Merge pull request #32 from LukasHedegaard/develop

Add Constant, Zero, and One

Author: LukasHedegaard

CHANGELOG.md

@@ -9,6 +9,12 @@ From v1.0.0 and on, the project will adherence strictly to Semantic Versioning.
 
 ## [Unreleased]
 
+## [0.12.0]
+### Added
+- Add `Constant`.
+- Add `Zero`.
+- Add `One`.
+
 
 ## [0.11.4]
 ### Fixed

continual/__init__.py

@@ -1,4 +1,4 @@
-from .closure import Add, Lambda, Multiply, Unity  # noqa: F401
+from .closure import Add, Constant, Lambda, Multiply, One, Unity, Zero  # noqa: F401
 from .container import (  # noqa: F401
     Broadcast,
     BroadcastReduce,

continual/closure.py

@@ -2,6 +2,7 @@
 from inspect import getsource
 from typing import Callable, Union
 
+import torch
 from torch import Tensor, nn
 
 from .module import CoModule
@@ -95,3 +96,17 @@ def _unity(x: Tensor):
 def Unity() -> Lambda:
     """Create Lambda with addition function"""
     return Lambda(_unity)
+
+
+def Constant(constant: float):
+    return Lambda(lambda x: constant * torch.ones_like(x))
+
+
+def Zero() -> Lambda:
+    """Create Lambda with zero output"""
+    return Lambda(torch.zeros_like)
+
+
+def One() -> Lambda:
+    """Create Lambda with zero output"""
+    return Lambda(torch.ones_like)

setup.py

@@ -25,7 +25,7 @@ def from_file(file_name: str = "requirements.txt", comment_char: str = "#"):
 
 setup(
     name="continual-inference",
-    version="0.11.4",
+    version="0.12.0",
     description="Building blocks for Continual Inference Networks in PyTorch",
     long_description=long_description(),
     long_description_content_type="text/markdown",

tests/continual/test_closure.py

@@ -1,6 +1,6 @@
 import torch
 
-from continual.closure import Add, Lambda, Multiply, Unity
+from continual.closure import Add, Constant, Lambda, Multiply, One, Unity, Zero
 
 
 def test_add():
@@ -76,3 +76,19 @@ def local_always42(x):
 def test_unity():
     x = torch.ones((1, 1, 2, 2))
     assert torch.equal(x, Unity()(x))
+
+
+def test_constant():
+    x = torch.randn((1, 1, 2, 2))
+    const = 42
+    assert torch.equal(const * torch.ones_like(x), Constant(const)(x))
+
+
+def test_zero():
+    x = torch.randn((1, 1, 2, 2))
+    assert torch.equal(torch.zeros_like(x), Zero()(x))
+
+
+def test_one():
+    x = torch.randn((1, 1, 2, 2))
+    assert torch.equal(torch.ones_like(x), One()(x))