Skip to content

This is a mirror of https//git.mlplatform.org/tosa/serialization_lib.git/

License

Notifications You must be signed in to change notification settings

pytorch-labs/tosa_serialization_lib-mirror

Repository files navigation

TOSA Serialization Library

Introduction

The TOSA Serialization library provides methods to read and write serialized TOSA graphs (https://developer.mlplatform.org/w/tosa/). The library includes a FlatBuffers schema and a C++ API for reading and writing TOSA graphs.

Prerequisites

The TOSA Seralization Library Requires the following
  • Python 3.9 or later (tested with 3.10.15)
  • CMake version 3.16 or later
  • GNU Make 4.1 or later
  • GCC (tested with 9.4.0) or Clang C++ compiler (tested with clang-10) with C++17 support
Checkout the Required Git Submodules with the following
git submodule update --init --recursive
Compile flatbuffers
cd third_party/flatbuffers
cmake -G "Unix Makefiles"
make -j
Install Additional pip Packages (for unit tests)
  • flatbuffers (tested with 24.3.25)
  • numpy (tested with 2.1.1)
  • ml_dtypes (tested with 0.5.0)
  • pytest (tested with 8.3.3)
pip install flatbuffers==24.3.25 numpy==2.1.1 ml_dtypes==0.5.0 pytest==8.3.3

Compilation

The TOSA Seralization Library Build can be prepared by the following
mkdir -p build
cd build
cmake ..
make

Usage

The section below describes serialization_lib API usage. For more details, please refer to include/tosa_serialization_handler.h.

TosaSerializationHandler

This is the top-level class that contains the entire TOSA graph. In particular, it contains a vector of TosaSerializationRegion objects, and provides API for file IO, region access, and version checking.

a. `LoadFileJson(filename)`:

    Loads json-formatted file "filename" from disk, and initialize the
    internal graph structure.

    Requires the schema file to be loaded via `LoadFileSchema()`.

b. `SaveFileJson(filename)`:

    Snapshots the internal graph structure and saves out JSON-formatted file
    `filename` to disk.
    Requires the schema file to be loaded via `LoadFileSchema()`.

c. `LoadFileTosaFlatbuffer(filename)`:

    Loads serialized flatbuffer file "filename" from disk, and initialize the
    internal graph structure.

d. `SaveFileTosaFlatbuffer(filename)`:

    Snapshots the internal graph structure and saves out serialized
    flatbuffer file `filename` to disk.

e. `GetVersion()`:

    Returns TOSA version implemented by the serialization library.

f. `GetRegions()`:

    Returns vector of `TosaSerializationRegion`. A valid graph must have
    one `main` region as the first region being traversed.

g. `GetMainRegion()`:

    Shortcut for accessing the first region.

h.  `GetRegionByName(name)`

    Returns region whose name is 'name'. A valid graph must have one `main`
    region as the first region being traversed.

i. `GetInputs()` / `GetOutputs()`:

    Shortcut for `main` region's input/output tensor name. Input tensors of
    the main block are usually treated as `tosa.PLACEHOLDER`. Output tensors
    are the output of the entire graph and should be evaluated when graph
    traversal has finished.

TosaSerializationRegion

This is the region class. It contains vectors of TosaSerializationBasicBlock objects, and provides API for block access.

a. `GetName()`:

    Returns name of the region.

b. `GetBlocks()`:

    Returns vector of TosaSerializationBasicBlock. A valid region must have
    at least one block.

c. `GetBlockByName(name)`:

    Returns the `TosaSerializationBasicBlock` with name `name`. Returns `nullptr`
    if nothing matches.

TosaSerializationBasicBlock

This is the basic-block class. It contains vectors of TosaSerializationOperator and TosaSerializationTensor. Once entering a basic block, all of the operators within the block will be evaluated in order.

Upon reaching a TOSA control flow operator (tosa.WHILE and tosa.COND_IF), the status of current unfinished block will be saved, and the regions specified in control flow operator will be evaluated first. Once the control flow regions finish its evaluation, the original unfinished block status will be restored and evaluation continues. This is more analogous to a function call than a compiler basic block.

a. `GetName()`:

    Returns name of the basic block.

b. `GetRegionName()`:

    Returns name of the region containing the basic block.

c. `GetOperators()`:

    Returns vector of `TosaSerializationOperator`

d. `GetTensors()`:

    Returns vector of `TosaSerializationTensor`

e. `GetTensorByName(name)`:

    Returns the `TosaSerializationTensor` with name `name`. Returns `nullptr`
    if nothing matches.

f. `GetInputs()` / `GetOutputs()`:

    Returns input/output tensor name of the basic block.

TosaSerializationOperator

The operator class contains (1) what TOSA Op, (2) attribute (compile-time- known input) and (3) input/output tensor names.

a. `GetOp()`:

    Returns TOSA Op. Defined in schema `tosa.fbs`.

b. `GetAttribute()` / `GetAttributeType()`:

    `GetAttribute()` returns the base object of attribute.
    `GetAttributeType()` returns which type of attribute the base object
    needs to be casted to.  Type of attribute is defined in `tosa.fbs` and
    `include/attribute.def`.

c. `GetInputTensorNames()` / `GetOutputTensorNames()`:

    Returns the input/output tensor names of the basic block.

TosaSerializationTensor

The tensor class contains (1) data type, (2) shape, (3) properties and (4) data value.

a. `GetName()` / `SetName(name)`:

    `GetName()` returns the name of the tensor. `SetName()` sets the name
    of the tensor.

b. `GetShape()`:

    Returns the shape of the tensor as `vector<int32_t>`.

c. `GetDtype()` / `SetDtype(dtype)`:

    `GetDtype()` returns the data type of the tensor. `SetDtype()` sets the
    data type of the tensor. DType is defined in `tosa.fbs`.

d. `GetVariable()`:

    Returns whether tensor is a Tosa Variable.

e. `GetIsUnranked()` / `SetIsUnranked(value)`:

    `GetIsUnranked()` returns whether tensor is an unranked tensor.
    `SetIsUnranked()` sets whether tensor is an unranked tensor.

f. `GetData()` / `SetData(data)`:

    `GetData()` returns a vector of `uint8_t` values which stores the constant
    value for a constant tensor, or the initialization value for a variable tensor.
    `SetData()` sets the constant value for a constant tensor, or the initialization
    value for a variable tensor.

Tests

The TOSA Serialization Library's C++ and Python versions can be tested with GoogleTest and PyTest, respectively. After building, unit tests can be run with the following commands.

  • ctest from the project's build directory
  • pytest from the project's root directory
    • pytest --leave-tmp preserves temporary files at python/pytests/tmp/ for debugging.

Pre Commit Checks

Before pushing a commit, pre commit checks must be run to ensure conformity.

Prerequisites
Install Additional pip Package
  • pre-commit (tested with 3.8.0)
  • clang-format (tested with 14)
pip install pre-commit==3.8.0 clang-format==14
Run Pre Commit Checks
pre-commit run --all

License

The TOSA Serialization Library is licensed under Apache-2.0.

Third Party Projects

  • The half library is licensed under MIT license.

Other third party projects are referenced as sub-modules and as such, are licensed under the licenses stated in their projects.

About

This is a mirror of https//git.mlplatform.org/tosa/serialization_lib.git/

Resources

License

Stars

Watchers

Forks

Packages

No packages published