Move to better supported strategy for avoiding circular imports

src/cdtools/models/base.py

@@ -40,6 +40,7 @@ import time
 from scipy import io
 from contextlib import contextmanager
 from cdtools.tools.data import nested_dict_to_h5, h5_to_nested_dict, nested_dict_to_numpy, nested_dict_to_torch
+from cdtools.reconstructors import AdamReconstructor, LBFGSReconstructor, SGDReconstructor
 from cdtools.datasets import CDataset
 from typing import List, Union, Tuple
 import os
@@ -378,13 +379,7 @@ class CDIModel(t.nn.Module):
         # cdtools.reconstructors.AdamReconstructor to perform reconstructions
         # without creating a new reconstructor each time we update the
         # hyperparameters.
-        #
-        # The only way to do this is to make the Adam reconstructor an
-        # attribute of the model. But since the Adam reconstructor also
-        # depends on CDIModel, this seems to give rise to a circular import
-        # error unless we import cdtools.reconstructors within this method:
         if not hasattr(self, 'reconstructor'):
-            from cdtools.reconstructors import AdamReconstructor
             self.reconstructor = AdamReconstructor(model=self,
                                                    dataset=dataset,
                                                    subset=subset)
@@ -449,12 +444,7 @@ class CDIModel(t.nn.Module):
         # cdtools.reconstructors.LBFGSReconstructor as an attribute to run
         # reconstructions without generating new reconstructors each time
         # CDIModel.LBFGS_optimize is called.
-        #
-        # Since the LBFGS reconstructor also depends on CDIModel, a circular
-        # import error arises unless we import cdtools.reconstructors within
-        # this method:
         if not hasattr(self, 'reconstructor'):
-            from cdtools.reconstructors import LBFGSReconstructor
             self.reconstructor = LBFGSReconstructor(model=self,
                                                     dataset=dataset,
                                                     subset=subset)
@@ -524,12 +514,7 @@ class CDIModel(t.nn.Module):
         # cdtools.reconstructors.SGDReconstructor as an attribute to run
         # reconstructions without generating new reconstructors each time
         # CDIModel.SGD_optimize is called.
-        #
-        # Since the SGD reconstructor also depends on CDIModel, a circular
-        # import error arises unless we import cdtools.reconstructors within
-        # this method:
         if not hasattr(self, 'reconstructor'):
-            from cdtools.reconstructors import SGDReconstructor
             self.reconstructor = SGDReconstructor(model=self, 
                                                   dataset=dataset, 
                                                   subset=subset)

src/cdtools/reconstructors/adam.py

@@ -6,12 +6,17 @@ The Reconstructor class is designed to resemble so-called
 'Trainer' classes that (in the language of the AI/ML folks) handles
 the 'training' of a model given some dataset and optimizer.
 """
+from __future__ import annotations
+from typing import TYPE_CHECKING
+
 import torch as t
-from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
-from cdtools.models import CDIModel
 from typing import Tuple, List, Union
 from cdtools.reconstructors import Reconstructor
 
+if TYPE_CHECKING:
+    from cdtools.models import CDIModel
+    from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
+
 __all__ = ['AdamReconstructor']
 
 

src/cdtools/reconstructors/base.py

@@ -8,16 +8,21 @@ the 'training' of a model given some dataset and optimizer.
 The subclasses of Reconstructor are required to implement
 their own data loaders and optimizer adjusters
 """
+from __future__ import annotations
+from typing import TYPE_CHECKING
 
 import torch as t
 from torch.utils import data as td
 import threading
 import queue
 import time
-from cdtools.datasets import CDataset
-from cdtools.models import CDIModel
 from typing import List, Union
 
+if TYPE_CHECKING:
+    from cdtools.models import CDIModel
+    from cdtools.datasets import CDataset
+    
+
 __all__ = ['Reconstructor']
 
 

src/cdtools/reconstructors/lbfgs.py

@@ -6,12 +6,18 @@ The Reconstructor class is designed to resemble so-called
 'Trainer' classes that (in the language of the AI/ML folks) handles
 the 'training' of a model given some dataset and optimizer.
 """
+from __future__ import annotations
+from typing import TYPE_CHECKING
+
 import torch as t
-from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
-from cdtools.models import CDIModel
 from typing import List, Union
 from cdtools.reconstructors import Reconstructor
 
+if TYPE_CHECKING:
+    from cdtools.models import CDIModel
+    from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
+
+
 __all__ = ['LBFGSReconstructor']
 
 

src/cdtools/reconstructors/sgd.py

@@ -6,12 +6,18 @@ The Reconstructor class is designed to resemble so-called
 'Trainer' classes that (in the language of the AI/ML folks) handles
 the 'training' of a model given some dataset and optimizer.
 """
+from __future__ import annotations
+from typing import TYPE_CHECKING
+
 import torch as t
-from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
-from cdtools.models import CDIModel
 from typing import List, Union
 from cdtools.reconstructors import Reconstructor
 
+if TYPE_CHECKING:
+    from cdtools.models import CDIModel
+    from cdtools.datasets.ptycho_2d_dataset import Ptycho2DDataset
+    
+
 __all__ = ['SGDReconstructor']