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auto: Rebuild docs.
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jupyter_execute/_examples/Covid19_Initial_Posterior_Estimation.ipynb

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},
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{
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"cell_type": "markdown",
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"id": "de5ccdf8",
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"id": "f436067e",
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"metadata": {},
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"source": [
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"## Table of Contents\n",

jupyter_execute/_examples/Linear_Regression_Starter.ipynb

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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from pathlib import Path\n",
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"\n",
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"import keras\n",
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"import bayesflow as bf"
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"outputs": [],
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"source": [
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"# Recommended - full serialization (checkpoints folder must exist)\n",
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"workflow.approximator.save(filepath=\"checkpoints/regression.keras\")\n",
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"filepath = Path(\"checkpoints\") / \"regression.keras\"\n",
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"filepath.parent.mkdir(exist_ok=True)\n",
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"workflow.approximator.save(filepath=filepath)\n",
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"\n",
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"# Not recommended due to adapter mismatches - weights only\n",
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"# approximator.save_weights(filepath=\"checkpoints/regression.h5\")"
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"outputs": [],
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"source": [
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"# Load approximator\n",
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"approximator = keras.saving.load_model(\"checkpoints/regression.keras\")"
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"approximator = keras.saving.load_model(filepath)"
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]
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},
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{

jupyter_execute/_examples/Lotka_Volterra_Point_Estimation_and_Expert_Stats.ipynb

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"source": [
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from pathlib import Path\n",
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"import seaborn as sns\n",
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"\n",
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"import scipy\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"checkpoint_path = \"checkpoints/model.keras\"\n",
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"checkpoint_path = Path(\"checkpoints\") / \"model.keras\"\n",
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"checkpoint_path.parent.mkdir(exist_ok=True)\n",
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"keras.saving.save_model(point_inference_workflow.approximator, checkpoint_path)"
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]
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},

main/.buildinfo

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# Sphinx build info version 1
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# This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 273de479dc7c41a9f5f267771e4254e0
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config: 453ff87bcc54e90502c6822856638e3a
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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