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* added tpu docs * added tpu flags * add tpu docs + init training call * amp * amp * amp * amp * optimizer step * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * fix test pkg create (#873) * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added test return and print * added test return and print * added test return and print * added test return and print * added test return and print * Update pytorch_lightning/trainer/trainer.py Co-Authored-By: Luis Capelo <luiscape@gmail.com> * Fix segmentation example (#876) * removed torchvision model and added custom model * minor fix * Fixed relative imports issue * Fix/typo (#880) * Update greetings.yml * Update greetings.yml * Changelog (#869) * Create CHANGELOG.md * Update CHANGELOG.md * Update CHANGELOG.md * Update PULL_REQUEST_TEMPLATE.md * Update PULL_REQUEST_TEMPLATE.md * Add PR links to Version 0.6.0 in CHANGELOG.md * Add PR links for Unreleased in CHANGELOG.md * Update PULL_REQUEST_TEMPLATE.md * Fixing Function Signatures (#871) * added tpu docs * added tpu flags * add tpu docs + init training call * amp * amp * amp * amp * optimizer step * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added auto data transfer to TPU * added test return and print * added test return and print * added test return and print * added test return and print * added test return and print * added test return and print * added test return and print * added test return and print Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: Luis Capelo <luiscape@gmail.com> Co-authored-by: Akshay Kulkarni <akshayk.vnit@gmail.com> Co-authored-by: Ethan Harris <ewah1g13@soton.ac.uk> Co-authored-by: Shikhar Chauhan <xssChauhan@users.noreply.github.com>
32 lines
777 B
Python
32 lines
777 B
Python
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from abc import ABC
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try:
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from apex import amp
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APEX_AVAILABLE = True
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except ImportError:
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APEX_AVAILABLE = False
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import logging as log
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class TrainerAMPMixin(ABC):
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def __init__(self):
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self.use_amp = None
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def init_amp(self, use_amp):
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self.use_amp = use_amp and APEX_AVAILABLE
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if self.use_amp:
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log.info('Using 16bit precision.')
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if use_amp and not APEX_AVAILABLE: # pragma: no cover
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msg = """
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You set `use_amp=True` but do not have apex installed.
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Install apex first using this guide and rerun with use_amp=True:
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https://github.com/NVIDIA/apex#linux
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this run will NOT use 16 bit precision
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"""
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raise ModuleNotFoundError(msg)
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