Update on "Use c10 version of half/bfloat16 in executorch"

Accomplished by importing relevant files from c10 into
executorch/runtime/core/portable_type/c10, and then using `using` in
the top-level ExecuTorch headers. This approach should keep the
ExecuTorch build hermetic for embedded use cases. In the future, we
should add a CI job to ensure the c10 files stay identical to the
PyTorch ones.

Differential Revision: [D66106969](https://our.internmc.facebook.com/intern/diff/D66106969/)

[ghstack-poisoned]

Author: swolchok

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-e0482fdf95eb3ce679fa442b50871d113ceb673b
+2ea4b56ec872424e486c4fe2d55da061067a2ed3

.ci/docker/common/install_pytorch.sh

@@ -26,7 +26,7 @@ install_pytorch_and_domains() {
 
   chown -R ci-user .
 
-  export _GLIBCXX_USE_CXX11_ABI=0
+  export _GLIBCXX_USE_CXX11_ABI=1
   # Then build and install PyTorch
   conda_run python setup.py bdist_wheel
   pip_install "$(echo dist/*.whl)"

.ci/scripts/gather_benchmark_configs.py

@@ -0,0 +1,224 @@
+#!/usr/bin/env python
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+import json
+import logging
+import os
+import re
+from typing import Any, Dict
+
+from examples.models import MODEL_NAME_TO_MODEL
+
+
+# Device pools for AWS Device Farm
+DEVICE_POOLS = {
+    "apple_iphone_15": "arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/3b5acd2e-92e2-4778-b651-7726bafe129d",
+    "apple_iphone_15+ios_18": "arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/12c8b15c-8d03-4e07-950d-0a627e7595b4",
+    "samsung_galaxy_s22": "arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/e59f866a-30aa-4aa1-87b7-4510e5820dfa",
+    "samsung_galaxy_s24": "arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/98f8788c-2e25-4a3c-8bb2-0d1e8897c0db",
+    "google_pixel_8_pro": "arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/d65096ab-900b-4521-be8b-a3619b69236a",
+}
+
+# Predefined benchmark configurations
+BENCHMARK_CONFIGS = {
+    "xplat": [
+        "xnnpack_q8",
+        "hf_xnnpack_fp32",
+        "llama3_fb16",
+        "llama3_spinquant",
+        "llama3_qlora",
+    ],
+    "android": [
+        "qnn_q8",
+        # TODO: Add support for llama3 htp
+        # "llama3_qnn_htp",
+    ],
+    "ios": [
+        "coreml_fp16",
+        "mps",
+        "llama3_coreml_ane",
+    ],
+}
+
+
+def parse_args() -> Any:
+    """
+    Parse command-line arguments.
+
+    Returns:
+        argparse.Namespace: Parsed command-line arguments.
+
+    Example:
+        parse_args() -> Namespace(models=['mv3', 'meta-llama/Llama-3.2-1B-Instruct-QLORA_INT4_EO8'],
+                                   os='android',
+                                   devices=['samsung_galaxy_s22'])
+    """
+    from argparse import ArgumentParser
+
+    def comma_separated(value: str):
+        """
+        Parse a comma-separated string into a list.
+        """
+        return value.split(",")
+
+    parser = ArgumentParser("Gather all benchmark configs.")
+    parser.add_argument(
+        "--os",
+        type=str,
+        choices=["android", "ios"],
+        help="The target OS.",
+    )
+    parser.add_argument(
+        "--models",
+        type=comma_separated,  # Use the custom parser for comma-separated values
+        help=f"Comma-separated model IDs or names. Valid values include {MODEL_NAME_TO_MODEL}.",
+    )
+    parser.add_argument(
+        "--devices",
+        type=comma_separated,  # Use the custom parser for comma-separated values
+        help=f"Comma-separated device names. Available devices: {list(DEVICE_POOLS.keys())}",
+    )
+
+    return parser.parse_args()
+
+
+def set_output(name: str, val: Any) -> None:
+    """
+    Set the output value to be used by other GitHub jobs.
+
+    Args:
+        name (str): The name of the output variable.
+        val (Any): The value to set for the output variable.
+
+    Example:
+        set_output("benchmark_configs", {"include": [...]})
+    """
+
+    if os.getenv("GITHUB_OUTPUT"):
+        print(f"Setting {val} to GitHub output")
+        with open(str(os.getenv("GITHUB_OUTPUT")), "a") as env:
+            print(f"{name}={val}", file=env)
+    else:
+        print(f"::set-output name={name}::{val}")
+
+
+def is_valid_huggingface_model_id(model_name: str) -> bool:
+    """
+    Validate if the model name matches the pattern for HuggingFace model IDs.
+
+    Args:
+        model_name (str): The model name to validate.
+
+    Returns:
+        bool: True if the model name matches the valid pattern, False otherwise.
+
+    Example:
+        is_valid_huggingface_model_id('meta-llama/Llama-3.2-1B') -> True
+    """
+    pattern = r"^[a-zA-Z0-9-_]+/[a-zA-Z0-9-_.]+$"
+    return bool(re.match(pattern, model_name))
+
+
+def get_benchmark_configs() -> Dict[str, Dict]:
+    """
+    Gather benchmark configurations for a given set of models on the target operating system and devices.
+
+    Args:
+        None
+
+    Returns:
+        Dict[str, Dict]: A dictionary containing the benchmark configurations.
+
+    Example:
+        get_benchmark_configs() -> {
+            "include": [
+                {
+                    "model": "meta-llama/Llama-3.2-1B",
+                    "config": "llama3_qlora",
+                    "device_name": "apple_iphone_15",
+                    "device_arn": "arn:aws:..."
+                },
+                {
+                    "model": "mv3",
+                    "config": "xnnpack_q8",
+                    "device_name": "samsung_galaxy_s22",
+                    "device_arn": "arn:aws:..."
+                },
+                ...
+            ]
+        }
+    """
+    args = parse_args()
+    target_os = args.os
+    devices = args.devices
+    models = args.models
+
+    benchmark_configs = {"include": []}
+
+    for model_name in models:
+        configs = []
+        if is_valid_huggingface_model_id(model_name):
+            if model_name.startswith("meta-llama/"):
+                # LLaMA models
+                repo_name = model_name.split("meta-llama/")[1]
+                if "qlora" in repo_name.lower():
+                    configs.append("llama3_qlora")
+                elif "spinquant" in repo_name.lower():
+                    configs.append("llama3_spinquant")
+                else:
+                    configs.append("llama3_fb16")
+                    configs.extend(
+                        [
+                            config
+                            for config in BENCHMARK_CONFIGS.get(target_os, [])
+                            if config.startswith("llama")
+                        ]
+                    )
+            else:
+                # Non-LLaMA models
+                configs.append("hf_xnnpack_fp32")
+        elif model_name in MODEL_NAME_TO_MODEL:
+            # ExecuTorch in-tree non-GenAI models
+            configs.append("xnnpack_q8")
+            configs.extend(
+                [
+                    config
+                    for config in BENCHMARK_CONFIGS.get(target_os, [])
+                    if not config.startswith("llama")
+                ]
+            )
+        else:
+            # Skip unknown models with a warning
+            logging.warning(f"Unknown or invalid model name '{model_name}'. Skipping.")
+            continue
+
+        # Add configurations for each valid device
+        for device in devices:
+            for config in configs:
+                if config == "llama3_coreml_ane" and not device.endswith("+ios_18"):
+                    device = f"{device}+ios_18"
+                    logging.info(
+                        f"Benchmark config '{config}' only works on iOS 18+, auto-upgraded device pool to '{device}'"
+                    )
+
+                if device not in DEVICE_POOLS:
+                    logging.warning(f"Unsupported device '{device}'. Skipping.")
+                    continue
+
+                record = {
+                    "model": model_name,
+                    "config": config,
+                    "device_name": device,
+                    "device_arn": DEVICE_POOLS[device],
+                }
+                benchmark_configs["include"].append(record)
+
+    set_output("benchmark_configs", json.dumps(benchmark_configs))
+
+
+if __name__ == "__main__":
+    get_benchmark_configs()

.ci/scripts/test_llama.sh

@@ -208,7 +208,7 @@ prepare_artifacts_upload() {
 PARAMS="params.json"
 CHECKPOINT_FILE_NAME=""
 touch "${PARAMS}"
-if [[ "${MODEL_NAME}" == "stories110M" ]]; then
+if [[ "${MODEL_NAME}" == "llama" ]] || [[ "${MODEL_NAME}" == "stories"* ]] || [[ "${MODEL_NAME}" == "tinyllama" ]]; then
   CHECKPOINT_FILE_NAME="stories110M.pt"
   download_stories_model_artifacts
 else

.ci/scripts/test_llava.sh

@@ -41,7 +41,6 @@ EXECUTORCH_COMMON_CMAKE_ARGS="                      \
         -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON     \
         -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON     \
         -DEXECUTORCH_BUILD_XNNPACK=ON               \
-        -DEXECUTORCH_DO_NOT_USE_CXX11_ABI=ON        \
         -DEXECUTORCH_XNNPACK_SHARED_WORKSPACE=ON"
 
 cmake_install_executorch_libraries() {

.ci/scripts/test_model.sh

@@ -209,25 +209,25 @@ test_model_with_mps() {
 if [[ "${BACKEND}" == "portable" ]]; then
   echo "Testing ${MODEL_NAME} with portable kernels..."
   test_model
-elif [[ "${BACKEND}" == "qnn" ]]; then
+elif [[ "${BACKEND}" == *"qnn"* ]]; then
   echo "Testing ${MODEL_NAME} with qnn..."
   test_model_with_qnn
   if [[ $? -eq 0 ]]; then
     prepare_artifacts_upload
   fi
-elif [[ "${BACKEND}" == "coreml" ]]; then
+elif [[ "${BACKEND}" == *"coreml"* ]]; then
   echo "Testing ${MODEL_NAME} with coreml..."
   test_model_with_coreml
   if [[ $? -eq 0 ]]; then
     prepare_artifacts_upload
   fi
-elif [[ "${BACKEND}" == "mps" ]]; then
+elif [[ "${BACKEND}" == *"mps"* ]]; then
   echo "Testing ${MODEL_NAME} with mps..."
   test_model_with_mps
   if [[ $? -eq 0 ]]; then
     prepare_artifacts_upload
   fi
-elif [[ "${BACKEND}" == "xnnpack" ]]; then
+elif [[ "${BACKEND}" == *"xnnpack"* ]]; then
   echo "Testing ${MODEL_NAME} with xnnpack..."
   WITH_QUANTIZATION=true
   WITH_DELEGATION=true