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andyl7anThe Meridian Authors
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Update TensorFlow Probability dependency to tfp-nightly.
PiperOrigin-RevId: 875794368
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.github/workflows/ci.yml

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@@ -78,7 +78,7 @@ jobs:
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strategy:
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max-parallel: 8
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matrix:
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python-version: ["3.10", "3.11", "3.12", "3.13"]
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python-version: ["3.11", "3.12", "3.13"]
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meridian-backend: ["tensorflow", "jax"]
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}-${{ matrix.python-version }}-${{ matrix.meridian-backend }}

meridian/schema/processors/reach_frequency_optimization_processor.py

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@@ -447,7 +447,7 @@ def _create_frequency_outcome_grid(
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aggregated_reach = backend.einsum(
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f"{input_tensor_dims}->...{output_tensor_dims}", filtered_reach
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)
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reach = aggregated_reach.numpy()[-1]
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reach = np.asarray(aggregated_reach)[-1]
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metric_data_array = optimal_frequency_dataset[constants.ROI].sel(
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frequency=frequency, rf_channel=channel

pyproject.toml

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@@ -7,7 +7,7 @@ description = """\
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your return on investment and direct your ad spend with confidence. \
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"""
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readme = "README.md"
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requires-python = ">=3.10"
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requires-python = ">=3.11"
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license-files = ["LICENSE"]
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authors = [
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{name = "The Meridian Authors", email="no-reply@google.com"},
@@ -34,8 +34,8 @@ dependencies = [
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"pandas >= 2.2.2, < 3",
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"scipy >= 1.13.1, < 2",
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"statsmodels >= 0.14.5",
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"tensorflow >= 2.18, < 2.21",
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"tensorflow-probability >= 0.25, < 0.26",
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"tensorflow >= 2.19.0, < 2.21",
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"tfp-nightly == 0.26.0.dev20260130",
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"tf-keras >= 2.18, < 2.21",
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"xarray",
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]
@@ -66,17 +66,17 @@ colab = [
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# GPU deps
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# Installed through `pip install -e .[and-cuda]`
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and-cuda = [
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"tensorflow[and-cuda] >= 2.18, < 2.21",
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"tensorflow[and-cuda] >= 2.19.0, < 2.21",
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]
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# MLflow deps
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# Installed through `pip install -e .[mlflow]`
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mlflow = ["mlflow"]
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# JAX backend dependencies.
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# Installed through `pip install -e .[jax]`
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jax = [
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"jax==0.5.3",
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"jaxlib==0.5.3",
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"tensorflow-probability[substrates-jax]==0.25.0",
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"jax==0.7.2",
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"jaxlib==0.7.2",
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"tfp-nightly[substrates-jax]==0.26.0.dev20260130",
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]
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# MMM proto schema.
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schema = [

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