keras/keras_core/random/seed_generator.py
2023-06-03 10:36:42 -07:00

56 lines
1.6 KiB
Python

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