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41d35dc201
Summary:
Included functions:
* save_mobile_module -> saves a mobile::Module to flatbuffer
* load_mobile_module_from_file -> loads a flatbuffer into mobile::Module
* parse_mobile_module -> parses from bytes or deserialized flatbuffer
Module object
Fixes #{issue number}
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67351
Reviewed By: iseeyuan
Differential Revision: D32010095
Pulled By: qihqi
fbshipit-source-id: d763b0557780f7c2661b6485105b045e41a5e8f1
33 lines
1.1 KiB
C++
33 lines
1.1 KiB
C++
#include <ATen/core/ivalue.h>
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#include <torch/csrc/jit/mobile/module.h>
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namespace torch {
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namespace jit {
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// Compares 2 mobile::Module. Comparison is done as follows:
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// 1. _ivalue() returned by both should be equal according to ivalueEquals below
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// 2. all functions with same name shall have same instructions and constants
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// 3. all functions in lhs exists in rhs.
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TORCH_API bool moduleEquals(
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const mobile::Module& lhs,
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const mobile::Module& rhs);
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// This is a function used in unittests to see if 2 IValue are the same.
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// If print is true; then it will print out where the ivalue differs.
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// Behavior of this function is different from IValue::operator== in the
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// following parts:
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// 1. Tensors are compared with allclose and returns bool (instead of bool
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// tensor)
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// 2. Therefore, comparing List[Tensor] or deeply nested tensor works
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// 3. 2 Capsules compares to true: this is because we intent to use this to
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// compare 2 IValue's after
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// saving and loading.
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TORCH_API bool ivalueEquals(
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const IValue& lhs,
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const IValue& rhs,
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bool print,
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int print_indent = 0);
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} // namespace jit
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} // namespace torch
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