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# Motivation According to [[1/2] Intel GPU Runtime Upstreaming for Generator](https://github.com/pytorch/pytorch/pull/118528), as mentioned in [[RFC] Intel GPU Runtime Upstreaming](https://github.com/pytorch/pytorch/issues/114842), the second PR covers the changes under `python frontend`. # Design Currently, it primarily offers geneartor-related APIs, including - `torch.xpu.default_generators` - `torch.xpu.get_rng_state` - `torch.xpu.get_rng_state_all` - `torch.xpu.initial_seed` - `torch.xpu.manual_seed` - `torch.xpu.manual_seed_all` - `torch.xpu.seed` - `torch.xpu.seed_all` - `torch.xpu.set_rng_state` - `torch.xpu.set_rng_state_all` # Additional Context The differences with CUDA: The generator-related frontend python APIs are 1:1 mapping with CUDA. Pull Request resolved: https://github.com/pytorch/pytorch/pull/118613 Approved by: https://github.com/gujinghui, https://github.com/EikanWang, https://github.com/jgong5, https://github.com/albanD
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997 B
ReStructuredText
57 lines
No EOL
997 B
ReStructuredText
torch.xpu
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===================================
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.. automodule:: torch.xpu
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.. currentmodule:: torch.xpu
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.. autosummary::
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:toctree: generated
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:nosignatures:
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StreamContext
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current_device
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current_stream
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device
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device_count
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device_of
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empty_cache
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get_device_capability
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get_device_name
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get_device_properties
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init
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is_available
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is_initialized
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set_device
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set_stream
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stream
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synchronize
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Random Number Generator
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-------------------------
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.. autosummary::
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:toctree: generated
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:nosignatures:
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get_rng_state
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get_rng_state_all
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initial_seed
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manual_seed
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manual_seed_all
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seed
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seed_all
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set_rng_state
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set_rng_state_all
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Streams and events
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------------------
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.. autosummary::
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:toctree: generated
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:nosignatures:
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Event
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Stream
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.. This module needs to be documented. Adding here in the meantime
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.. for tracking purposes
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.. py:module:: torch.xpu.random
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.. py:module:: torch.xpu.streams |