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The TensorFlow Datasets Authors
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Automated documentation update.
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‎docs/catalog/imdb_reviews.md

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@@ -25,6 +25,8 @@ and 25,000 for testing. There is additional unlabeled data for use as well.
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<span class="material-icons icon-after" aria-hidden="true"> north_east
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</span> </a>
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* **Config description**: Plain text
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* **Homepage**:
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[http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/)
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@@ -36,35 +38,6 @@ and 25,000 for testing. There is additional unlabeled data for use as well.
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* **`1.0.0`** (default): New split API
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(https://tensorflow.org/datasets/splits)
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* **Supervised keys** (See
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[`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
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`('text', 'label')`
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* **Figure**
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([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
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Not supported.
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* **Citation**:
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```
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@InProceedings{maas-EtAl:2011:ACL-HLT2011,
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author = {Maas, Andrew L. and Daly, Raymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y. and Potts, Christopher},
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title = {Learning Word Vectors for Sentiment Analysis},
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booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
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month = {June},
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year = {2011},
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address = {Portland, Oregon, USA},
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publisher = {Association for Computational Linguistics},
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pages = {142--150},
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url = {http://www.aclweb.org/anthology/P11-1015}
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}
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```
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## imdb_reviews/plain_text (default config)
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* **Config description**: Plain text
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* **Download size**: `80.23 MiB`
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* **Dataset size**: `129.83 MiB`
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label | ClassLabel | | int64 |
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text | Text | | string |
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* **Examples**
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([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):
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<!-- mdformat off(HTML should not be auto-formatted) -->
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{% framebox %}
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<button id="displaydataframe">Display examples...</button>
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<div id="dataframecontent" style="overflow-x:auto"></div>
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<script>
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const url = "https://storage.googleapis.com/tfds-data/visualization/dataframe/imdb_reviews-plain_text-1.0.0.html";
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const dataButton = document.getElementById('displaydataframe');
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dataButton.addEventListener('click', async () => {
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// Disable the button after clicking (dataframe loaded only once).
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dataButton.disabled = true;
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const contentPane = document.getElementById('dataframecontent');
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try {
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const response = await fetch(url);
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// Error response codes don't throw an error, so force an error to show
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// the error message.
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if (!response.ok) throw Error(response.statusText);
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const data = await response.text();
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contentPane.innerHTML = data;
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} catch (e) {
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contentPane.innerHTML =
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'Error loading examples. If the error persist, please open '
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+ 'a new issue.';
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}
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});
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</script>
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{% endframebox %}
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<!-- mdformat on -->
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## imdb_reviews/bytes
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* **Config description**: Uses byte-level text encoding with
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`tfds.deprecated.text.ByteTextEncoder`
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* **Download size**: `Unknown size`
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* **Dataset size**: `Unknown size`
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* **Auto-cached**
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([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
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Unknown
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* **Splits**:
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Split | Examples
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:---- | -------:
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* **Feature structure**:
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```python
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FeaturesDict({
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'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
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'text': Text(shape=(None,), dtype=int64, encoder=<ByteTextEncoder vocab_size=257>),
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})
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```
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* **Feature documentation**:
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* **Supervised keys** (See
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[`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
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`('text', 'label')`
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Feature | Class | Shape | Dtype | Description
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:------ | :----------- | :------ | :---- | :----------
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| FeaturesDict | | |
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label | ClassLabel | | int64 |
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text | Text | (None,) | int64 |
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* **Figure**
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([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
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Not supported.
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* **Examples**
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([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):
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<button id="displaydataframe">Display examples...</button>
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<div id="dataframecontent" style="overflow-x:auto"></div>
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<script>
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const url = "https://storage.googleapis.com/tfds-data/visualization/dataframe/imdb_reviews-bytes-1.0.0.html";
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const url = "https://storage.googleapis.com/tfds-data/visualization/dataframe/imdb_reviews-plain_text-1.0.0.html";
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const dataButton = document.getElementById('displaydataframe');
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dataButton.addEventListener('click', async () => {
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// Disable the button after clicking (dataframe loaded only once).
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<!-- mdformat on -->
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## imdb_reviews/subwords8k
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* **Config description**: Uses `tfds.deprecated.text.SubwordTextEncoder` with
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8k vocab size
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* **Download size**: `Unknown size`
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* **Dataset size**: `Unknown size`
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* **Auto-cached**
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([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
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Unknown
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* **Splits**:
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Split | Examples
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:---- | -------:
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* **Feature structure**:
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* **Citation**:
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```python
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FeaturesDict({
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'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
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'text': Text(shape=(None,), dtype=int64),
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})
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```
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* **Feature documentation**:
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Feature | Class | Shape | Dtype | Description
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:------ | :----------- | :------ | :---- | :----------
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| FeaturesDict | | |
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label | ClassLabel | | int64 |
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text | Text | (None,) | int64 |
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* **Examples**
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([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):
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<!-- mdformat off(HTML should not be auto-formatted) -->
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{% framebox %}
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<button id="displaydataframe">Display examples...</button>
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<div id="dataframecontent" style="overflow-x:auto"></div>
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<script>
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const url = "https://storage.googleapis.com/tfds-data/visualization/dataframe/imdb_reviews-subwords8k-1.0.0.html";
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const dataButton = document.getElementById('displaydataframe');
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dataButton.addEventListener('click', async () => {
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// Disable the button after clicking (dataframe loaded only once).
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dataButton.disabled = true;
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const contentPane = document.getElementById('dataframecontent');
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try {
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const response = await fetch(url);
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// Error response codes don't throw an error, so force an error to show
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// the error message.
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if (!response.ok) throw Error(response.statusText);
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const data = await response.text();
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contentPane.innerHTML = data;
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} catch (e) {
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contentPane.innerHTML =
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'Error loading examples. If the error persist, please open '
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+ 'a new issue.';
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}
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});
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</script>
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{% endframebox %}
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<!-- mdformat on -->
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## imdb_reviews/subwords32k
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* **Config description**: Uses `tfds.deprecated.text.SubwordTextEncoder` with
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32k vocab size
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* **Download size**: `Unknown size`
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* **Dataset size**: `Unknown size`
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* **Auto-cached**
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([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
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Unknown
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* **Splits**:
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Split | Examples
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:---- | -------:
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* **Feature structure**:
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```python
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FeaturesDict({
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'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
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'text': Text(shape=(None,), dtype=int64),
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})
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@InProceedings{maas-EtAl:2011:ACL-HLT2011,
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author = {Maas, Andrew L. and Daly, Raymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y. and Potts, Christopher},
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title = {Learning Word Vectors for Sentiment Analysis},
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booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
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month = {June},
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year = {2011},
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address = {Portland, Oregon, USA},
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publisher = {Association for Computational Linguistics},
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pages = {142--150},
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url = {http://www.aclweb.org/anthology/P11-1015}
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}
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```
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* **Feature documentation**:
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Feature | Class | Shape | Dtype | Description
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:------ | :----------- | :------ | :---- | :----------
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| FeaturesDict | | |
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label | ClassLabel | | int64 |
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text | Text | (None,) | int64 |
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* **Examples**
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([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):
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<!-- mdformat off(HTML should not be auto-formatted) -->
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{% framebox %}
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<button id="displaydataframe">Display examples...</button>
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<div id="dataframecontent" style="overflow-x:auto"></div>
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<script>
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const url = "https://storage.googleapis.com/tfds-data/visualization/dataframe/imdb_reviews-subwords32k-1.0.0.html";
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const dataButton = document.getElementById('displaydataframe');
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dataButton.addEventListener('click', async () => {
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// Disable the button after clicking (dataframe loaded only once).
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dataButton.disabled = true;
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const contentPane = document.getElementById('dataframecontent');
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try {
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const response = await fetch(url);
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// Error response codes don't throw an error, so force an error to show
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// the error message.
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if (!response.ok) throw Error(response.statusText);
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const data = await response.text();
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contentPane.innerHTML = data;
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} catch (e) {
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contentPane.innerHTML =
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'Error loading examples. If the error persist, please open '
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+ 'a new issue.';
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}
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});
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</script>
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{% endframebox %}
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<!-- mdformat on -->
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## imdb_reviews/plain_text (default config)

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