fix triplet ddp training

Summary: fixup precision alignment when triplet loss with ddp

fastreid/__init__.py

@@ -5,4 +5,4 @@
 """
 
 
-__version__ = "0.1.0"
+__version__ = "0.2.0"

fastreid/modeling/losses/triplet_loss.py

@@ -97,11 +97,11 @@ def triplet_loss(embedding, targets, margin, norm_feat, hard_mining):
         all_embedding = embedding
         all_targets = targets
 
-    dist_mat = euclidean_dist(embedding, all_embedding)
+    dist_mat = euclidean_dist(all_embedding, all_embedding)
 
-    N, M = dist_mat.size()
-    is_pos = targets.view(N, 1).expand(N, M).eq(all_targets.view(M, 1).expand(M, N).t())
-    is_neg = targets.view(N, 1).expand(N, M).ne(all_targets.view(M, 1).expand(M, N).t())
+    N, N = dist_mat.size()
+    is_pos = all_targets.view(N, 1).expand(N, N).eq(all_targets.view(N, 1).expand(N, N).t())
+    is_neg = all_targets.view(N, 1).expand(N, N).ne(all_targets.view(N, 1).expand(N, N).t())
 
     if hard_mining:
         dist_ap, dist_an = hard_example_mining(dist_mat, is_pos, is_neg)

fastreid/utils/visualizer.py

@@ -66,7 +66,7 @@ class Visualizer:
             plt.clf()
             ax = fig.add_subplot(1, max_rank + 1, 1)
             ax.imshow(query_img)
-            ax.set_title('{}/{:.2f}/cam{}'.format(query_name, self.all_ap[q_idx], cam_id))
+            ax.set_title('{:.4f}/cam{}'.format(self.all_ap[q_idx], cam_id))
             ax.axis("off")
             for i in range(max_rank):
                 if vis_label:
@@ -112,7 +112,7 @@ class Visualizer:
             #         axes.flat[i].imshow(acts[i], alpha=0.3, cmap='jet')
             if vis_label:
                 label_indice = np.where(cmc == 1)[0]
-                if label_sort == "ascending":   label_indice = label_indice[::-1]
+                if label_sort == "ascending": label_indice = label_indice[::-1]
                 label_indice = label_indice[:max_rank]
                 for i in range(max_rank):
                     if i >= len(label_indice): break
@@ -176,9 +176,9 @@ class Visualizer:
         self.plot_roc_curve(fpr, tpr)
         filepath = os.path.join(output, "roc.jpg")
         plt.savefig(filepath)
-        self.plot_distribution(pos, neg)
-        filepath = os.path.join(output, "pos_neg_dist.jpg")
-        plt.savefig(filepath)
+        # self.plot_distribution(pos, neg)
+        # filepath = os.path.join(output, "pos_neg_dist.jpg")
+        # plt.savefig(filepath)
         return fpr, tpr, pos, neg
 
     @staticmethod