Update on "[executorch][serialization] Serialize PTD files."

Introduce top-level serialization file that calls:
- serialize_pte_binary for PTE file
- FlatTensor.serialize_tensors for PTD files.

Differential Revision: [D66523267](https://our.internmc.facebook.com/intern/diff/D66523267/)

[ghstack-poisoned]

Author: lucylq

.ci/docker/requirements-ci.txt

@@ -1,17 +1,14 @@
 mpmath==1.3.0
-numpy==1.21.3; python_version == '3.10'
-numpy==1.23.2; python_version == '3.11'
-numpy; python_version >= '3.12'
+numpy==2.0.0; python_version >= '3.10'
 PyYAML==6.0.1
 ruamel.yaml==0.17.32
 sympy==1.12
 timm==0.6.13
 tomli==2.0.1
 torchsr==1.0.4
-transformers==4.38.0
+transformers==4.47.1
 zstd==1.5.5.1
-pandas==2.0.3; python_version == '3.10'
-pandas; python_version >= '3.11'
+pandas==2.2.2; python_version >= '3.10'
 pytest==7.2.0
 pytest-cov==4.1.0
 expecttest==0.1.6
@@ -24,7 +21,7 @@ sphinx-gallery==0.14.0
 breathe==4.34.0
 exhale==0.2.3
 docutils==0.16
-matplotlib==3.7.2
+matplotlib==3.9.4
 # PyTorch Theme
 -e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
 myst-parser==0.18.1

.ci/scripts/build-qnn-sdk.sh

@@ -1,5 +1,6 @@
 #!/bin/bash
 # Copyright (c) Meta Platforms, Inc. and affiliates.
+# Copyright 2025 Arm Limited and/or its affiliates.
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
@@ -11,10 +12,16 @@ set -o xtrace
 build_qnn_backend() {
   echo "Start building qnn backend."
   export ANDROID_NDK_ROOT=/opt/ndk
-  export QNN_SDK_ROOT=/tmp/qnn/2.25.0.240728
+  export QNN_SDK_ROOT=/tmp/qnn/2.28.0.241029
   export EXECUTORCH_ROOT="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/../.." && pwd)"
 
-  bash backends/qualcomm/scripts/build.sh --skip_aarch64 --job_number 2 --release
+  # Workaround to avoid issues around missing flatccrt library (depending on the
+  # number of jobs used), see issue #7300:
+  # Build twice (second time with `--no_clean`) to make sure libflatccrt.a is
+  # available.
+  # TODO: Remove this workaround once the underlying issue is fixed.
+  bash backends/qualcomm/scripts/build.sh --skip_aarch64 --job_number 2 --release || \
+  bash backends/qualcomm/scripts/build.sh --skip_aarch64 --job_number 2 --release --no_clean
 }
 
 set_up_aot() {

.ci/scripts/setup-qnn-deps.sh

@@ -16,9 +16,9 @@ install_qnn() {
   QNN_INSTALLATION_DIR=/tmp/qnn
   mkdir -p "${QNN_INSTALLATION_DIR}"
 
-  curl -Lo /tmp/v2.25.0.24.07.28.zip "https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.25.0.240728.zip"
+  curl -Lo /tmp/v2.28.0.24.10.29.zip "https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.28.0.241029.zip"
   echo "Finishing downloading qnn sdk."
-  unzip -qo /tmp/v2.25.0.24.07.28.zip -d /tmp
+  unzip -qo /tmp/v2.28.0.24.10.29.zip -d /tmp
   echo "Finishing unzip qnn sdk."
 
 

.ci/scripts/test_llama.sh

@@ -121,7 +121,7 @@ echo "COREML option ${COREML}"
 if [[ "${MODE}" =~ .*qnn.* ]]; then
   QNN=ON
   export EXECUTORCH_ROOT="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/.." && pwd)"
-  export QNN_SDK_ROOT=/tmp/qnn/2.25.0.240728
+  export QNN_SDK_ROOT=/tmp/qnn/2.28.0.241029
   export LD_LIBRARY_PATH="${QNN_SDK_ROOT}/lib/x86_64-linux-clang"
   export PYTHONPATH=".."
   cp schema/program.fbs exir/_serialize/program.fbs

.github/pytorch-probot.yml

@@ -1,4 +1,5 @@
 # The schema is from https://github.com/pytorch/pytorch/blob/main/.github/pytorch-probot.yml
+tracking_issue: 7679
 ciflow_push_tags:
 - ciflow/android
 - ciflow/apple

.github/workflows/android-perf.yml

@@ -260,7 +260,7 @@ jobs:
                       --output_name="${OUT_ET_MODEL_NAME}.pte"
                     ls -lh "${OUT_ET_MODEL_NAME}.pte"
                 elif [[ ${{ matrix.config }} == "llama3_qnn_htp" ]]; then
-                    export QNN_SDK_ROOT=/tmp/qnn/2.25.0.240728
+                    export QNN_SDK_ROOT=/tmp/qnn/2.28.0.241029
                     export LD_LIBRARY_PATH=$QNN_SDK_ROOT/lib/x86_64-linux-clang/
                     export PYTHONPATH=$(pwd)/..
 
@@ -347,7 +347,7 @@ jobs:
         PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh
 
         export ANDROID_ABIS="arm64-v8a"
-        PYTHON_EXECUTABLE=python EXECUTORCH_BUILD_QNN=ON QNN_SDK_ROOT=/tmp/qnn/2.25.0.240728 bash build/build_android_llm_demo.sh ${ARTIFACTS_DIR_NAME}
+        PYTHON_EXECUTABLE=python EXECUTORCH_BUILD_QNN=ON QNN_SDK_ROOT=/tmp/qnn/2.28.0.241029 bash build/build_android_llm_demo.sh ${ARTIFACTS_DIR_NAME}
 
   # Let's see how expensive this job is, we might want to tone it down by running it periodically
   benchmark-on-device:

.github/workflows/pull.yml

@@ -333,6 +333,9 @@ jobs:
 
   unittest-arm:
     uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
     with:
       runner: linux.2xlarge
       docker-image: executorch-ubuntu-22.04-arm-sdk
@@ -395,6 +398,25 @@ jobs:
         # Test llama2
         PYTHON_EXECUTABLE=python bash .ci/scripts/test_llama.sh -model stories110M -build_tool "${BUILD_TOOL}" -mode "${MODE}" -dtype "${DTYPE}" -pt2e_quantize "${PT2E_QUANTIZE}"
 
+  test-qnn-models-linux:
+    name: test-qnn-models-linux
+    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
+    strategy:
+      fail-fast: false
+    with:
+      runner: linux.2xlarge
+      docker-image: executorch-ubuntu-22.04-qnn-sdk
+      submodules: 'true'
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      timeout: 180
+      script: |
+        # The generic Linux job chooses to use base env, not the one setup by the image
+        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
+        conda activate "${CONDA_ENV}"
+
+        # placeholder for running test_qnn_delegate.py, can use matrix such that we can trigger different jobs, refers to test-llama-runner-qnn-linux
+        # reminder: make sure each job runs fast
+
   test-phi-3-mini-runner-linux:
     name: test-phi-3-mini-runner-linux
     uses: pytorch/test-infra/.github/workflows/linux_job.yml@main

.github/workflows/trunk.yml

@@ -132,6 +132,9 @@ jobs:
   test-arm-backend-delegation:
     name: test-arm-backend-delegation
     uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
     with:
       runner: linux.2xlarge
       docker-image: executorch-ubuntu-22.04-arm-sdk
@@ -159,6 +162,9 @@ jobs:
   test-arm-reference-delegation:
     name: test-arm-reference-delegation
     uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
     with:
       runner: linux.2xlarge
       docker-image: executorch-ubuntu-22.04-arm-sdk

.lintrunner.toml

@@ -294,6 +294,7 @@ include_patterns = [
     'build/**/*.py',
     'codegen/**/*.py',
     # 'devtools/**/*.py',
+    'devtools/visualization/**/*.py',
     'docs/**/*.py',
     # 'examples/**/*.py',
     # 'exir/**/*.py',

backends/apple/coreml/README.md

@@ -93,14 +93,14 @@ class Model(torch.nn.Module):
 source_model = Model()
 example_inputs = (torch.randn((1, 3, 256, 256)), )
 
-pre_autograd_aten_dialect = export_for_training(model, example_inputs).module()
+pre_autograd_aten_dialect = export_for_training(source_model, example_inputs).module()
 
 quantization_config = LinearQuantizerConfig.from_dict(
     {
         "global_config": {
             "quantization_scheme": QuantizationScheme.symmetric,
-            "activation_dtype": torch.uint8,
-            "weight_dtype": torch.int8,
+            "activation_dtype": torch.quint8,
+            "weight_dtype": torch.qint8,
             "weight_per_channel": True,
         }
     }