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c80592ff9c
Fix circular dependencies Fixes #98959 Pull Request resolved: https://github.com/pytorch/pytorch/pull/98958 Approved by: https://github.com/BowenBao, https://github.com/thiagocrepaldi
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
from __future__ import annotations
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from typing import Dict
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from torch import _C
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class ExportTypes:
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r"""Specifies how the ONNX model is stored."""
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PROTOBUF_FILE = "Saves model in the specified protobuf file."
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ZIP_ARCHIVE = "Saves model in the specified ZIP file (uncompressed)."
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COMPRESSED_ZIP_ARCHIVE = "Saves model in the specified ZIP file (compressed)."
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DIRECTORY = "Saves model in the specified folder."
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class SymbolicContext:
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"""Extra context for symbolic functions.
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Args:
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params_dict (Dict[str, _C.IValue]): Mapping from graph initializer name to IValue.
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env (Dict[_C.Value, _C.Value]): Mapping from Torch domain graph Value to ONNX domain graph Value.
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cur_node (_C.Node): Current node being converted to ONNX domain.
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onnx_block (_C.Block): Current ONNX block that converted nodes are being appended to.
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"""
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def __init__(
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self,
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params_dict: Dict[str, _C.IValue],
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env: dict,
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cur_node: _C.Node,
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onnx_block: _C.Block,
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):
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self.params_dict: Dict[str, _C.IValue] = params_dict
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self.env: Dict[_C.Value, _C.Value] = env
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# Current node that is being converted.
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self.cur_node: _C.Node = cur_node
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# Current onnx block that converted nodes are being appended to.
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self.onnx_block: _C.Block = onnx_block
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