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SECURITY.md
to the network can execute arbitrary code with the privileges of the user running the `tf.train.Server`. ## Untrusted inputs during training and prediction TensorFlow supports a wide range of input data formats. For example it can process images, audio, videos, and text. There are several modules specialized in taking those formats, modifying them, and/or converting them to intermediate
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RELEASE.md
`DynamicUpdateSlice`. * Enabled a new MLIR-based dynamic range quantization backend by default * The new backend is used for post-training int8 dynamic range quantization and post-training float16 quantization. * Set `experimental_new_dynamic_range_quantizer` in tf.lite.TFLiteConverter to False to disable this change
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