Add qti backend (#21)

Co-authored-by: Mohit Mundhra <[email protected]> Co-authored-by: Aasheesh Tiwari <[email protected]> Co-authored-by: Mohit Mundhra <[email protected]> Co-authored-by: Aasheesh Tiwari <[email protected]>
mlcommons · Aug 10, 2021 · 0e4e20d · 0e4e20d
1 parent 89917b9
commit 0e4e20d
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Showing 48 changed files with 4,812 additions and 9 deletions.
diff --git a/.bazelrc b/.bazelrc
@@ -20,3 +20,13 @@ build --host_cxxopt='--std=c++14'
 test --fat_apk_cpu=x86_64,arm64-v8a
 test --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
 
+#common --experimental_repo_remote_exec
+build:linux --copt=-w
+
+build:asan --strip=never
+build:asan --copt -fsanitize=address
+build:asan --copt -DADDRESS_SANITIZER
+build:asan --copt -O1
+build:asan --copt -g
+build:asan --copt -fno-omit-frame-pointer
+build:asan --linkopt -fsanitize=address
diff --git a/Makefile b/Makefile
@@ -22,7 +22,7 @@ SAMSUNG_BACKEND=
 all: app
 
 include mobile_back_tflite/tflite_backend.mk
-include mobile_back_qti/qti_backend.mk
+include mobile_back_qti/make/qti_backend.mk
 
 
 output/mlperf_mobile_docker_1_0.stamp: android/docker/mlperf_mobile/Dockerfile
@@ -144,3 +144,8 @@ clean:
 	@([ -d output/home/mlperf/cache ] && chmod -R +w output/home/mlperf/cache) || true
 	@rm -rf output
 
+ifeq (${WITH_QTI},1)
+  include mobile_back_qti/make/qti_backend_targets.mk
+endif
+
+
diff --git a/mobile_back_qti/BUILD b/mobile_back_qti/BUILD
@@ -53,12 +53,12 @@ cc_library(
 cc_library(
     name = "qtibackend",
     srcs = select({
-        "//conditions:default": ["//mobile_back_qti/cpp/backend_mock_qti:libqtibackend.so"],
-        # TODO: Add proper handling for QTI devices
-        ":android_arm64": ["//mobile_back_qti/cpp/backend_mock_qti:libqtibackend.so"],
-        #        ":android_arm64": [
-        #            "//mobile_back_qti/cpp/backend_qti:libqtibackend.so",
-        #        ],
+        "//conditions:default": [
+            "//mobile_back_qti/cpp/backend_mock_qti:libqtibackend.so"
+        ],
+        ":android_arm64": [
+            "//mobile_back_qti/cpp/backend_qti:libqtibackend.so"
+        ],
     }),
     deps = select({
         "//conditions:default": [],

diff --git a/mobile_back_qti/DLC/Makefile b/mobile_back_qti/DLC/Makefile
@@ -0,0 +1,321 @@
+# Copyright (c) 2020-2021 Qualcomm Innovation Center, Inc. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+##########################################################################
+
+# This file must be called from top level Makefile
+
+include ../make/builddir.mk
+
+all: ${BUILDDIR}/datasets.stamp sdm865-dlc sdm888-dlc
+
+.PHONY: sdm865-dlc sdm888-dlc dependencies gen-sdm865-dlc-info gen-sdm888-dlc-info clean
+
+include ../make/docker.mk
+
+DLCBUILDDIR=${BUILDDIR}/DLC
+MODEL_BASE_PATH=${BUILDDIR}/mobile
+MOBILENETEDGETPU_MODEL_PATH=${MODEL_BASE_PATH}/vision/mobilenet/models_and_code/checkpoints/float
+DEEPLABV3QAT_MODEL_PATH=${MODEL_BASE_PATH}/vision/deeplab/models_and_code/checkpoints/quantize_aware_training
+
+sdm865-dlc: ${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_hta.stamp \
+            ${DLCBUILDDIR}/ssd_mobiledet_qat_hta.stamp \
+            ${DLCBUILDDIR}/deeplabv3_hta.stamp
+
+sdm888-dlc: ${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_htp.stamp \
+            ${DLCBUILDDIR}/ssd_mobiledet_qat_htp.stamp \
+            ${DLCBUILDDIR}/deeplabv3_htp.stamp \
+	    ${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_htp_batched.stamp
+
+mobiledet: \
+	    ${DLCBUILDDIR}/ssd_mobiledet_qat_hta.stamp \
+            ${DLCBUILDDIR}/ssd_mobiledet_qat_htp.stamp
+
+${BUILDDIR}/datasets.stamp:
+	@(cd ../datasets && make)
+	@touch $@
+
+${BUILDDIR}/mobile/.stamp:
+	@curl -H  "Authorization: token ${GITHUB_TOKEN}" -o ${BUILDDIR}/mobile.zip -L https://github.com/mlcommons/mobile/archive/mobiledet-export_inference_graph.zip
+	@cd ${BUILDDIR} && unzip mobile.zip
+	@mv mobile-mobiledet-export_inference_graph mobile
+	@touch $@
+
+${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_float.dlc: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${BUILDDIR}/mobile/.stamp
+	@echo "Mobilenetedge TPU model conversion ...."
+	@echo "Float model"
+	@mkdir -p ${DLCBUILDDIR}
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${MOBILENETEDGETPU_MODEL_PATH}:/models \
+		-v ${DLCBUILDDIR}:/output \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '/snpe_sdk/bin/x86_64-linux-clang/snpe-tensorflow-to-dlc \
+ 		-i /models/frozen_graph_tf1x_transform.pb \
+		-d input "1,224,224,3" --out_node "MobilenetEdgeTPU/Predictions/Softmax" \
+		-o /output/mobilenet_edgetpu_224_1.0_float.dlc'
+
+${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_hta.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_float.dlc
+	@echo "Quantization of MobilenetEdgeTPU DLC for HTA"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/imagenet/imagenet_out:/imagenet-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c "cd /imagenet-out && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/mobilenet_edgetpu_224_1.0_float.dlc \
+		--input_list=/imagenet-out/imagenet_image_list.txt \
+		--output_dlc=/output/mobilenet_edgetpu_224_1.0_hta.dlc \
+  		--enable_hta"
+	@echo "Mobilenetedge TPU model conversion completed"
+	@touch $@
+
+${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_htp.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_float.dlc
+	@echo "Quantization of MobilenetEdgeTPU DLC for HTP"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/imagenet/imagenet_out:/imagenet-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c "cd /imagenet-out && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/mobilenet_edgetpu_224_1.0_float.dlc \
+		--input_list=/imagenet-out/imagenet_image_list.txt \
+		--output_dlc=/output/mobilenet_edgetpu_224_1.0_htp.dlc \
+  		--enable_htp"
+	@echo "Mobilenetedge TPU model conversion completed"
+	@touch $@
+
+${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_float_batched.dlc: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${BUILDDIR}/mobile/.stamp
+	@echo "Mobilenetedge TPU model conversion ...."
+	@echo "Batched Float model"
+	@mkdir -p ${DLCBUILDDIR}
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${MOBILENETEDGETPU_MODEL_PATH}:/models \
+		-v ${DLCBUILDDIR}:/output \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '/snpe_sdk/bin/x86_64-linux-clang/snpe-tensorflow-to-dlc \
+ 		-i /models/frozen_graph_tf1x_transform.pb \
+		-d input "3,224,224,3" --out_node "MobilenetEdgeTPU/Predictions/Softmax" \
+		-o /output/mobilenet_edgetpu_224_1.0_float_batched.dlc'
+
+${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_htp_batched.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${DLCBUILDDIR}/mobilenet_edgetpu_224_1.0_float_batched.dlc
+	@echo "Quantization of MobilenetEdgeTPU Batched DLC for HTP"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/imagenet/imagenet_out:/imagenet-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c "cd /imagenet-out && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/mobilenet_edgetpu_224_1.0_float_batched.dlc \
+		--input_list=/imagenet-out/imagenet_image_list.txt \
+		--output_dlc=/output/mobilenet_edgetpu_224_1.0_htp_batched.dlc \
+  		--enable_htp"
+	@echo "Mobilenetedge TPU model conversion completed"
+	@touch $@
+
+${DLCBUILDDIR}/ssd_mobiledet_qat.dlc: \
+                ${BUILDDIR}/mobile/.stamp
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/dlc \
+		-v ${BUILDDIR}/mobile/vision/mobiledet/uint8/export_inference_graph:/model \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '/snpe_sdk/bin/x86_64-linux-clang/snpe-tensorflow-to-dlc \
+		-i model/frozen_inference_graph.pb \
+		-d Preprocessor/map/TensorArrayStack/TensorArrayGatherV3 "1,320,320,3" \
+                --out_node "detection_classes" \
+                --out_node "detection_boxes" \
+                --out_node "detection_scores" \
+		-o /dlc/ssd_mobiledet_qat.dlc'
+
+${DLCBUILDDIR}/ssd_mobiledet_qat_hta.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${BUILDDIR}/mobile/.stamp \
+		${DLCBUILDDIR}/ssd_mobiledet_qat.dlc
+	@echo "Quantization of MobileDET SSD DLC for HTA"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/coco/coco_out:/coco-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		bash -c "cd /coco-out && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/ssd_mobiledet_qat.dlc \
+		--input_list=/coco-out/coco_image_list.txt \
+		--output_dlc=/output/ssd_mobiledet_qat_hta.dlc \
+		--enable_hta --hta_partitions sm8250"
+	@echo "SSD MobileDET model conversion for HTA completed"
+	@touch $@
+
+${DLCBUILDDIR}/ssd_mobiledet_qat_htp.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${BUILDDIR}/mobile/.stamp \
+		${DLCBUILDDIR}/ssd_mobiledet_qat.dlc
+	@echo "Quantization of MobileDET SSD DLC for HTP"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${MOBILEDETSSDQAT_MODEL_PATH}:/models \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/coco/coco_out:/coco-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		bash -c "cd /coco-out && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/ssd_mobiledet_qat.dlc \
+		--input_list=/coco-out/coco_image_list.txt \
+		--output_dlc=/output/ssd_mobiledet_qat_htp.dlc \
+		--enable_htp"
+	@echo "SSD MobileDET model conversion for HTP completed"
+	@touch $@
+
+
+${DLCBUILDDIR}/deeplabv3_quantized.dlc: ${TOPDIR}/DLC/argmax-quant.json ${DEEPLABV3QAT_MODEL_PATH}/freeze.pb \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${BUILDDIR}/mobile/.stamp
+	@echo "Deeplab v3 model conversion ...."
+	@echo "Deeplabv3 QAT model"
+	@cat ${TOPDIR}/DLC/argmax-quant.json
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DEEPLABV3QAT_MODEL_PATH}:/deeplabv3 \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${TOPDIR}/DLC:/dlc \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '/snpe_sdk/bin/x86_64-linux-clang/snpe-tensorflow-to-dlc \
+		-i /deeplabv3/freeze.pb \
+		-d ImageTensor "1,512,512,3" \
+		--out_node ArgMax \
+                --quantization_overrides /dlc/argmax-quant.json \
+		-o /output/deeplabv3_quantized.dlc'
+	@echo "Generated DLC from Deeplabv3 QAT model"
+
+
+${DLCBUILDDIR}/deeplabv3_hta.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${DLCBUILDDIR}/deeplabv3_quantized.dlc
+	@echo "Quantization of Deeplabv3 DLC"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/ade20k/ade20k_out:/ade20k-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c 'cd /ade20k-out/ && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/deeplabv3_quantized.dlc \
+		--input_list=/ade20k-out/ade20k_image_list.txt \
+		--output_dlc=/output/deeplabv3_hta.dlc \
+		--enable_hta'
+	@echo "Deeplab v3 model conversion completed"
+	@# Can't use deeplabv3_hta.dlc as make target since this file is present on failure
+	@touch $@
+
+${DLCBUILDDIR}/deeplabv3_htp.stamp: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		${DLCBUILDDIR}/deeplabv3_quantized.dlc
+	@echo "Quantization of Deeplabv3 DLC"
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/output \
+		-v ${BUILDDIR}/ade20k/ade20k_out:/ade20k-out \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c 'cd /ade20k-out/ && /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-quantize \
+		--input_dlc=/output/deeplabv3_quantized.dlc \
+		--input_list=/ade20k-out/ade20k_image_list.txt \
+		--output_dlc=/output/deeplabv3_htp.dlc \
+		--override_params --enable_htp'
+	@echo "Deeplab v3 model conversion completed"
+	@# Can't use deeplabv3_htp.dlc as make target since this file is present on failure
+	@touch $@
+
+gen-sdm865-dlc-info: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		sdm865-dlc
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/dlc \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '\
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/mobilenet_edgetpu_224_1.0_hta.dlc && \
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/ssd_mobilenet_v2_qat_hta.dlc && \
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/deeplabv3_hta.dlc'
+
+gen-sdm888-dlc-info: \
+		${BUILDDIR}/mlperf_mobile_docker_1_0.stamp ${BUILDDIR}/datasets.stamp \
+		sdm888-dlc
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/dlc \
+		-u ${USERID}:${GROUPID} \
+		mlcommons/mlperf_mobile:1.0 \
+		/bin/bash -c '\
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/mobilenet_edgetpu_224_1.0_htp.dlc && \
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/ssd_mobiledet_qat_htp.dlc && \
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/deeplabv3_htp.dlc && \
+	        /snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info -i /dlc/mobilenet_edgetpu_224_1.0_htp_batched.dlc'
+
+test: ${BUILDDIR}/mlperf_snpe${OSVER}_docker_image.stamp
+	@docker run \
+		-e PYTHONPATH=/snpe_sdk/lib/python \
+		-e LD_LIBRARY_PATH=/snpe_sdk/lib/x86_64-linux-clang \
+		-v ${SNPE_SDK}:/snpe_sdk \
+		-v ${DLCBUILDDIR}:/dlc \
+		-u ${USERID}:${GROUPID} \
+		mlperf_snpe${OSVER}:latest \
+		/bin/bash -c '\
+		/snpe_sdk/bin/x86_64-linux-clang/snpe-dlc-info'
+
+clean:
+	@rm -rf ${BUILDDIR}/DLC
+
diff --git a/mobile_back_qti/DLC/README.md b/mobile_back_qti/DLC/README.md
@@ -0,0 +1,7 @@
+# DLC
+
+This Makefile will create the DLCs used by the QTI backend.
+
+The DLCs are already checked into [Mobile Models](https://github.com/mlcommons/mobile_models)
+
+This Makefile is only to show how to re-create the DLCs.
diff --git a/mobile_back_qti/DLC/argmax-quant.json b/mobile_back_qti/DLC/argmax-quant.json
@@ -0,0 +1,13 @@
+{
+     "activation_encodings": {
+         "ArgMax:0": [{
+             "min": 0,
+             "max": 255,
+             "scale": 1,
+             "offset": 0,
+             "is_symmetric": "False",
+             "bitwidth": 8
+        }]
+    },
+    "param_encodings": {}
+}