257 lines
8.1 KiB
Python
257 lines
8.1 KiB
Python
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import numpy as np
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import pytest
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from tensorflow.python.ops.numpy_ops import np_config
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from keras_core import testing
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from keras_core.backend import backend
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from keras_core.backend.keras_tensor import KerasTensor
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from keras_core.operations import nn as knn
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@pytest.mark.skipif(
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backend() != "tensorflow",
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reason="Dynamic shapes are only supported in TensorFlow backend.",
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)
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class NNOpsDynamicShapeTest(testing.TestCase):
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def test_relu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.relu(x).shape, (None, 2, 3))
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def test_relu6(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.relu6(x).shape, (None, 2, 3))
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def test_sigmoid(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.sigmoid(x).shape, (None, 2, 3))
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def test_softplus(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.softplus(x).shape, (None, 2, 3))
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def test_softsign(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.softsign(x).shape, (None, 2, 3))
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def test_silu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.silu(x).shape, (None, 2, 3))
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def test_swish(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.swish(x).shape, (None, 2, 3))
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def test_log_sigmoid(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.log_sigmoid(x).shape, (None, 2, 3))
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def test_leaky_relu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.leaky_relu(x).shape, (None, 2, 3))
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def test_hard_sigmoid(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.hard_sigmoid(x).shape, (None, 2, 3))
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def test_elu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.elu(x).shape, (None, 2, 3))
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def test_selu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.selu(x).shape, (None, 2, 3))
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def test_gelu(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.gelu(x).shape, (None, 2, 3))
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def test_softmax(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.softmax(x).shape, (None, 2, 3))
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self.assertEqual(knn.softmax(x, axis=1).shape, (None, 2, 3))
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self.assertEqual(knn.softmax(x, axis=-1).shape, (None, 2, 3))
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def test_log_softmax(self):
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x = KerasTensor([None, 2, 3])
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self.assertEqual(knn.log_softmax(x).shape, (None, 2, 3))
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self.assertEqual(knn.log_softmax(x, axis=1).shape, (None, 2, 3))
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self.assertEqual(knn.log_softmax(x, axis=-1).shape, (None, 2, 3))
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class NNOpsStaticShapeTest(testing.TestCase):
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def test_relu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.relu(x).shape, (1, 2, 3))
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def test_relu6(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.relu6(x).shape, (1, 2, 3))
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def test_sigmoid(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.sigmoid(x).shape, (1, 2, 3))
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def test_softplus(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.softplus(x).shape, (1, 2, 3))
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def test_softsign(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.softsign(x).shape, (1, 2, 3))
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def test_silu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.silu(x).shape, (1, 2, 3))
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def test_swish(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.swish(x).shape, (1, 2, 3))
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def test_log_sigmoid(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.log_sigmoid(x).shape, (1, 2, 3))
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def test_leaky_relu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.leaky_relu(x).shape, (1, 2, 3))
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def test_hard_sigmoid(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.hard_sigmoid(x).shape, (1, 2, 3))
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def test_elu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.elu(x).shape, (1, 2, 3))
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def test_selu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.selu(x).shape, (1, 2, 3))
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def test_gelu(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.gelu(x).shape, (1, 2, 3))
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def test_softmax(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.softmax(x).shape, (1, 2, 3))
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self.assertEqual(knn.softmax(x, axis=1).shape, (1, 2, 3))
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self.assertEqual(knn.softmax(x, axis=-1).shape, (1, 2, 3))
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def test_log_softmax(self):
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x = KerasTensor([1, 2, 3])
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self.assertEqual(knn.log_softmax(x).shape, (1, 2, 3))
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self.assertEqual(knn.log_softmax(x, axis=1).shape, (1, 2, 3))
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self.assertEqual(knn.log_softmax(x, axis=-1).shape, (1, 2, 3))
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class NNOpsCorrectnessTest(testing.TestCase):
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def test_relu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(knn.relu(x), [0, 0, 1, 2, 3])
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def test_relu6(self):
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x = np.array([-1, 0, 1, 2, 3, 4, 5, 6, 7], dtype=np.float32)
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self.assertAllClose(knn.relu6(x), [0, 0, 1, 2, 3, 4, 5, 6, 6])
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def test_sigmoid(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.sigmoid(x), [0.26894143, 0.5, 0.7310586, 0.880797, 0.95257413]
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)
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def test_softplus(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.softplus(x),
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[0.31326166, 0.6931472, 1.3132616, 2.126928, 3.0485873],
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)
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def test_softsign(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(knn.softsign(x), [-0.5, 0, 0.5, 0.6666667, 0.75])
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def test_silu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.silu(x),
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[-0.26894143, 0, 0.7310586, 1.7615942, 2.8577223],
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)
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def test_swish(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.swish(x), [-0.26894143, 0.0, 0.7310586, 1.7615943, 2.8577223]
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)
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def test_log_sigmoid(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.log_sigmoid(x),
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[-1.3132616, -0.6931472, -0.31326166, -0.126928, -0.04858732],
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)
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def test_leaky_relu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.leaky_relu(x),
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[-0.2, 0, 1, 2, 3],
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)
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def test_hard_sigmoid(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.hard_sigmoid(x),
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[0.33333334, 0.5, 0.6666667, 0.8333334, 1.0],
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)
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def test_elu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.elu(x),
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[-0.63212055, 0, 1, 2, 3],
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)
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def test_selu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.selu(x),
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[-1.1113307, 0.0, 1.050701, 2.101402, 3.152103],
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)
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def test_gelu(self):
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x = np.array([-1, 0, 1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.gelu(x),
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[-0.15880796, 0.0, 0.841192, 1.9545977, 2.9963627],
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)
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def test_softmax(self):
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x = np.array([1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.softmax(x),
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[0.09003057, 0.24472848, 0.66524094],
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)
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self.assertAllClose(
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knn.softmax(x, axis=0),
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[0.09003057, 0.24472848, 0.66524094],
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)
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self.assertAllClose(
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knn.softmax(x, axis=-1),
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[0.09003057, 0.24472848, 0.66524094],
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)
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def test_log_softmax(self):
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x = np.array([1, 2, 3], dtype=np.float32)
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self.assertAllClose(
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knn.log_softmax(x),
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[-2.407606, -1.4076059, -0.4076059],
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)
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self.assertAllClose(
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knn.log_softmax(x, axis=0),
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[-2.407606, -1.4076059, -0.4076059],
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)
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self.assertAllClose(
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knn.log_softmax(x, axis=-1),
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[-2.407606, -1.4076059, -0.4076059],
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)
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