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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/49980 From ``` ./python/libcst/libcst codemod remove_unused_imports.RemoveUnusedImportsWithGlean --no-format caffe2/ ``` Test Plan: Standard sandcastle tests Reviewed By: xush6528 Differential Revision: D25727359 fbshipit-source-id: c4f60005b10546423dc093d31d46deb418352286
58 lines
2.2 KiB
Python
58 lines
2.2 KiB
Python
## @package _import_c_extension
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# Module caffe2.python._import_c_extension
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import atexit
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import logging
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import sys
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from caffe2.python import extension_loader
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# We will first try to load the gpu-enabled caffe2. If it fails, we will then
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# attempt to load the cpu version. The cpu backend is the minimum required, so
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# if that still fails, we will exit loud.
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with extension_loader.DlopenGuard():
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has_hip_support = False
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has_cuda_support = False
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has_gpu_support = False
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try:
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from caffe2.python.caffe2_pybind11_state_gpu import * # noqa
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if num_cuda_devices(): # noqa
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has_gpu_support = has_cuda_support = True
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except ImportError as gpu_e:
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logging.info('Failed to import cuda module: {}'.format(gpu_e))
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try:
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from caffe2.python.caffe2_pybind11_state_hip import * # noqa
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# we stop checking whether we have AMD GPU devices on the host,
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# because we may be constructing a net on a machine without GPU,
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# and run the net on another one with GPU
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has_gpu_support = has_hip_support = True
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logging.info('This caffe2 python run has AMD GPU support!')
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except ImportError as hip_e:
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logging.info('Failed to import AMD hip module: {}'.format(hip_e))
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logging.warning(
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'This caffe2 python run failed to load cuda module:{},'
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'and AMD hip module:{}.'
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'Will run in CPU only mode.'.format(gpu_e, hip_e))
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try:
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from caffe2.python.caffe2_pybind11_state import * # noqa
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except ImportError as cpu_e:
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logging.critical(
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'Cannot load caffe2.python. Error: {0}'.format(str(cpu_e)))
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sys.exit(1)
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# libcaffe2_python contains a global Workspace that we need to properly delete
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# when exiting. Otherwise, cudart will cause segfaults sometimes.
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atexit.register(on_module_exit) # noqa
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# Add functionalities for the TensorCPU interface.
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def _TensorCPU_shape(self):
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return tuple(self._shape)
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def _TensorCPU_reshape(self, shape):
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return self._reshape(list(shape))
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TensorCPU.shape = property(_TensorCPU_shape) # noqa
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TensorCPU.reshape = _TensorCPU_reshape # noqa
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