Update on "[ET-VK] Replace Uniform buffers with push constants for view op"

This diff replaces uniform buffers with push constants for view op in the Vulkan backend of Executorch. The changes include updating the GLSL code to use push constants instead of uniform buffers and updating the C++ code to pass the sizes as push constants to the shader.

Differential Revision: [D66733658](https://our.internmc.facebook.com/intern/diff/D66733658/)

[ghstack-poisoned]

Author: trivedivivek

.ci/docker/build.sh

@@ -41,6 +41,10 @@ case "${IMAGE_NAME}" in
     QNN_SDK=yes
     CLANG_VERSION=12
     ;;
+  executorch-ubuntu-22.04-mediatek-sdk)
+    MEDIATEK_SDK=yes
+    CLANG_VERSION=12
+    ;;
   executorch-ubuntu-22.04-clang12-android)
     LINTRUNNER=""
     CLANG_VERSION=12
@@ -77,6 +81,7 @@ docker build \
   --build-arg "BUILD_DOCS=${BUILD_DOCS}" \
   --build-arg "ARM_SDK=${ARM_SDK:-}" \
   --build-arg "QNN_SDK=${QNN_SDK:-}" \
+  --build-arg "MEDIATEK_SDK=${MEDIATEK_SDK:-}" \
   --build-arg "ANDROID_NDK_VERSION=${ANDROID_NDK_VERSION:-}" \
   -f "${OS}"/Dockerfile \
   "$@" \

.ci/docker/ubuntu/Dockerfile

@@ -85,5 +85,7 @@ RUN if [ -n "${ARM_SDK}" ]; then git config --global user.email "[email protected]
 
 ARG QNN_SDK
 
+ARG MEDIATEK_SDK
+
 USER ci-user
 CMD ["bash"]

.ci/scripts/test_llama.sh

@@ -110,6 +110,12 @@ else
   COREML=OFF
 fi
 
+if [[ "${MODE}" =~ .*quantize_kv.* ]]; then
+  QUANTIZE_KV_CACHE=ON
+else
+  QUANTIZE_KV_CACHE=OFF
+fi
+
 echo "COREML option ${COREML}"
 
 if [[ "${MODE}" =~ .*qnn.* ]]; then
@@ -249,6 +255,9 @@ if [[ "${QNN}" == "ON" ]]; then
     EXPORT_ARGS+=" --tokenizer_path tokenizer.model --pt2e_quantize qnn_16a16w --calibration_tasks wikitext --calibration_limit 1 --calibration_seq_length 128 --calibration_data Once "
   fi
 fi
+if [[ "${QUANTIZE_KV_CACHE}" == "ON" ]]; then
+  EXPORT_ARGS="${EXPORT_ARGS} --quantize_kv_cache"
+fi
 # Add dynamically linked library location
 $PYTHON_EXECUTABLE -m examples.models.llama.export_llama ${EXPORT_ARGS}
 

.github/workflows/docker-builds.yml

@@ -42,6 +42,7 @@ jobs:
           - docker-image-name: executorch-ubuntu-22.04-linter
           - docker-image-name: executorch-ubuntu-22.04-arm-sdk
           - docker-image-name: executorch-ubuntu-22.04-qnn-sdk
+          - docker-image-name: executorch-ubuntu-22.04-mediatek-sdk
           - docker-image-name: executorch-ubuntu-22.04-clang12-android
     env:
       DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/executorch/${{ matrix.docker-image-name }}

.github/workflows/pull.yml

@@ -86,7 +86,7 @@ jobs:
     strategy:
       matrix:
         dtype: [fp32]
-        mode: [portable, xnnpack+custom, xnnpack+custom+qe]
+        mode: [portable, xnnpack+custom, xnnpack+custom+qe,xnnpack+custom+quantize_kv,xnnpack+quantize_kv]
         include:
           - dtype: bf16
             mode: portable
@@ -504,3 +504,21 @@ jobs:
 
         # run llama runner in eager mode
         PYTHON_EXECUTABLE=python bash .ci/scripts/test_llama_runner_eager.sh
+
+  test-mediatek-models-linux:
+    name: test-mediatek-models-linux
+    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
+    strategy:
+      fail-fast: false
+    with:
+      runner: linux.24xlarge
+      docker-image: executorch-ubuntu-22.04-mediatek-sdk
+      submodules: 'true'
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      timeout: 90
+      script: |
+        # The generic Linux job chooses to use base env, not the one setup by the image
+        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
+        conda activate "${CONDA_ENV}"
+
+        # placeholder for mediatek to add more tests

.github/workflows/trunk.yml

@@ -225,7 +225,7 @@ jobs:
     strategy:
       matrix:
         dtype: [fp32]
-        mode: [portable, xnnpack+kv+custom, mps, coreml]
+        mode: [portable, xnnpack+kv+custom, mps, coreml, xnnpack+custom+quantize_kv]
         include:
           - dtype: bf16
             mode: portable

CMakeLists.txt

@@ -742,9 +742,9 @@ if(EXECUTORCH_BUILD_PYBIND)
   endif()
 
   if(EXECUTORCH_BUILD_XNNPACK)
-    # need to explicitly specify XNNPACK here otherwise uses XNNPACK symbols
-    # from libtorch_cpu
-    list(APPEND _dep_libs xnnpack_backend XNNPACK)
+    # need to explicitly specify XNNPACK and microkernels-prod
+    # here otherwise uses XNNPACK and microkernel-prod symbols from libtorch_cpu
+    list(APPEND _dep_libs xnnpack_backend XNNPACK microkernels-prod)
   endif()
 
   # compile options for pybind

backends/arm/arm_backend.py

@@ -13,7 +13,7 @@
 
 import logging
 import os
-from typing import final, List, Optional
+from typing import cast, final, List, Optional
 
 import serializer.tosa_serializer as ts
 from executorch.backends.arm.arm_vela import vela_compile
@@ -32,6 +32,7 @@
 from executorch.exir.backend.backend_details import BackendDetails, PreprocessResult
 from executorch.exir.backend.compile_spec_schema import CompileSpec
 from torch.export.exported_program import ExportedProgram
+from torch.fx import Node
 
 # TOSA backend debug functionality
 logger = logging.getLogger(__name__)
@@ -269,6 +270,7 @@ def preprocess(  # noqa: C901
         node_visitors = get_node_visitors(edge_program, tosa_spec)
         input_count = 0
         for node in graph_module.graph.nodes:
+            node = cast(Node, node)
             if node.op == "call_function":
                 process_call_function(node, tosa_graph, node_visitors, tosa_spec)
             elif node.op == "placeholder":
@@ -288,9 +290,6 @@ def preprocess(  # noqa: C901
                     "The rank of the input order is not equal to amount of input tensors"
                 )
 
-        # TODO: It would be awesome if this dump could somehow be done on top level and not here.
-        # Problem is that the desc.json has to be created on the tosa_graph object, which we can't
-        # access from top level.
         if artifact_path:
             tag = _get_first_delegation_tag(graph_module)
             dbg_tosa_dump(
@@ -311,6 +310,4 @@ def preprocess(  # noqa: C901
         else:
             raise RuntimeError(f"Unknown format {output_format}")
 
-        # Continueing from above. Can I put tosa_graph into this function?
-        # debug_handle_map = ...
         return PreprocessResult(processed_bytes=binary)

backends/arm/test/common.py

@@ -74,19 +74,15 @@ def get_tosa_compile_spec_unbuilt(
     the compile spec before calling .build() to finalize it.
     """
     if not custom_path:
-        intermediate_path = maybe_get_tosa_collate_path() or tempfile.mkdtemp(
-            prefix="arm_tosa_"
-        )
-    else:
-        intermediate_path = custom_path
+        custom_path = maybe_get_tosa_collate_path()
 
-    if not os.path.exists(intermediate_path):
-        os.makedirs(intermediate_path, exist_ok=True)
+    if custom_path is not None:
+        os.makedirs(custom_path, exist_ok=True)
     compile_spec_builder = (
         ArmCompileSpecBuilder()
         .tosa_compile_spec(tosa_version)
         .set_permute_memory_format(permute_memory_to_nhwc)
-        .dump_intermediate_artifacts_to(intermediate_path)
+        .dump_intermediate_artifacts_to(custom_path)
     )
 
     return compile_spec_builder

backends/arm/test/misc/test_debug_feats.py

@@ -111,7 +111,9 @@ def test_numerical_diff_prints(self):
                 model,
                 example_inputs=model.get_inputs(),
                 compile_spec=common.get_tosa_compile_spec(
-                    "TOSA-0.80.0+MI", permute_memory_to_nhwc=True
+                    "TOSA-0.80.0+MI",
+                    permute_memory_to_nhwc=True,
+                    custom_path=tempfile.mkdtemp("diff_print_test"),
                 ),
             )
             .export()