63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import numpy as np
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from keras_core import backend
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from keras_core import testing
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from keras_core.layers.layer import Layer
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class LayerTest(testing.TestCase):
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def test_positional_arg_error(self):
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class SomeLayer(Layer):
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def call(self, x, bool_arg):
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if bool_arg:
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return x
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return x + 1
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x = backend.KerasTensor(shape=(2, 3), name="x")
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with self.assertRaisesRegex(
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ValueError, "Only input tensors may be passed as"
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):
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SomeLayer()(x, True)
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# This works
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SomeLayer()(x, bool_arg=True)
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def test_rng_seed_tracking(self):
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class RNGLayer(Layer):
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def __init__(self):
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super().__init__()
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self.seed_gen = backend.random.SeedGenerator(seed=1337)
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def call(self, x):
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return backend.random.dropout(x, rate=0.5, seed=self.seed_gen)
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layer = RNGLayer()
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self.assertEqual(layer.variables, [layer.seed_gen.state])
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self.assertAllClose(layer.variables[0], [1337, 0])
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layer(np.ones((3, 4)))
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self.assertAllClose(layer.variables[0], [1337, 1])
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# Test tracking in list attributes.
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class RNGListLayer(Layer):
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def __init__(self):
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super().__init__()
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self.seed_gens = []
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self.seed_gens.append(backend.random.SeedGenerator(seed=1))
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self.seed_gens.append(backend.random.SeedGenerator(seed=10))
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def call(self, x):
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x = backend.random.dropout(x, rate=0.5, seed=self.seed_gens[0])
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x = backend.random.dropout(x, rate=0.5, seed=self.seed_gens[1])
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return x
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layer = RNGListLayer()
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self.assertEqual(
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layer.variables,
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[layer.seed_gens[0].state, layer.seed_gens[1].state],
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)
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self.assertAllClose(layer.variables[0], [1, 0])
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self.assertAllClose(layer.variables[1], [10, 0])
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layer(np.ones((3, 4)))
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self.assertAllClose(layer.variables[0], [1, 1])
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self.assertAllClose(layer.variables[1], [10, 1])
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