Google Developers Italia: Presentazione di TensorFlow 1.0

Local blog for Italian speaking developers

Presentazione di TensorFlow 1.0

20 febbraio 2017

primo annotraduzione linguisticaprevenzione della cecità nei diabetici6000 repository open source onlineTensorFlow Developer Summittrasmesso in diretta streaming in tutto il mondoTensorFlow 1.0È più veloce: XLAtensorflow.orgconsigli e suggerimentiÈ più flessibile:KerasÈ più "production-ready" che mai:quiTensorFlow 1.0

Le API Python sono state modificate per assomigliare di più a NumPy. Per questo e gli altri cambiamenti retrocompatibili apportati per sostenere la stabilità delle API in futuro, sei pregato di utilizzare la nostra pratica guida alla migrazione e lo script di conversione.

API sperimentali per Java e Go

I moduli API tf.layers, tf.metrics e tf.losses di livello più alto, presi da tf.contrib.learn dopo aver incorporato skflow e TF Slim.

La release sperimentale di XLA, un compilatore specifico di dominio per grafici TensorFlow rivolto a CPU e GPU. XLA è in rapida evoluzione, aspettati ulteriori miglioramenti nelle prossime versioni.

TensorFlow Debugger (tfdbg), un'interfaccia della riga di comando e un'API per il debugging live dei programmi TensorFlow.

Nuove demo Android per il rilevamento e la localizzazione di oggetti, e la stilizzazione di immagini basata su fotocamera.

Miglioramenti per l'installazione: sono state aggiunte immagini del Python 3 Docker e i pacchetti pip di TensorFlow sono stati resi conformi a PyPI. Ciò significa che da ora TensorFlow può essere installato con una semplice chiamata di pip install tensorflow.

Siamo entusiasti di vedere come la community Tensorflow si stia sviluppando velocemente in tutto il mondo. Per approfondire la tua conoscenza di Tensorflow 1.0 e dei suoi utilizzi, vieni a vedere le sessioni del TensorFlow Developer Summit su YouTube, incentrate sui recenti aggiornamenti, dalle API di livello più alto e TensorFlow su mobile al nostro nuovo compilatore XLA, oltre a tutti gli altri modi intelligenti di utilizzare TensorFlow.

sul linkFoldEmbedding Projectoraggiornamenti dei nostri strumenti già esistenti, come ad esempio TensorFlow Servingi numeri di GitHubStack Overflow@TensorFlowdiscuss@tensorflow.orgPubblicato da Amy McDonald Sandjideh, Technical Program Manager, TensorFlow

Etichette

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