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@@ 64-85 (lines=22) @@
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) |
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assert is_equal_tf(got, expected) |
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def test_2d(self): |
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weights = tf.constant(np.array([[0.2], [0.3]], dtype=np.float32)) |
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values = tf.constant( |
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np.array( |
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[ |
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[1], # value at corner (0, 0), weight = 0.2 * 0.3 |
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[2], # value at corner (0, 1), weight = 0.2 * 0.7 |
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[3], # value at corner (1, 0), weight = 0.8 * 0.3 |
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[4], # value at corner (1, 1), weight = 0.8 * 0.7 |
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], |
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dtype=np.float32, |
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) |
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) |
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# expected = 1 * 0.2 * 0.3 |
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# + 2 * 0.2 * 0.7 |
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# + 3 * 0.8 * 0.3 |
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# + 4 * 0.8 * 0.7 |
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expected = tf.constant(np.array([3.3], dtype=np.float32)) |
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got = layer_util.pyramid_combination( |
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values=values, weight_floor=weights, weight_ceil=1 - weights |
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) |
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assert is_equal_tf(got, expected) |
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def test_error_dim(self): |
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weights = tf.constant(np.array([[[0.2]], [[0.2]]], dtype=np.float32)) |
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@@ 53-62 (lines=10) @@
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class TestPyramidCombination: |
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def test_1d(self): |
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weights = tf.constant(np.array([[0.2]], dtype=np.float32)) |
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values = tf.constant(np.array([[1], [2]], dtype=np.float32)) |
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# expected = 1 * 0.2 + 2 * 2 |
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expected = tf.constant(np.array([1.8], dtype=np.float32)) |
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got = layer_util.pyramid_combination( |
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values=values, weight_floor=weights, weight_ceil=1 - weights |
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) |
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assert is_equal_tf(got, expected) |
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def test_2d(self): |
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weights = tf.constant(np.array([[0.2], [0.3]], dtype=np.float32)) |
DeepRegNet /
DeepReg
