Update base for Update on "[executorch][runtime] Add NamedDataMap to method load"

Add NamedDataMap as an arg to:
- Method
- load_method
- parseTensor

Use NamedDataMap to resolve external tensors in parseTensor.

Test that the PTE + PTD file run well inside method_test.

Differential Revision: [D67127327](https://our.internmc.facebook.com/intern/diff/D67127327/)

[ghstack-poisoned]

Author: lucylq

.ci/docker/common/install_base.sh

@@ -26,6 +26,11 @@ install_ubuntu() {
     libssl-dev \
     zip
 
+  # These libraries are needed by TorchVision
+  apt-get install -y --no-install-recommends \
+    libjpeg-dev \
+    libpng-dev
+
   # Cleanup package manager
   apt-get autoclean && apt-get clean
   rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

.ci/docker/common/install_conda.sh

@@ -31,8 +31,16 @@ install_miniconda() {
 
 install_python() {
   pushd /opt/conda
-  # Install the correct Python version
+  # Install the selected Python version for CI jobs
   as_ci_user conda create -n "py_${PYTHON_VERSION}" -y --file /opt/conda/conda-env-ci.txt python="${PYTHON_VERSION}"
+
+  # From https://github.com/pytorch/pytorch/blob/main/.ci/docker/common/install_conda.sh
+  if [[ $(uname -m) == "aarch64" ]]; then
+    conda_install "openblas==0.3.28=*openmp*"
+  else
+    conda_install mkl=2022.1.0 mkl-include=2022.1.0
+  fi
+
   popd
 }
 
@@ -53,7 +61,7 @@ fix_conda_ubuntu_libstdcxx() {
   # PyTorch sev: https://github.com/pytorch/pytorch/issues/105248
   # Ref: https://github.com/pytorch/pytorch/blob/main/.ci/docker/common/install_conda.sh
   if grep -e "2[02].04." /etc/issue >/dev/null; then
-    rm "/opt/conda/envs/py_${PYTHON_VERSION}/lib/libstdc++.so.6"
+    rm /opt/conda/envs/py_${PYTHON_VERSION}/lib/libstdc++.so*
   fi
 }
 

.github/workflows/lint.yml

@@ -31,7 +31,7 @@ jobs:
         # The generic Linux job chooses to use base env, not the one setup by the image
         CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
         conda activate "${CONDA_ENV}"
-        
+
         # For mypy linting, we need to first install executorch first so that
         # it builds the python package information.
         BUILD_TOOL="cmake"
@@ -74,6 +74,7 @@ jobs:
       docker-image: executorch-ubuntu-22.04-linter
       fetch-depth: 0
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      timeout: 90
       script: |
         FILES_NEEDS_FORMAT=$(/opt/google-java-format -n extension/android/src/main/java/org/pytorch/executorch/*.java \
           examples/demo-apps/android/ExecuTorchDemo/app/src/main/java/com/example/executorchdemo/*.java \

.github/workflows/pull.yml

@@ -212,7 +212,7 @@ jobs:
       docker-image: executorch-ubuntu-22.04-clang12
       submodules: 'true'
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
-      timeout: 180
+      timeout: 90
       script: |
         # The generic Linux job chooses to use base env, not the one setup by the image
         CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
@@ -526,7 +526,7 @@ jobs:
       docker-image: executorch-ubuntu-22.04-clang12
       submodules: 'true'
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
-      timeout: 180
+      timeout: 90
       script: |
         # The generic Linux job chooses to use base env, not the one setup by the image
         CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")

CMakeLists.txt

@@ -182,6 +182,10 @@ option(EXECUTORCH_BUILD_EXTENSION_DATA_LOADER "Build the Data Loader extension"
        OFF
 )
 
+option(EXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR "Build the Flat Tensor extension"
+       OFF
+)
+
 option(EXECUTORCH_BUILD_EXTENSION_MODULE "Build the Module extension" OFF)
 
 option(EXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL "Build the Runner Util extension"
@@ -240,6 +244,9 @@ cmake_dependent_option(
   "NOT EXECUTORCH_BUILD_ARM_BAREMETAL" OFF
 )
 
+if(EXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR)
+  set(EXECUTORCH_BUILF_EXTENSION_DATA_LOADER ON)
+endif()
 
 if(EXECUTORCH_BUILD_EXTENSION_TRAINING)
   set(EXECUTORCH_BUILD_EXTENSION_TENSOR ON)
@@ -694,6 +701,11 @@ if(EXECUTORCH_BUILD_EXTENSION_DATA_LOADER)
   add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/extension/data_loader)
 endif()
 
+if(EXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR)
+  add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/extension/flat_tensor)
+  add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/extension/flat_tensor/serialize)
+endif()
+
 if(EXECUTORCH_BUILD_EXTENSION_MODULE)
   add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/extension/module)
 endif()

CONTRIBUTING.md

@@ -215,6 +215,14 @@ must work with threading**
 
 ## Testing
 
+### Running Tests Locally
+
+CI is run automatically on all pull requests. However, if you want to run tests locally, here are some example commands (not exhaustive):
+
+- The `sh test/build_size_test.sh` script will compile the C++runtime along with portable kernels.
+- The `test/run_oss_cpp_tests.sh` script will build and run C++ tests locally
+- Running `pytest` from the root directory will run Python tests locally.
+
 ### Writing Tests
 To help keep code quality high, ExecuTorch uses a combination of unit tests and
 end-to-end (e2e) tests. If you add a new feature or fix a bug, please add tests
@@ -229,8 +237,6 @@ If it's not clear how to add a test for your PR, take a look at the blame for
 the code you're modifying and find an author who has more context. Ask them
 for their help in the PR comments.
 
-The `test/run_oss_cpp_tests.sh` script will build and run C++ tests locally.
-
 ### Continuous Integration
 See https://hud.pytorch.org/hud/pytorch/executorch/main for the current state of
 the CI (continuous integration) jobs. If `main` is broken, consider rebasing

README.md

@@ -7,7 +7,7 @@
 <div align="center">
   <a href="https://github.com/pytorch/executorch/graphs/contributors"><img src="https://img.shields.io/github/contributors/pytorch/executorch?style=for-the-badge&color=blue" alt="Contributors"></a>
   <a href="https://github.com/pytorch/executorch/stargazers"><img src="https://img.shields.io/github/stars/pytorch/executorch?style=for-the-badge&color=blue" alt="Stargazers"></a>
-  <a href="https://discord.gg/MeacgB7A"><img src="https://img.shields.io/badge/Discord-Join%20Us-purple?logo=discord&logoColor=white&style=for-the-badge" alt="Join our Discord community"></a>
+  <a href="https://discord.gg/Dh43CKSAdc"><img src="https://img.shields.io/badge/Discord-Join%20Us-purple?logo=discord&logoColor=white&style=for-the-badge" alt="Join our Discord community"></a>
   <a href="https://pytorch.org/executorch/stable/index.html"><img src="https://img.shields.io/badge/Documentation-000?logo=googledocs&logoColor=FFE165&style=for-the-badge" alt="Check out the documentation"></a>
   <hr>
 </div>
@@ -55,11 +55,11 @@ To get started you can:
 ## Feedback and Engagement
 
 We welcome any feedback, suggestions, and bug reports from the community to help
-us improve our technology. Check out the [Discussion Board](https://github.com/pytorch/executorch/discussions) or chat real time with us on [Discord](https://discord.gg/MeacgB7A)
+us improve our technology. Check out the [Discussion Board](https://github.com/pytorch/executorch/discussions) or chat real time with us on [Discord](https://discord.gg/Dh43CKSAdc)
 
 ## Contributing
 
-We welcome contributions. To get started review the [guidelines](CONTRIBUTING.md) and chat with us on [Discord](https://discord.gg/MeacgB7A)
+We welcome contributions. To get started review the [guidelines](CONTRIBUTING.md) and chat with us on [Discord](https://discord.gg/Dh43CKSAdc)
 
 
 ## Directory Structure

backends/arm/_passes/decompose_select.py

@@ -37,14 +37,13 @@ def call(self, graph_module: torch.fx.GraphModule):
             rank = len(input_node.meta["val"].size())
             dim = dim % rank if dim < 0 else dim
             index = index % rank if index < 0 else index
-            dim_list = list(range(rank))
 
             with graph_module.graph.inserting_before(node):
                 slice_node = create_node(
                     graph_module.graph, slice_op, (input_node, dim, index, index + 1)
                 )
                 squeeze_node = create_node(
-                    graph_module.graph, squeeze_op, (slice_node, dim_list)
+                    graph_module.graph, squeeze_op, (slice_node, [dim])
                 )
 
             node.replace_all_uses_with(squeeze_node)

backends/arm/test/ops/test_bmm.py

@@ -124,6 +124,7 @@ def test_bmm_tosa_MI(self, test_data_generator: Callable[[], Tuple]):
         self._test_bmm_tosa_MI_pipeline(self.BMM(), test_data)
 
     @parameterized.expand(BMMSingleInput.test_data_generators)
+    @pytest.mark.flaky  # TODO: Investigate flakyness (MLETORCH-534)
     def test_bmm_single_input_tosa_MI(self, test_data_generator: Callable[[], Tuple]):
         test_data = test_data_generator()
         self._test_bmm_tosa_MI_pipeline(self.BMMSingleInput(), test_data)
@@ -144,6 +145,7 @@ def test_bmm_tosa_BI(self, test_data_generator: Callable[[], Tuple]):
         self._test_bmm_tosa_BI_pipeline(self.BMM(), test_data)
 
     @parameterized.expand(BMMSingleInput.test_data_generators)
+    @pytest.mark.flaky  # TODO: Investigate flakyness (MLETORCH-534)
     def test_bmm_single_input_tosa_BI(self, test_data_generator: Callable[[], Tuple]):
         test_data = test_data_generator()
         self._test_bmm_tosa_BI_pipeline(self.BMMSingleInput(), test_data)

backends/arm/test/ops/test_mm.py

@@ -115,6 +115,7 @@ def test_mm_tosa_MI(self, test_data_generator: Callable[[], Tuple]):
         self._test_mm_tosa_MI_pipeline(self.MM(), test_data)
 
     @parameterized.expand(MMSingleInput.test_data_generators)
+    @pytest.mark.flaky  # TODO: Investigate flakyness (MLETORCH-534)
     def test_mm_single_input_tosa_MI(self, test_data_generator: Callable[[], Tuple]):
         test_data = test_data_generator()
         self._test_mm_tosa_MI_pipeline(self.MMSingleInput(), test_data)
@@ -126,6 +127,7 @@ def test_mm_tosa_BI(self, test_data_generator: Callable[[], Tuple]):
         self._test_mm_tosa_BI_pipeline(self.MM(), test_data)
 
     @parameterized.expand(MMSingleInput.test_data_generators)
+    @pytest.mark.flaky  # TODO: Investigate flakyness (MLETORCH-534)
     def test_mm_single_input_tosa_BI(self, test_data_generator: Callable[[], Tuple]):
         test_data = test_data_generator()
         self._test_mm_tosa_BI_pipeline(self.MMSingleInput(), test_data)