Convolution default fixed, extensive tests (#321)

The default (gather/scatter) backend for convolution is fixed, with
aggressive testing to confirm.

---------

Signed-off-by: Christopher Horvath <[email protected]>

Author: blackencino

fvdb/convolution_plan.py

@@ -189,12 +189,16 @@ def from_grid_batch(
         kernel_size = to_Vec3i(kernel_size, value_constraint=ValueConstraint.POSITIVE)
         stride = to_Vec3i(stride, value_constraint=ValueConstraint.POSITIVE)
 
-        if not _vec_is_all(kernel_size, kernel_size[0].item()):
-            raise NotImplementedError("Non-uniform kernel sizes are not currently supported")
+        if not _vec_is_all(stride, 1):
+            raise NotImplementedError("Strides not equal to 1 are not currently supported")
+
         if not _vec_is_all(stride, stride[0].item()):
             raise NotImplementedError("Non-uniform strides are not currently supported")
 
         backend = expert_config.get("backend", "default")
+        if backend != "default":
+            raise NotImplementedError("Non-default backends are not currently supported")
+
         if backend in ["dense", "halo", "lggs"]:
             if target_grid is not None:
                 raise ValueError("Target grid must be None for dense, halo, and lggs backends.")
@@ -267,12 +271,16 @@ def from_grid_batch_transposed(
         kernel_size = to_Vec3i(kernel_size, value_constraint=ValueConstraint.POSITIVE)
         stride = to_Vec3i(stride, value_constraint=ValueConstraint.POSITIVE)
 
-        if not _vec_is_all(kernel_size, kernel_size[0].item()):
-            raise NotImplementedError("Non-uniform kernel sizes are not currently supported")
+        if not _vec_is_all(stride, 1):
+            raise NotImplementedError("Strides not equal to 1 are not currently supported")
+
         if not _vec_is_all(stride, stride[0].item()):
             raise NotImplementedError("Non-uniform strides are not currently supported")
 
         backend = expert_config.get("backend", "default")
+        if backend != "default":
+            raise NotImplementedError("Non-default backends are not currently supported")
+
         if backend == "dense":
             if target_grid is not None:
                 raise ValueError("Target grid must be None for dense backend, transposed.")
@@ -348,12 +356,16 @@ def from_grid(
         kernel_size = to_Vec3i(kernel_size, value_constraint=ValueConstraint.POSITIVE)
         stride = to_Vec3i(stride, value_constraint=ValueConstraint.POSITIVE)
 
-        if not _vec_is_all(kernel_size, kernel_size[0].item()):
-            raise NotImplementedError("Non-uniform kernel sizes are not currently supported")
+        if not _vec_is_all(stride, 1):
+            raise NotImplementedError("Strides not equal to 1 are not currently supported")
+
         if not _vec_is_all(stride, stride[0].item()):
             raise NotImplementedError("Non-uniform strides are not currently supported")
 
         backend = expert_config.get("backend", "default")
+        if backend != "default":
+            raise NotImplementedError("Non-default backends are not currently supported")
+
         if backend in ["dense", "halo", "lggs"]:
             if target_grid is not None:
                 raise ValueError("Target grid must be None for dense, halo, and lggs backends.")
@@ -424,12 +436,16 @@ def from_grid_transposed(
         kernel_size = to_Vec3i(kernel_size, value_constraint=ValueConstraint.POSITIVE)
         stride = to_Vec3i(stride, value_constraint=ValueConstraint.POSITIVE)
 
-        if not _vec_is_all(kernel_size, kernel_size[0].item()):
-            raise NotImplementedError("Non-uniform kernel sizes are not currently supported")
+        if not _vec_is_all(stride, 1):
+            raise NotImplementedError("Strides not equal to 1 are not currently supported")
+
         if not _vec_is_all(stride, stride[0].item()):
             raise NotImplementedError("Non-uniform strides are not currently supported")
 
         backend = expert_config.get("backend", "default")
+        if backend != "default":
+            raise NotImplementedError("Non-default backends are not currently supported")
+
         if backend == "dense":
             if target_grid is not None:
                 raise ValueError("Target grid must be None for dense backend, transposed.")