Inductor - Post-grad FX Passes PyTorch Developer podcast

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Inductor - Post-grad FX passes

1y ago 24:07

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Kandungan disediakan oleh PyTorch, Edward Yang, and Team PyTorch. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh PyTorch, Edward Yang, and Team PyTorch atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

The post-grad FX passes in Inductor run after AOTAutograd has functionalized and normalized the input program into separate forward/backward graphs. As such, they generally can assume that the graph in question is functionalized, except for some mutations to inputs at the end of the graph. At the end of post-grad passes, there are special passes that reintroduce mutation into the graph before going into the rest of Inductor lowering which is generally aware of passes. The post-grad FX passes are varied but are typically domain specific passes making local changes to specific parts of the graph.

… continue reading

83 episod

#Tech #PyTorch #Edward Yang #Team PyTorch #Deep Learning #Machine Learning

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Inductor - Post-grad FX passes

PyTorch Developer Podcast

32 subscribers

published 1y ago

Kongsi

MP3•Laman utama episod

Kandungan disediakan oleh PyTorch, Edward Yang, and Team PyTorch. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh PyTorch, Edward Yang, and Team PyTorch atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

The post-grad FX passes in Inductor run after AOTAutograd has functionalized and normalized the input program into separate forward/backward graphs. As such, they generally can assume that the graph in question is functionalized, except for some mutations to inputs at the end of the graph. At the end of post-grad passes, there are special passes that reintroduce mutation into the graph before going into the rest of Inductor lowering which is generally aware of passes. The post-grad FX passes are varied but are typically domain specific passes making local changes to specific parts of the graph.

… continue reading

83 episod

#Tech #PyTorch #Edward Yang #Team PyTorch #Deep Learning #Machine Learning

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