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Fix Typos in research_tools.ipynb Documentation #894

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Merged
merged 4 commits into from
Sep 12, 2025
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Fix Typos in research_tools.ipynb Documentation #894

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aba2eaa
Fix: Convert set to list for random.sample() for Python 3.11 compatib…
Aniketsy Sep 3, 2025
a33d17d
Fix typos in research_tools.ipynb
Aniketsy Sep 3, 2025
48a461e
Fix typos in research_tools.ipynb
Aniketsy Sep 3, 2025
c283fdd
Merge branch 'master' into fix-typos-research-tools
mhucka Sep 4, 2025
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8 changes: 4 additions & 4 deletions docs/tutorials/research_tools.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@
"TensorFlow Quantum brings quantum primitives into the TensorFlow ecosystem. Now quantum researchers can leverage tools from TensorFlow. In this tutorial you will take a closer look at incorporating [TensorBoard](https://www.tensorflow.org/tensorboard) into your quantum computing research. Using the [DCGAN tutorial](https://www.tensorflow.org/tutorials/generative/dcgan) from TensorFlow you will quickly build up working experiments and visualizations similar to ones done by [Niu et al.](https://arxiv.org/pdf/2010.11983.pdf). Broadly speaking you will:\n",
"\n",
"1. Train a GAN to produce samples that look like they came from quantum circuits.\n",
"2. Visualize the training progress as well as distribuion evolution over time.\n",
"2. Visualize the training progress as well as distribution evolution over time.\n",
"3. Benchmark the experiment by exploring the compute graph."
]
},
Expand Down Expand Up @@ -356,7 +356,7 @@
"\n",
"\n",
"def make_discriminator_model():\n",
" \"\"\"Constrcut discriminator model.\"\"\"\n",
" \"\"\"Construct discriminator model.\"\"\"\n",
" model = tf.keras.Sequential()\n",
" model.add(layers.Dense(256, use_bias=False, input_shape=(N_QUBITS,)))\n",
" model.add(layers.Dense(128, activation='relu'))\n",
Expand Down Expand Up @@ -538,7 +538,7 @@
"id": "4ceb5dc64798"
},
"source": [
"## 3. Vizualize training and performance\n",
"## 3. Visualize training and performance\n",
"\n",
"The TensorBoard dashboard can now be launched with:"
]
Expand Down Expand Up @@ -901,7 +901,7 @@
"id": "0ab7afeef60f"
},
"source": [
"When calling `train` the TensoBoard dashboard will auto-update with all of the summary statistics given in the training loop."
"When calling `train` the TensorBoard dashboard will auto-update with all of the summary statistics given in the training loop."
]
},
{
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