Debug negative sampling.

tests/triacontagon/test_sampling.py

@@ -2,7 +2,8 @@ from triacontagon.data import Data
 from triacontagon.sampling import fixed_unigram_candidate_sampler, \
     get_true_classes, \
     negative_sample_adj_mat, \
-    negative_sample_data
+    negative_sample_data, \
+    get_edges_and_degrees
 from triacontagon.decode import dedicom_decoder
 import torch
 import time
@@ -22,6 +23,29 @@ def test_fixed_unigram_candidate_sampler_01():
     print('res:', res)
 
 
+def test_fixed_unigram_candidate_sampler_02():
+    foo_bar = torch.tensor([
+        [0, 1, 0, 1],
+        [0, 0, 0, 1],
+        [0, 1, 0, 0],
+        [1, 0, 0, 0],
+        [0, 0, 1, 1]
+    ], dtype=torch.float32)
+
+    # bar_foo = foo_bar.transpose(0, 1).to_sparse().coalesce()
+    bar_foo = foo_bar.to_sparse().coalesce()
+
+    true_classes, row_count = get_true_classes(bar_foo)
+    print('true_classes:', true_classes)
+    print('row_count:', row_count)
+
+    edges_pos, degrees = get_edges_and_degrees(bar_foo)
+
+    res = fixed_unigram_candidate_sampler(true_classes, row_count,
+        degrees, 0.75)
+    print('res:', res)
+
+
 def test_get_true_classes_01():
     adj_mat = torch.tensor([
         [0, 1, 0, 1, 0],