8 Advanced parallelization - Deep Learning with JAX
Por um escritor misterioso
Last updated 22 fevereiro 2025
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Using easy-to-revise parallelism with xmap() · Compiling and automatically partitioning functions with pjit() · Using tensor sharding to achieve parallelization with XLA · Running code in multi-host configurations
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Learn JAX in 2023: Part 2 - grad, jit, vmap, and pmap
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Breaking Up with NumPy: Why JAX is Your New Favorite Tool
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Information, Free Full-Text
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What is Google JAX? Everything You Need to Know - Geekflare
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Build a Transformer in JAX from scratch: how to write and train
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Writing a Training Loop in JAX and Flax
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Vectorize and Parallelize RL Environments with JAX: Q-learning at
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Hardware for Deep Learning. Part 4: ASIC
Learn JAX in 2023: Part 2 - grad, jit, vmap, and pmap
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Why You Should (or Shouldn't) be Using Google's JAX in 2023
Why You Should (or Shouldn't) be Using Google's JAX in 2023
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Why You Should (or Shouldn't) be Using Google's JAX in 2023
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7 Parallelizing your computations - Deep Learning with JAX
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