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Remove KerasCV and KerasNLP; new structure for KerasHub and KerasTuner #1993

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Rework templates for new structure
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mattdangerw committed Nov 23, 2024
commit 8975e76dfa77ef0b5c0f2750e77ae6ba9b1657de
5 changes: 3 additions & 2 deletions .gitignore
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Expand Up @@ -11,7 +11,8 @@ templates/examples/rl/*
templates/examples/keras_recipes/*
templates/examples/timeseries/*
templates/examples/graph/*
templates/guides/**/*.md
templates/keras-tuner/getting_started.md
templates/**/guides/**/*.md
templates/keras_hub/getting_started.md
templates/keras_tuner/getting_started.md
datasets/*
.vscode/*
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9 changes: 0 additions & 9 deletions templates/api/keras_hub/models/xlm_roberta/index.md

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3 changes: 2 additions & 1 deletion templates/examples/audio/stft.md
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Expand Up @@ -6,7 +6,7 @@
**Description:** Introducing the `STFTSpectrogram` layer to extract spectrograms for audio classification.


<div class='example_version_banner keras_3'>ⓘ This example uses Keras 3</div>
<div class='example_version_banner keras_2'>ⓘ This example uses Keras 2</div>
<img class="k-inline-icon" src="https://colab.research.google.com/img/colab_favicon.ico"/> [**View in Colab**](https://colab.research.google.com/github/keras-team/keras-io/blob/master/examples/audio/ipynb/stft.ipynb) <span class="k-dot">•</span><img class="k-inline-icon" src="https://github.com/favicon.ico"/> [**GitHub source**](https://github.com/keras-team/keras-io/blob/master/examples/audio/stft.py)


Expand Down Expand Up @@ -1819,3 +1819,4 @@ print(f"2D model with trainable STFT -> Test Accuracy: {test_acc * 100:.2f}%")




5 changes: 4 additions & 1 deletion templates/examples/audio/transformer_asr.md
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Expand Up @@ -36,6 +36,7 @@ as proposed in the paper, "Attention is All You Need".

```python

import re
import os

os.environ["KERAS_BACKEND"] = "tensorflow"
Expand All @@ -45,6 +46,8 @@ import tensorflow as tf
import keras
from keras import layers

pattern_wav_name = re.compile(r'([^/\\\.]+)')

```

---
Expand Down Expand Up @@ -328,7 +331,7 @@ def get_data(wavs, id_to_text, maxlen=50):
"""returns mapping of audio paths and transcription texts"""
data = []
for w in wavs:
id = w.split("/")[-1].split(".")[0]
id = pattern_wav_name.split(w)[-4]
if len(id_to_text[id]) < maxlen:
data.append({"audio": w, "text": id_to_text[id]})
return data
Expand Down
7 changes: 0 additions & 7 deletions templates/guides/keras_cv/index.md

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7 changes: 0 additions & 7 deletions templates/guides/keras_hub/index.md

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