| /external/pytorch/torch/jit/ |
| D | _recursive.py | 75 def make_stub_from_method(nn_module, method_name): argument
76 func = getattr(nn_module, method_name)
185 def infer_concrete_type_builder(nn_module, share_types=True): argument
192 concrete_type_builder = torch._C.ConcreteModuleTypeBuilder(type(nn_module))
193 if isinstance(nn_module, (torch.nn.ModuleDict)):
195 if isinstance(nn_module, (torch.nn.ModuleList, torch.nn.Sequential)):
197 if isinstance(nn_module, (torch.nn.ParameterList)):
199 if isinstance(nn_module, (torch.nn.ParameterDict)):
202 class_annotations = get_annotations(nn_module)
203 if isinstance(nn_module, (torch.ao.quantization.QuantWrapper)):
[all …]
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| D | _check.py | 61 def check(self, nn_module: torch.nn.Module) -> None:
62 source_lines = inspect.getsource(nn_module.__class__.__init__)
77 self.class_level_annotations = list(nn_module.__annotations__.keys())
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| /external/pytorch/torch/_export/ |
| D | non_strict_utils.py | 115 nn_module, argument
137 combined_args = _combine_args(nn_module, args, kwargs)
154 code = nn_module.forward.__code__
189 original_signature = inspect.signature(nn_module.forward)
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| /external/pytorch/torch/_dynamo/variables/ |
| D | __init__.py | 88 from .nn_module import (
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| D | builtin.py | 272 from .nn_module import NNModuleVariable
1294 from .nn_module import NNModuleVariable
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| D | builder.py | 188 from .nn_module import (
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| /external/pytorch/torch/testing/_internal/ |
| D | jit_metaprogramming_utils.py | 590 def create_script_module(self, nn_module, constructor_args, *args, **kwargs): argument
609 self.submodule = nn_module(*constructor_args)
677 nn_module = kwargs['constructor']
679 nn_module = getattr(torch.nn, name)
681 if "FunctionalModule" in str(nn_module):
716 …args, mod = f_args_variable, create_script_module(None, nn_module, constructor_args, *f_args_varia…
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| D | jit_utils.py | 627 def checkModule(self, nn_module, args): argument
632 sm = torch.jit.script(nn_module)
635 eager_out = nn_module(*args)
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| /external/pytorch/torch/_dynamo/ |
| D | utils.py | 1949 nn_module = tracer.output_graph.nn_modules[node.target]
1950 if not is_lazy_module(nn_module):
1951 nn_module = copy.deepcopy(nn_module)
1955 nn_module(*args, **kwargs)
1957 nn_module = None
1960 real_value = run_node(tracer, node, args, kwargs, nn_module)
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| D | codegen.py | 27 from .variables.nn_module import NNModuleVariable
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| D | output_graph.py | 100 from .variables.nn_module import NNModuleVariable
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| D | symbolic_convert.py | 121 from .variables.nn_module import NNModuleVariable, UnspecializedNNModuleVariable
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| /external/executorch/examples/qualcomm/scripts/ |
| D | mobilebert_fine_tune.py | 286 nn_module=model,
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| /external/executorch/backends/qualcomm/utils/ |
| D | utils.py | 434 nn_module: torch.nn.Module,
555 graph_module = torch.export.export(nn_module, sample_input).module()
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| /external/pytorch/test/functorch/ |
| D | test_control_flow.py | 415 nn_module = Nested()
418 return nn_module(
423 return nn_module(
487 nn_module = torch.nn.Linear(4, 4)
490 return nn_module(x)
493 return x * nn_module(x)
504 grads = torch.autograd.grad(result, (nn_module.weight,), grad_out)
509 (nn_module.weight,),
517 return torch.autograd.grad(result, (nn_module.weight,), grad_out)
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| /external/pytorch/torch/onnx/_internal/exporter/ |
| D | _core.py | 267 for name, nn_module in nn_module_stack.values():
269 nn_module_name = _get_qualified_module_name(nn_module)
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| /external/executorch/backends/qualcomm/tests/ |
| D | test_qnn_delegate.py | 1742 nn_module=module,
1789 nn_module=module,
1825 nn_module=module,
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| /external/pytorch/test/ |
| D | test_jit.py | 16076 nn_module = kwargs['constructor']
16078 nn_module = getattr(torch.nn, module_name)
16080 if "FunctionalModule" in str(nn_module):
16108 self.submodule = nn_module(*constructor_args)
16126 module = nn_module(*constructor_args)
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