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8d45f555d7
Rewrite Python built-in class `super()` calls. Only non-semantic changes should be applied. - #94587 - #94588 - #94592 Also, methods with only a `super()` call are removed: ```diff class MyModule(nn.Module): - def __init__(self): - super().__init__() - def forward(self, ...): ... ``` Some cases that change the semantics should be kept unchanged. E.g.:f152a79be9/caffe2/python/net_printer.py (L184-L190)f152a79be9/test/test_jit_fuser_te.py (L2628-L2635)Pull Request resolved: https://github.com/pytorch/pytorch/pull/94587 Approved by: https://github.com/ezyang
52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
## @package onnx
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# Module caffe2.python.onnx.backend_rep_cpp
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from onnx.backend.base import BackendRep, namedtupledict
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# This is a wrapper around C++ Caffe2BackendRep,
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# mainly to handle the different input and output types for convenience of Python
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class Caffe2CppRep(BackendRep):
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def __init__(self, cpp_rep):
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super().__init__()
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self.__core = cpp_rep
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self.__external_outputs = cpp_rep.external_outputs()
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self.__external_inputs = cpp_rep.external_inputs()
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self.__uninitialized_inputs = cpp_rep.uninitialized_inputs()
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def init_net(self):
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return self.__core.init_net()
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def pred_net(self):
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return self.__core.pred_net()
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def external_outputs(self):
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return self.__core.external_outputs()
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def external_inputs(self):
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return self.__core.external_inputs()
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def run(self, inputs):
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output_values = None
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if isinstance(inputs, dict):
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output_values = self.__core.run(inputs)
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elif isinstance(inputs, list) or isinstance(inputs, tuple):
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if len(inputs) != len(self.__uninitialized_inputs):
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raise RuntimeError('Expected {} values for uninitialized '
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'graph inputs ({}), but got {}.'.format(
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len(self.__uninitialized_inputs),
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', '.join(self.__uninitialized_inputs),
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len(inputs)))
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input_map = {}
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for k, v in zip(self.__uninitialized_inputs, inputs):
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input_map[k] = v
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output_values = self.__core.run(input_map)
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else:
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# single input
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output_values = self.__core.run([inputs])
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return namedtupledict('Outputs', self.__external_outputs)(*output_values)
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