49 lines
1.4 KiB
Python
49 lines
1.4 KiB
Python
import random as python_random
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from keras_core.api_export import keras_core_export
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@keras_core_export("keras_core.random.SeedGenerator")
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class SeedGenerator:
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def __init__(self, seed):
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from keras_core.backend import Variable
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if seed is None:
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seed = make_default_seed()
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if not isinstance(seed, int):
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raise ValueError(
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"Argument `seed` must be an integer. " f"Received: seed={seed}"
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)
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def seed_initializer(*args, **kwargs):
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return [seed, 0]
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self.state = Variable(
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seed_initializer, shape=(2,), dtype="uint32", trainable=False
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)
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def make_default_seed():
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return python_random.randint(1, int(1e9))
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def draw_seed(seed):
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from keras_core.backend import convert_to_tensor
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if isinstance(seed, SeedGenerator):
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# Use * 1 to create a copy
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new_seed_value = seed.state.value * 1
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seed.state.assign(
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seed.state + convert_to_tensor([0, 1], dtype="uint32")
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)
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return new_seed_value
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elif isinstance(seed, int):
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return convert_to_tensor([seed, 0], dtype="uint32")
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elif seed is None:
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return convert_to_tensor([make_default_seed(), 0], dtype="uint32")
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raise ValueError(
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"Argument `seed` must be either an integer "
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"or an instance of `SeedGenerator`. "
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f"Received: seed={seed} (of type {type(seed)})"
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)
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