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4 changes: 2 additions & 2 deletions docs/notebooks/summary_tutorial.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -353,7 +353,7 @@
"source": [
"Then we can transform the `loss` function with the function transformation: `summary.with_summary_output_reduced`.\n",
"This transformation goes through the computation and extracts all the tagged values and returns them to us by name in a dictionary.\n",
"In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/tensorflow/probability/blob/main/spinoffs/oryx/oryx/core/interpreters/harvest.py)).\n",
"In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/jax-ml/oryx/tree/main/oryx/core/interpreters/harvest.py)).\n",
"When we wrap a function this, we return a tuple containing the original result, and a dictionary with the desired metrics."
]
},
Expand Down Expand Up @@ -893,7 +893,7 @@
"source": [
"def monitor(a):\n",
" summary.summary(\"with_input\", a)\n",
" summary.summary(\"constant\", 2.0)\n",
" summary.summary(\"constant\", jnp.asarray(2.0))\n",
" summary.summary(\"constant_with_inp\", 2.0 + (a * 0))\n",
" return a\n",
"\n",
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4 changes: 2 additions & 2 deletions docs/notebooks/summary_tutorial.md
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Expand Up @@ -112,7 +112,7 @@ def loss(parameters):

Then we can transform the `loss` function with the function transformation: `summary.with_summary_output_reduced`.
This transformation goes through the computation and extracts all the tagged values and returns them to us by name in a dictionary.
In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/tensorflow/probability/blob/main/spinoffs/oryx/oryx/core/interpreters/harvest.py)).
In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/jax-ml/oryx/tree/main/oryx/core/interpreters/harvest.py)).
When we wrap a function this, we return a tuple containing the original result, and a dictionary with the desired metrics.

```{code-cell}
Expand Down Expand Up @@ -399,7 +399,7 @@ outputId: b1ccd1db-5615-45b9-b52c-0ae78ea9369f
---
def monitor(a):
summary.summary("with_input", a)
summary.summary("constant", 2.0)
summary.summary("constant", jnp.asarray(2.0))
summary.summary("constant_with_inp", 2.0 + (a * 0))
return a

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5 changes: 3 additions & 2 deletions docs/notebooks/summary_tutorial.py
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Expand Up @@ -25,6 +25,7 @@
# kernelspec:
# display_name: Python 3
# name: python3
# pylint: disable=line-too-long
# ---

# + [markdown] id="ryqPvTKI19zH"
Expand Down Expand Up @@ -99,7 +100,7 @@ def loss(parameters):
# + [markdown] id="AL9_xgfR4yPS"
# Then we can transform the `loss` function with the function transformation: `summary.with_summary_output_reduced`.
# This transformation goes through the computation and extracts all the tagged values and returns them to us by name in a dictionary.
# In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/tensorflow/probability/blob/main/spinoffs/oryx/oryx/core/interpreters/harvest.py)).
# In implementation, all the hard work here is done by the wonderful `oryx` library (in particular [harvest](https://github.com/jax-ml/oryx/tree/main/oryx/core/interpreters/harvest.py)).
# When we wrap a function this, we return a tuple containing the original result, and a dictionary with the desired metrics.

# + colab={"base_uri": "https://localhost:8080/"} id="hZQkB6Um8PI5" outputId="984e4f64-7562-48ae-ca68-ff4014037553"
Expand Down Expand Up @@ -299,7 +300,7 @@ def loss(parameters):
# + colab={"base_uri": "https://localhost:8080/"} id="iIbrjrJ4HEd-" outputId="b1ccd1db-5615-45b9-b52c-0ae78ea9369f"
def monitor(a):
summary.summary("with_input", a)
summary.summary("constant", 2.0)
summary.summary("constant", jnp.asarray(2.0))
summary.summary("constant_with_inp", 2.0 + (a * 0))
return a

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