Merge branch 'develop' of https://github.com/LukasHedegaard/continual-inference into develop

Author: LukasHedegaard

CHANGELOG.md

@@ -9,14 +9,18 @@ From v1.0.0 and on, the project will adherence strictly to Semantic Versioning.
 
 ## [Unreleased]
 
-
-## [0.11.4]
+## [0.12.0]
 ### Added
 - Add `Constant`.
 - Add `Zero`.
 - Add `One`.
 
 
+## [0.11.4]
+### Fixed
+- `co.ConvXd` cuda compatibility.
+
+
 ## [0.11.3]
 ### Added
 - Add `flatten_state_dict` state variable.

Makefile

@@ -36,7 +36,7 @@ clean:
 ## Test the setup
 test:
 	@echo ⚡⚡⚡ Testing ⚡⚡⚡
-	py.test --cov continual --cov-report term-missing 
+	python -m pytest --cov continual --cov-report term-missing 
 
 
 ## Upload to codecov.io

continual/conv.py

@@ -45,6 +45,8 @@ def __init__(
         groups: int = 1,
         bias: bool = True,
         padding_mode: PaddingMode = "zeros",
+        device=None,
+        dtype=None,
         temporal_fill: PaddingMode = "zeros",
     ):
         assert issubclass(
@@ -82,6 +84,8 @@ def __init__(
             groups=groups,
             bias=bias,
             padding_mode=padding_mode,
+            device=device,
+            dtype=dtype,
         )
         self.make_padding = {
             PaddingMode.ZEROS.value: torch.zeros_like,
@@ -142,7 +146,7 @@ def _forward_step(self, input: Tensor, prev_state: State) -> Tuple[Tensor, State
         ), f"A tensor of shape {(*self.input_shape_desciption[:2], *self.input_shape_desciption[3:])} should be passed as input but got {input.shape}"
 
         # e.g. B, C -> B, C, 1
-        x = input.unsqueeze(2)
+        x = input.unsqueeze(2).to(device=self.weight.device)
 
         if self.padding_mode == "zeros":
             x = self._conv_func(
@@ -239,6 +243,8 @@ def __init__(
         groups: int = 1,
         bias: bool = True,
         padding_mode: PaddingMode = "zeros",
+        device=None,
+        dtype=None,
         temporal_fill: PaddingMode = "zeros",
     ):
         r"""Applies a continual 1D convolution over an input signal composed of several input
@@ -295,6 +301,8 @@ def __init__(
             groups,
             bias,
             padding_mode,
+            device,
+            dtype,
             temporal_fill,
         )
 
@@ -338,6 +346,8 @@ def __init__(
         groups: int = 1,
         bias: bool = True,
         padding_mode: PaddingMode = "zeros",
+        device=None,
+        dtype=None,
         temporal_fill: PaddingMode = "zeros",
     ):
         r"""Applies a continual 2D convolution over an input signal composed of several input
@@ -394,6 +404,8 @@ def __init__(
             groups,
             bias,
             padding_mode,
+            device,
+            dtype,
             temporal_fill,
         )
 
@@ -437,6 +449,8 @@ def __init__(
         groups: int = 1,
         bias: bool = True,
         padding_mode: PaddingMode = "zeros",
+        device=None,
+        dtype=None,
         temporal_fill: PaddingMode = "zeros",
     ):
         r"""Applies a continual 3D convolution over an input signal composed of several input
@@ -495,6 +509,8 @@ def __init__(
             groups,
             bias,
             padding_mode,
+            device,
+            dtype,
             temporal_fill,
         )