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.tox | ||
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# MacOS | ||
.DS_Store | ||
.DS_Store |
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from . import ( | ||
approximators, | ||
configurators, | ||
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from .approximator import Approximator |
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import numpy as np | ||
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from bayesflow.types import Tensor | ||
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from .base_approximator import BaseApproximator | ||
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class NumpyApproximator(BaseApproximator): | ||
def train_step(self, data: dict[str, Tensor]) -> dict[str, Tensor]: | ||
raise NotImplementedError(f"Keras currently has no support for numpy training.") | ||
raise NotImplementedError("Keras currently has no support for numpy training.") |
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import tensorflow as tf | ||
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from bayesflow.types import Tensor | ||
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import torch | ||
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from .base_approximator import BaseApproximator | ||
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from .base_configurator import BaseConfigurator | ||
from .configurator import Configurator |
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from keras.saving import register_keras_serializable | ||
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from bayesflow.types import Tensor | ||
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from .offline_dataset import OfflineDataset | ||
from .online_dataset import OnlineDataset | ||
from .rounds_dataset import RoundsDataset | ||
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from .distribution import Distribution | ||
from .diagonal_normal import DiagonalNormal |
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import keras | ||
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from bayesflow.types import Shape, Tensor | ||
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from .coupling_flow import CouplingFlow | ||
from .deep_set import DeepSet | ||
from .flow_matching import FlowMatching | ||
from .inference_network import InferenceNetwork | ||
from .mlp import MLP | ||
from .resnet import ResNet | ||
from .lstnet import LSTNet | ||
from .summary_network import SummaryNetwork | ||
from .transformers import SetTransformer | ||
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from .inference_network import InferenceNetwork | ||
from .summary_network import SummaryNetwork |
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from .coupling_flow import CouplingFlow |
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