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* Code drop: Update recipes documentation and remove custom recipes from low precision training
Signed-off-by: Pawel Gadzinski <pgadzinski@nvidia.com>

* Fix SVG css import path for diagrams
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* Refactor low_precision_training docs: remove optimizers, fix imports, add GPU checks

Changes:
- Remove optimizer code from all recipe examples (keep only forward/backward)
- Fix Format imports (use Format.E4M3 instead of string 'E4M3')
- Fix params_dtype for PyTorch examples (add params_dtype=torch.bfloat16)
- Add GPU capability assertions before START blocks for blockwise/mxfp8/nvfp4
- Fix JAX imports (Float8CurrentScaling from common.recipe, NVFP4BlockScaling)
- Add global_shard_guard for TransformerLayer examples in JAX
- Fix fused_layers_jax.py return tuple unpacking
- Update memory_usage JAX examples with dynamic GPU measurement
- Remove memory_usage_3_jax (JAX doesn't support FP8 weight storage)
- Update performance_considerations.rst for JAX differences
- Delete unused .out files and fp8_autocast_jax.py
Signed-off-by: Pawel Gadzinski <pgadzinski@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Fix JAX memory usage .out files with correct output
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* responded to comments
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* applied suggestions form greptile
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* fix
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* fix
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* fix
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* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix
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* fix
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* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix
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* fix
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* year change
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* fix
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* jax compute capability fix
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* fix
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* fix
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* fixes
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* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix
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* fix
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Signed-off-by: Pawel Gadzinski <pgadzinski@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>