--- a
+++ b/utils/ramps.py
@@ -0,0 +1,41 @@
+# Copyright (c) 2018, Curious AI Ltd. All rights reserved.
+#
+# This work is licensed under the Creative Commons Attribution-NonCommercial
+# 4.0 International License. To view a copy of this license, visit
+# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
+# Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
+
+"""Functions for ramping hyperparameters up or down
+
+Each function takes the current training step or epoch, and the
+ramp length in the same format, and returns a multiplier between
+0 and 1.
+"""
+
+
+import numpy as np
+
+
+def sigmoid_rampup(current, rampup_length):
+    """Exponential rampup from https://arxiv.org/abs/1610.02242"""
+    if rampup_length == 0:
+        return 1.0
+    else:
+        current = np.clip(current, 0.0, rampup_length)
+        phase = 1.0 - current / rampup_length
+        return float(np.exp(-5.0 * phase * phase))
+
+
+def linear_rampup(current, rampup_length):
+    """Linear rampup"""
+    assert current >= 0 and rampup_length >= 0
+    if current >= rampup_length:
+        return 1.0
+    else:
+        return current / rampup_length
+
+
+def cosine_rampdown(current, rampdown_length):
+    """Cosine rampdown from https://arxiv.org/abs/1608.03983"""
+    assert 0 <= current <= rampdown_length
+    return float(.5 * (np.cos(np.pi * current / rampdown_length) + 1))