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‎torch/_torch_docs.py‎

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@@ -5297,12 +5297,12 @@ def parse_kwargs(desc):
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.. note::
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For CUDA tensors, an LRU cache is used for cuFFT plans to speed up
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repeatedly running FFT methods on tensors of same geometry with same
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same configuration.
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same configuration.
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Changing ``torch.backends.cuda.cufft_plan_cache.max_size`` (default 1023)
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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``torch.backends.cuda.cufft_plan_cache.clear()`` to clear the cache.
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.. warning::
@@ -5397,12 +5397,12 @@ def parse_kwargs(desc):
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.. note::
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For CUDA tensors, an LRU cache is used for cuFFT plans to speed up
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repeatedly running FFT methods on tensors of same geometry with same
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same configuration.
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same configuration.
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Changing ``torch.backends.cuda.cufft_plan_cache.max_size`` (default 1023)
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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``torch.backends.cuda.cufft_plan_cache.clear()`` to clear the cache.
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.. warning::
@@ -5486,12 +5486,12 @@ def parse_kwargs(desc):
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.. note::
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For CUDA tensors, an LRU cache is used for cuFFT plans to speed up
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repeatedly running FFT methods on tensors of same geometry with same
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same configuration.
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same configuration.
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Changing ``torch.backends.cuda.cufft_plan_cache.max_size`` (default 1023)
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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``torch.backends.cuda.cufft_plan_cache.clear()`` to clear the cache.
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.. warning::
@@ -5567,12 +5567,12 @@ def parse_kwargs(desc):
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.. note::
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For CUDA tensors, an LRU cache is used for cuFFT plans to speed up
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repeatedly running FFT methods on tensors of same geometry with same
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same configuration.
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same configuration.
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Changing ``torch.backends.cuda.cufft_plan_cache.max_size`` (default 1023)
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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controls the capacity of this cache. Some cuFFT plans may allocate GPU
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memory. You may use ``torch.backends.cuda.cufft_plan_cache.size`` to query
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the number of plans currently in cache, and
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``torch.backends.cuda.cufft_plan_cache.clear()`` to clear the cache.
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.. warning::

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