Revert "Distributed Fast Fourier Transforms (#1218)"

This reverts commit 8b87890.

heat/__init__.py

@@ -9,7 +9,6 @@
 from . import core
 from . import classification
 from . import cluster
-from . import fft
 from . import graph
 from . import naive_bayes
 from . import nn

heat/core/stride_tricks.py

@@ -151,10 +151,7 @@ def sanitize_axis(
 
     """
     # scalars are handled like unsplit matrices
-    original_axis = axis
-    ndim = len(shape)
-
-    if ndim == 0:
+    if len(shape) == 0:
         axis = None
 
     if axis is not None and not isinstance(axis, int) and not isinstance(axis, tuple):
@@ -163,9 +160,7 @@ def sanitize_axis(
         axis = tuple(dim + len(shape) if dim < 0 else dim for dim in axis)
         for dim in axis:
             if dim < 0 or dim >= len(shape):
-                raise ValueError(
-                    f"axis {original_axis} is out of bounds for {ndim}-dimensional array"
-                )
+                raise ValueError(f"axis {axis} is out of bounds for shape {shape}")
         return axis
 
     if axis is None or 0 <= axis < len(shape):
@@ -174,7 +169,7 @@ def sanitize_axis(
         axis += len(shape)
 
     if axis < 0 or axis >= len(shape):
-        raise ValueError(f"axis {original_axis} is out of bounds for {ndim}-dimensional array")
+        raise ValueError(f"axis {axis} is out of bounds for shape {shape}")
 
     return axis
 

heat/core/tests/test_suites/basic_test.py

@@ -129,11 +129,11 @@ def assert_array_equal(self, heat_array, expected_array):
             f"Local shapes do not match. Got {heat_array.lshape} expected {expected_array[slices].shape}",
         )
         # compare local tensors to corresponding slice of expected_array
-        is_allclose = torch.tensor(
-            np.allclose(heat_array.larray.cpu(), expected_array[slices]), dtype=torch.int32
+        is_allclose = np.allclose(heat_array.larray.cpu(), expected_array[slices])
+        ht_is_allclose = ht.array(
+            [is_allclose], dtype=ht.bool, is_split=0, device=heat_array.device
         )
-        heat_array.comm.Allreduce(MPI.IN_PLACE, is_allclose, MPI.SUM)
-        self.assertTrue(is_allclose == heat_array.comm.size)
+        self.assertTrue(ht.all(ht_is_allclose))
 
     def assert_func_equal(
         self,