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deepcore/methods/methods_utils/cossim.py

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+import numpy as np
+import torch
+
+
+def cossim_np(v1, v2):
+    # return cossim(torch.tensor(v1),torch.tensor(v2)).cpu().numpy()
+    num = np.dot(v1, v2.T)
+    denom = np.linalg.norm(v1, axis=1).reshape(-1, 1) * np.linalg.norm(v2, axis=1)
+    res = num / (denom + 1e-6)
+    res[np.isneginf(res)] = 0.
+    return 0.5 + 0.5 * res
+
+def cossim_pair_np(v1):
+    num = np.dot(v1, v1.T)
+    norm = np.linalg.norm(v1, axis=1)
+    denom = norm.reshape(-1, 1) * norm
+    res = num / (denom + 1e-6)
+    res[np.isneginf(res)] = 0.
+    return 0.5 + 0.5 * res
+
+def cossim(v1, v2):
+    num = torch.matmul(v1, v2.T)
+    denom = torch.norm(v1, dim=1).view(-1, 1) * torch.norm(v2, dim=1)
+    res = num / (denom + 1e-6)
+    res[torch.isneginf(res)] = 0.
+    return 0.5 + 0.5 * res
+
+def cossim_pair(v1):
+    num = torch.matmul(v1, v1.T)
+    norm = torch.norm(v1, dim=1)
+    denom = norm.view(-1, 1) * norm
+    res = num / (denom + 1e-6)
+    res[torch.isneginf(res)] = 0.
+    return 0.5 + 0.5 * res
+