:
-                raise ConversionError('Invalid rpu_config in layer: {} not '
-                                      'among the presets'.format(preset_cls))
+                raise ConversionError('Invalid rpu_config in layer: '
+                                      f'{preset_cls} not '
+                                      'among the presets')
             return Mappings.presets[preset_cls]
         return super().get_field_value_to_proto(source, field, default)
 
@@ -182,12 +187,28 @@ class Mappings:
             'bias': bool,
             'rpu_config': str,
         }),
+        AnalogConv2dMapped: LayerFunction('AnalogConv2dMapped', {
+            'in_channels': int,
+            'out_channels': int,
+            'kernel_size': [int],
+            'stride': [int],
+            'padding': [int],
+            'dilation': [int],
+            'bias': bool,
+            'rpu_config': str,
+        }),
         AnalogLinear: LayerFunction('AnalogLinear', {
             'in_features': int,
             'out_features': int,
             'bias': bool,
             'rpu_config': str,
         }),
+        AnalogLinearMapped: LayerFunction('AnalogLinearMapped', {
+            'in_features': int,
+            'out_features': int,
+            'bias': bool,
+            'rpu_config': str,
+        }),
         BatchNorm2d: LayerFunction('BatchNorm2d', {
             'num_features': int
         }),

src/aihwkit/cloud/converter/v1/inferencing.py

@@ -68,11 +68,11 @@ def from_proto(self, protobuf: Any) -> BasicInferencing:
         """Convert a protobuf representation to an `Experiment`."""
 
         dataset = InverseMappings.datasets[protobuf.dataset.dataset_id]
-
+        layers = protobuf.network.layers
         # build RPUconfig_info to be used when it is instantiated dynamically
         alog_info = AnalogInfo(protobuf.inferencing.analog_info)
         nm_info = NoiseModelInfo(protobuf.inferencing.noise_model_info)
-        rc_info = RPUconfigInfo(nm_info, alog_info)
+        rc_info = RPUconfigInfo(nm_info, alog_info, layers)
 
         model = self._model_from_proto(protobuf.network, rc_info)
 
@@ -104,8 +104,8 @@ def _version_to_proto() -> Any:
 
     @staticmethod
     def _dataset_to_proto(dataset: type, batch_size: int) -> Any:
-        if dataset not in Mappings.datasets.keys():
-            raise ConversionError('Unsupported dataset: {}'.format(dataset))
+        if dataset not in Mappings.datasets:
+            raise ConversionError(f'Unsupported dataset: {dataset}')
 
         return Dataset(
             dataset_id=Mappings.datasets[dataset],
@@ -121,7 +121,8 @@ def _model_to_proto(model: Module, weight_template_id: str) -> Any:
         children_types = {type(layer) for layer in model.children()}
         valid_types = set(Mappings.layers.keys()) | set(Mappings.activation_functions.keys())
         if children_types - valid_types:
-            raise ConversionError('Unsupported layers: {}'.format(children_types - valid_types))
+            raise ConversionError('Unsupported layers: '
+                                  f'{children_types - valid_types}')
 
         # Create a new input_file pb Network object with weight_template_id
         network = Network(weight_template_id=weight_template_id)
@@ -189,7 +190,7 @@ def rpu_config_info_from_info(analog_info: Dict,
         nm_info = NoiseModelInfo(BasicInferencingConverter._noise_model_to_proto(
             noise_model_info))  # type: ignore[name-defined]
         a_info = AnalogInfo(AnalogProto(**analog_info))
-        return RPUconfigInfo(nm_info, a_info)
+        return RPUconfigInfo(nm_info, a_info, None)
 
     @staticmethod
     def rpu_config_from_info(analog_info: Dict,
@@ -200,7 +201,8 @@ def rpu_config_from_info(analog_info: Dict,
         nm_info = NoiseModelInfo(BasicInferencingConverter._noise_model_to_proto(
             noise_model_info))  # type: ignore[name-defined]
         a_info = AnalogInfo(AnalogProto(**analog_info))
-        return RPUconfigInfo(nm_info, a_info).create_inference_rpu_config(func_id)
+        return RPUconfigInfo(nm_info,
+                             a_info, None).create_inference_rpu_config(func_id)
 
     @staticmethod
     def _inferencing_to_proto(

src/aihwkit/cloud/converter/v1/rpu_config_info.py

@@ -11,34 +11,81 @@
 # that they have been altered from the originals.
 
 """Creates InferenceRPUConfig to add to nn model"""
-
+from typing import Dict, Any
 from collections import OrderedDict
 
 from aihwkit.simulator.configs.configs import InferenceRPUConfig
-from aihwkit.simulator.presets.web import OldWebComposerInferenceRPUConfig
+from aihwkit.simulator.presets.web import (
+    WebComposerInferenceRPUConfig,
+    OldWebComposerInferenceRPUConfig
+)
 from aihwkit.inference.noise.pcm import PCMLikeNoiseModel
 from aihwkit.inference.noise.custom import StateIndependentNoiseModel
 from aihwkit.inference.compensation.drift import GlobalDriftCompensation
 from aihwkit.cloud.converter.v1.analog_info import AnalogInfo
 from aihwkit.cloud.converter.v1.noise_model_info import NoiseModelInfo
 
-# pylint: disable=too-few-public-methods
+RPU_CLASSES = {
+    'InferenceRPUConfig': InferenceRPUConfig,
+    'WebComposerInferenceRPUConfig': WebComposerInferenceRPUConfig,
+    'OldWebComposerInferenceRPUConfig': OldWebComposerInferenceRPUConfig
+}
 
 
+# pylint: disable=too-few-public-methods
 class NoiseModelDeviceIDException(Exception):
     """Exception raised if noise model device id is not correct"""
 
 
 class RPUconfigInfo:
     """Data only class for RPUConfig fields"""
 
-    def __init__(self, nm_info: NoiseModelInfo, a_info: AnalogInfo):
-        """"Constructor for this class"""
-
+    def __init__(self, nm_info: NoiseModelInfo,
+                 a_info: AnalogInfo,
+                 layers: Any = None):
+        """
+        The only constructor for this class
+        """
         self._noise_model_info = nm_info
         self._analog_info = a_info
+        self._layers = layers
         self._device_id = ''
 
+    @staticmethod
+    def _get_common_rpucfg_name(layers: Any) -> Any:
+        """Set common rpu config name by search all analog layers"""
+        # Use default RPU config for Composer
+        if layers is None:
+            return 'WebComposerInferenceRPUConfig'
+        # Need to loop through protobuf layers and figure out
+        #   common rpu_config value.
+        names: Dict[str, int] = {}
+        # pylint: disable=too-many-nested-blocks
+        for layer_proto in layers:  # type: ignore[attr-defined]
+            if layer_proto.WhichOneof('item') == 'layer':
+                layer = layer_proto.layer
+                if layer.id.startswith('Analog'):
+                    # Loop though all AttributeProto objecs in layer.arguments
+                    for argument in layer.arguments:
+                        if argument.name == 'rpu_config':
+                            # stored as UTF8 byte string in attribute s
+                            arg_value = getattr(argument, 's')
+                            # update count of this rpu_config in all analog layers
+                            if arg_value in names:
+                                names[arg_value] += 1
+                            else:
+                                names[arg_value] = 1
+        # pylint: enable=too-many-nested-blocks
+        # should have exactly on in dictionary 'names'
+        if len(names) > 1:
+            print(f'>>> ERROR: more than one rpu_config: {names}')
+            return None
+        if len(names) == 1:
+            # keys() returns dict_keys object, need a list
+            return list(names.keys())[0].decode('UTF-8')  # type: ignore[attr-defined]
+        print('>>> INFO: experiment has not analog layers')
+        return ''
+
     def _print_rpu_config(
             self,
             rpu_config: InferenceRPUConfig,
@@ -92,9 +139,22 @@ def _print_rpu_config(
     def create_inference_rpu_config(self, func_id: str,
                                     verbose: bool = False) -> InferenceRPUConfig:
         """Creates a InferenceRPUConfig class using noise and analog info"""
+        # Need to find name of 'common-rpu-conf-class-name' in protobuf
+        #   This should be the consistent across all layers.
+        #   The Composer Validator should have already caught this but
+        #   it is checked here for testcases and other unknown environments
+        rpu_class_name = self._get_common_rpucfg_name(self._layers)
+        print(f'>>> INFO: rpu_class_name={rpu_class_name}')
+        if rpu_class_name is None or len(rpu_class_name) == 0:
+            raise Exception('class name error. see previous messages')
+        rpu_config_class = None
+        if rpu_class_name in RPU_CLASSES:
+            rpu_config_class = RPU_CLASSES[rpu_class_name]
+        else:
+            raise Exception(f"rpu class name '{rpu_class_name}' not one of '{RPU_CLASSES.keys()}'")
 
-        rpu_config = OldWebComposerInferenceRPUConfig()
-
+        # Dynamically create the right InferenceRPUConfig class
+        rpu_config = rpu_config_class()
         # Assign values from AnalogProto
         rpu_config.forward.out_noise = self._analog_info.output_noise_strength
 

src/aihwkit/experiments/experiments/inferencing.py

@@ -185,7 +185,7 @@ def get_model(
                 if weight_template_id.startswith('http'):
                     template_url = weight_template_id
                 else:
-                    print('weights_template_id: ', weight_template_id)
+                    # print('weights_template_id: ', weight_template_id)
                     template_path = template_dir + "/" + weight_template_id + ".pth"
                     template_url = WEIGHT_TEMPLATE_URL + weight_template_id + ".pth"
                 # check if the file exists
@@ -194,7 +194,7 @@ def get_model(
                 if not path.exists(template_path):
                     download(template_url, template_path)
 
-            print('template_path: ', template_path)
+            # print('template_path: ', template_path)
             if path.exists(template_path):
                 model.load_state_dict(load(template_path, map_location=device),
                                       load_rpu_config=False)
@@ -203,7 +203,7 @@ def get_model(
 
             if self.remap_weights:
                 for module in model.analog_modules():
-                    module.remap_weights()
+                    module.remap_weights(1.0)
 
         return model.to(device)