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| author | MathieuCarriere <mathieu.carriere3@gmail.com> | 2022-06-24 16:19:34 +0200 |
|---|---|---|
| committer | MathieuCarriere <mathieu.carriere3@gmail.com> | 2022-06-24 16:19:34 +0200 |
| commit | 370c09100d94dc73f582ebbabb994bcd2a3820eb (patch) | |
| tree | daae040b8079870772dffd7ab24a54d7b1b72387 /src/python/test | |
| parent | b93fbe5e7c246a6ee23a8686f9b5983624a6ab42 (diff) | |
changed dimensions into homology_dimensions
Diffstat (limited to 'src/python/test')
| -rw-r--r-- | src/python/test/test_diff.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/src/python/test/test_diff.py b/src/python/test/test_diff.py index e0a4717c..dca001a9 100644 --- a/src/python/test/test_diff.py +++ b/src/python/test/test_diff.py @@ -7,7 +7,7 @@ def test_rips_diff(): Xinit = np.array([[1.,1.],[2.,2.]], dtype=np.float32) X = tf.Variable(initial_value=Xinit, trainable=True) - rl = RipsLayer(maximum_edge_length=2., dimensions=[0]) + rl = RipsLayer(maximum_edge_length=2., homology_dimensions=[0]) with tf.GradientTape() as tape: dgm = rl.call(X)[0][0] @@ -19,7 +19,7 @@ def test_cubical_diff(): Xinit = np.array([[0.,2.,2.],[2.,2.,2.],[2.,2.,1.]], dtype=np.float32) X = tf.Variable(initial_value=Xinit, trainable=True) - cl = CubicalLayer(dimensions=[0]) + cl = CubicalLayer(homology_dimensions=[0]) with tf.GradientTape() as tape: dgm = cl.call(X)[0][0] @@ -31,7 +31,7 @@ def test_nonsquare_cubical_diff(): Xinit = np.array([[-1.,1.,0.],[1.,1.,1.]], dtype=np.float32) X = tf.Variable(initial_value=Xinit, trainable=True) - cl = CubicalLayer(dimensions=[0]) + cl = CubicalLayer(homology_dimensions=[0]) with tf.GradientTape() as tape: dgm = cl.call(X)[0][0] @@ -66,7 +66,7 @@ def test_st_diff(): Finit = np.array([6.,4.,3.,4.,5.,4.,3.,2.,3.,4.,5.], dtype=np.float32) F = tf.Variable(initial_value=Finit, trainable=True) - sl = LowerStarSimplexTreeLayer(simplextree=st, dimensions=[0]) + sl = LowerStarSimplexTreeLayer(simplextree=st, homology_dimensions=[0]) with tf.GradientTape() as tape: dgm = sl.call(F)[0][0] |