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Added 2 lines of code `import keras`, `@keras.saving.register_keras_serializable()` on top of the Keras Custom model definition because it shows typeerror - "Make sure custom classes are decorated with `@keras.saving.register_keras_serializable()`" after reloading the model when saving as `.keras`. As mentioned in this Saving [Custom objects](https://www.tensorflow.org/guide/keras/serialization_and_saving#custom_objects) definition. Please refer to this replicated working code [gist](https://colab.research.google.com/gist/RenuPatelGoogle/f124503c52144c5ed6e9c79cffcb593d/intro_to_modules.ipynb#scrollTo=hpW-4Dj3Q1Rb) for your reference. Thank you.
Added keras import on top of the code.
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In the boundless.ipynb file in the section: "Loading an image" there is a typo in the description: "We will load a sample image but fell free to upload your own image to the colab and try with it." but it should be "We will load a sample image but feel free to upload your own image to the colab and try with it." the change is from "fell" to the corrected "feel"
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bug fix ValueError: Multi-dimensional indexing (e.g. `obj[:, None]`) is no longer supported. Convert to a numpy array before indexing instead.
This page contains hyperlink for Mnist dataset which is actually asking for credentials now. IMO, for this page the hyperlink may not required.Hence I propose to delete the hyperlink. Fixes TF ticket #62306 Thanks!
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…ntation, and fix other issues in the docs as well. PiperOrigin-RevId: 585777041
…s when installing TensorFlow with cuda support. PiperOrigin-RevId: 586819519
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… invalid escape sequence. PiperOrigin-RevId: 839358055
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chore: migrate gsutil to gcloud storage
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…_execution > 1` When `steps_per_execution > 1` is set in `Model.compile`, Keras runs `steps_per_execution` batches inside a single on-device `tf.range` loop per `tf.function` call. Add a note and code example explaining how to pass `validation_steps` (and drop partial batches) on finite validation datasets so TPU replicas do not hit `EOF` mid-execution and hang. PiperOrigin-RevId: 994034385
`FieldDescriptor.label` was deprecated in protobuf 6.31 and removed in Python protobuf 7.x (36.x) in favor of `FieldDescriptor.is_repeated` and `FieldDescriptor.is_required`. Check for `is_repeated` and `is_required` first and fall back to `field.label` only on older protobuf versions (< 6.31). PiperOrigin-RevId: 1002774147
…and update Java documentation links. Fixes #96799 PiperOrigin-RevId: 1007523976
…patibility. Several TensorFlow guide and TF Hub tutorial notebooks fail under TensorFlow 2.21 and Keras 3 due to stricter weight filename checks, custom layer input coercion, and removed TF1 Hub APIs. * Add the required `.weights.h5` extension when saving model weights, build subclassed models before saving weights, create layer weights with `self.add_weight`, and pass tensor inputs to custom Keras layers in the guide notebooks. * Configure legacy Keras (`tf-keras`) in the extension type guide and TF Hub image feature vector tutorials where legacy behavior or `ExtensionType` inputs are used. * Unpin `tensorflow-text` and replace removed TF1 Hub module calls with `hub.load` and `tf.compat.v1` in the TF Hub tutorials. PiperOrigin-RevId: 1012491183
…on 3.11 compatibility. Several TensorFlow guide, TF Hub, and core tutorial notebooks fail during scheduled Kokoro execution due to removed APIs in Keras 3, Matplotlib 3.9+, IPython 8+, and NumPy 2.0, as well as outdated Python 3.10 package pins and archive extraction paths. * Update `basic_training_loops.ipynb`, `checkpoint.ipynb`, `data_performance.ipynb`, and `effective_tf2.ipynb` for Keras 3 loss, metric, and RNN cell APIs, `super()` initialization, `get_cmap`, and `TF_USE_LEGACY_KERAS=1` where low-level TF2 checkpoint keys are inspected. * Update the TF Hub tutorial notebooks to use public IPython display imports, `buffer_rgba` canvas rendering, scalar PSNR squeezing, a Wikimedia-compliant HTTP request header, and unpinned Python 3.11 and `protobuf` dependencies. * Update the core tutorial notebooks to enable recursive globbing in `glob.glob`, unwrap NumPy and TensorFlow scalar arguments, bump the Oxford-IIIT Pet dataset version, and resolve extracted CSV directory paths from `get_file`. PiperOrigin-RevId: 1013992537
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