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Merge pull request #14 from google-ai-edge:test_windows_0511
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‎test_scripts/models/efficientnet.ps1‎

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# Copyright 2026 The LiteRT CLI Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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# LiteRT CLI EfficientNet Demo & Test Script for Windows
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# --- Environment Setup ---
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$SCRIPT_DIR = $PSScriptRoot
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$REPO_ROOT = (Resolve-Path "$SCRIPT_DIR/../..").Path
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$LITERT_CLI_ROOT = Join-Path $env:TEMP "litert_cli_efficientnet"
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# Source shared utilities
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. (Join-Path $SCRIPT_DIR "utils.ps1")
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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Write-Host "${BLUE}${BOLD}>>> LiteRT CLI EfficientNet Demo Script${NC}"
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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# Clean up and create work directory
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Write-Host ""
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Write-Host "${YELLOW}Setting up workspace at: $LITERT_CLI_ROOT...${NC}"
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if (Test-Path $LITERT_CLI_ROOT) {
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Remove-Item -Recurse -Force $LITERT_CLI_ROOT
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}
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New-Item -ItemType Directory -Force -Path $LITERT_CLI_ROOT | Out-Null
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Set-Location $LITERT_CLI_ROOT
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# Create Python virtual environment
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Write-Host "${YELLOW}Creating Python virtual environment...${NC}"
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python -m venv venv_efficientnet
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. .\venv_efficientnet\Scripts\Activate.ps1
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# Create output directories
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$MODEL_DIR = Join-Path $LITERT_CLI_ROOT "models"
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New-Item -ItemType Directory -Force -Path $MODEL_DIR | Out-Null
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# Test data directory
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$TEST_DATA_DIR = "$REPO_ROOT/litert_cli/test_data"
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# Install litert-cli from source
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Write-Host "${YELLOW}Installing litert-cli from source...${NC}"
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pip install -e "$REPO_ROOT"
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# --- 1. Download EfficientNet-B1 model ---
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Run-Case "Download: EfficientNet-B1 from HuggingFace" {
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litert download litert-community/efficientnet_b1 --file "*.tflite" --output "$MODEL_DIR/efficientnet"
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}
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# Verify the downloaded model exists
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$EFFICIENTNET_TFLITE = Join-Path $MODEL_DIR "efficientnet/efficientnet_b1.tflite"
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if (-not (Test-Path $EFFICIENTNET_TFLITE -PathType Leaf)) {
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Write-Host "${RED}Error: Downloaded model not found at $EFFICIENTNET_TFLITE${NC}"
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Exit 1
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}
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# --- 2. Quantize the EfficientNet model ---
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Run-Case "Quantize: EfficientNet Dynamic Range INT8" {
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litert quantize "$EFFICIENTNET_TFLITE" --type int8_dynamic --output "$MODEL_DIR/efficientnet/efficientnet_b1_int8_dynamic.tflite"
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}
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Run-Case "Quantize: EfficientNet Weight-Only INT8" {
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litert quantize "$EFFICIENTNET_TFLITE" --type int8_weight_only --output "$MODEL_DIR/efficientnet/efficientnet_b1_int8_weight_only.tflite"
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}
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# --- 3. Run Inference (Desktop & Android) ---
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# Run-Case "Run: EfficientNet FP32 on Desktop (CPU)" {
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# litert run "$EFFICIENTNET_TFLITE" --desktop --cpu --iterations 1
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# }
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if (Has-DesktopGpu "$EFFICIENTNET_TFLITE") {
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Run-Case "Run: EfficientNet FP32 on Desktop (GPU)" {
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litert run "$EFFICIENTNET_TFLITE" --desktop --gpu --iterations 1
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}
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} else {
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Write-Host ""
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Write-Host "${YELLOW}Desktop GPU delegate is not supported. Skipping Desktop GPU run.${NC}"
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}
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# Run-Case "Run: EfficientNet Dynamic INT8 on Desktop (CPU)" {
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# litert run "$MODEL_DIR/efficientnet/efficientnet_b1_int8_dynamic.tflite" --desktop --cpu --iterations 1
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# }
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if (Has-AndroidDevice) {
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Write-Host ""
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Write-Host "${GREEN}Android device detected. Running Android inference...${NC}"
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Run-Case "Run: EfficientNet FP32 on Android (CPU)" {
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litert run "$EFFICIENTNET_TFLITE" --android --cpu --iterations 1
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}
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Run-Case "Run: EfficientNet FP32 on Android (GPU)" {
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litert run "$EFFICIENTNET_TFLITE" --android --gpu --iterations 1
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}
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# If you have Android devices with NPU connected, enable those use cases.
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# Run-Case "Run: EfficientNet FP32 on Android (NPU)" {
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# litert run "$EFFICIENTNET_TFLITE" --android --npu --iterations 1
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# }
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Run-Case "Run: EfficientNet Dynamic INT8 on Android (CPU)" {
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litert run "$MODEL_DIR/efficientnet/efficientnet_b1_int8_dynamic.tflite" --android --cpu --iterations 1
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}
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}
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# --- 4. Benchmark (Android) ---
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if (Has-AndroidDevice) {
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Write-Host ""
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Write-Host "${GREEN}Android device detected. Running Android benchmarks...${NC}"
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Run-Case "Benchmark: EfficientNet FP32 on Android (CPU)" {
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litert benchmark "$EFFICIENTNET_TFLITE" --android
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}
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Run-Case "Benchmark: EfficientNet FP32 on Android (GPU)" {
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litert benchmark "$EFFICIENTNET_TFLITE" --android --gpu
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}
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# If you have Android devices with NPU connected, enable those use cases.
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# Run-Case "Benchmark: EfficientNet FP32 on Android (NPU)" {
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# litert benchmark "$EFFICIENTNET_TFLITE" --android --npu
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# }
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Run-Case "Benchmark: EfficientNet Dynamic INT8 on Android" {
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litert benchmark "$MODEL_DIR/efficientnet/efficientnet_b1_int8_dynamic.tflite" --android
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}
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} else {
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Write-Host ""
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Write-Host "${YELLOW}No Android device detected. Skipping benchmarks on Android.${NC}"
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}
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# --- 5. Compile (AOT Compilation) ---
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# Run-Case "Compile: EfficientNet FP32 for Qualcomm sm8750 NPU" {
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# litert compile "$EFFICIENTNET_TFLITE" --target sm8750 --output-dir "$MODEL_DIR/efficientnet"
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# }
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# Run-Case "Compile: EfficientNet FP32 for MediaTek MT6993 NPU" {
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# litert compile "$EFFICIENTNET_TFLITE" --target MT6993 --output-dir "$MODEL_DIR/efficientnet"
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# }
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# --- 6. Benchmark compiled model ---
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# Enable those use cases, or change to your own targets, if you have connected those android
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# devices through NPU.
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#
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# Run-Case "Run Qualcomm compiled EfficientNet" {
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# litert run "$MODEL_DIR/efficientnet/efficientnet_b1_Qualcomm_SM8750.tflite" --android --npu
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# }
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# Run-Case "Benchmark Qualcomm compiled EfficientNet" {
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# litert benchmark "$MODEL_DIR/efficientnet/efficientnet_b1_Qualcomm_SM8750.tflite" --android --npu
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# }
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# Run-Case "Run MediaTek compiled EfficientNet" {
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# litert run "$MODEL_DIR/efficientnet/efficientnet_b1_MediaTek_MT6993.tflite" --android --npu
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# }
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# Run-Case "Benchmark MediaTek compiled EfficientNet" {
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# litert benchmark "$MODEL_DIR/efficientnet/efficientnet_b1_MediaTek_MT6993.tflite" --android --npu
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# }
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# --- 7. Visualize (Model Explorer) ---
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# Run-Case "Visualize: Launch Model Explorer in the background" {
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# litert visualize "$EFFICIENTNET_TFLITE"
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# }
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# Run-Case "Visualize: Stop all Model Explorer servers" {
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# litert visualize --stop-all
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# }
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# --- Summary Report ---
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Print-SummaryReport "EfficientNet"

‎test_scripts/models/gemma4.ps1‎

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# Copyright 2026 The LiteRT CLI Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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# LiteRT CLI Gemma4 LLM Demo & Test Script for Windows
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# --- Environment Setup ---
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$SCRIPT_DIR = $PSScriptRoot
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$REPO_ROOT = (Resolve-Path "$SCRIPT_DIR/../..").Path
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$LITERT_CLI_ROOT = Join-Path $env:TEMP "litert_cli_gemma4"
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# Source shared utilities
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. (Join-Path $SCRIPT_DIR "utils.ps1")
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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Write-Host "${BLUE}${BOLD}>>> LiteRT CLI Gemma4 LLM Demo Script${NC}"
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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# Clean up and create work directory
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Write-Host ""
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Write-Host "${YELLOW}Setting up workspace at: $LITERT_CLI_ROOT...${NC}"
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if (Test-Path $LITERT_CLI_ROOT) {
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Remove-Item -Recurse -Force $LITERT_CLI_ROOT
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}
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New-Item -ItemType Directory -Force -Path $LITERT_CLI_ROOT | Out-Null
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Set-Location $LITERT_CLI_ROOT
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# Create Python virtual environment
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Write-Host "${YELLOW}Creating Python virtual environment...${NC}"
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python -m venv venv_gemma4
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. .\venv_gemma4\Scripts\Activate.ps1
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# Create output directories
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$MODEL_DIR = Join-Path $LITERT_CLI_ROOT "models"
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New-Item -ItemType Directory -Force -Path $MODEL_DIR | Out-Null
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# Install litert-cli from source
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Write-Host "${YELLOW}Installing litert-cli from source...${NC}"
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pip install -e "$REPO_ROOT"
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# --- 1. Convert HuggingFace Model google/gemma-4-E2B-it ---
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# TODO: Bring this back when we add support for --externalize_embedder in CLI convert command.
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# Run-Case "Convert: HuggingFace google/gemma-4-E2B-it" {
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# litert convert google/gemma-4-E2B-it --output "$MODEL_DIR/gemma4"
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# }
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# --- 2. Run Gemma4 Generative LLM Model ---
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Run-Case "Run Gemma4: Generative inference with custom prompt" {
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litert lm run --from-huggingface-repo=litert-community/gemma-4-E2B-it-litert-lm gemma-4-E2B-it.litertlm --prompt="What is the capital of France?"
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}
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# --- 3. Benchmark Gemma4 LLM Model ---
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Run-Case "Benchmark Gemma4: Local benchmark of LLM generation" {
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litert lm benchmark gemma-4-E2B-it.litertlm --from-huggingface-repo=litert-community/gemma-4-E2B-it-litert-lm -p 128 -d 128
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}
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# --- Summary Report ---
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Print-SummaryReport "Gemma4"

‎test_scripts/models/resnet.ps1‎

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# Copyright 2026 The LiteRT CLI Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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# LiteRT CLI ResNet Demo & Test Script for Windows
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# --- Environment Setup ---
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$SCRIPT_DIR = $PSScriptRoot
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$REPO_ROOT = (Resolve-Path "$SCRIPT_DIR/../..").Path
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$LITERT_CLI_ROOT = Join-Path $env:TEMP "litert_cli_resnet"
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# Source shared utilities
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. (Join-Path $SCRIPT_DIR "utils.ps1")
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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Write-Host "${BLUE}${BOLD}>>> LiteRT CLI ResNet Demo Script${NC}"
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Write-Host "${BLUE}${BOLD}==================================================================${NC}"
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# Clean up and create work directory
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Write-Host ""
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Write-Host "${YELLOW}Setting up workspace at: $LITERT_CLI_ROOT...${NC}"
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if (Test-Path $LITERT_CLI_ROOT) {
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Remove-Item -Recurse -Force $LITERT_CLI_ROOT
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}
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New-Item -ItemType Directory -Force -Path $LITERT_CLI_ROOT | Out-Null
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Set-Location $LITERT_CLI_ROOT
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# Create Python virtual environment
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Write-Host "${YELLOW}Creating Python virtual environment...${NC}"
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python -m venv venv_resnet
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. .\venv_resnet\Scripts\Activate.ps1
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# Create output directories
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$MODEL_DIR = Join-Path $LITERT_CLI_ROOT "models"
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New-Item -ItemType Directory -Force -Path $MODEL_DIR | Out-Null
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# Test data directory
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$TEST_DATA_DIR = "$REPO_ROOT/litert_cli/test_data"
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# Install litert-cli from source
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Write-Host "${YELLOW}Installing litert-cli from source...${NC}"
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pip install -e "$REPO_ROOT"
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# --- 1. Convert PyTorch ResNet18 model to LiteRT ---
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Run-Case "Convert: PyTorch ResNet18 to LiteRT" {
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litert convert "$TEST_DATA_DIR/resnet18.py" --output "$MODEL_DIR/resnet18"
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}
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# Verify the converted model exists
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$RESNET_TFLITE = Join-Path $MODEL_DIR "resnet18/resnet18.tflite"
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if (-not (Test-Path $RESNET_TFLITE -PathType Leaf)) {
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Write-Host "${RED}Error: Converted model not found at $RESNET_TFLITE${NC}"
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Exit 1
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}
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# --- 2. Quantize the ResNet18 model ---
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Run-Case "Quantize: ResNet18 Dynamic Range INT8" {
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litert quantize "$RESNET_TFLITE" --type int8_dynamic --output "$MODEL_DIR/resnet18/resnet18_int8_dynamic.tflite"
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}
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Run-Case "Quantize: ResNet18 Weight-Only INT8" {
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litert quantize "$RESNET_TFLITE" --type int8_weight_only --output "$MODEL_DIR/resnet18/resnet18_int8_weight_only.tflite"
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}
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# --- 3. Run Inference (Desktop & Android) ---
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Run-Case "Run: ResNet18 FP32 on Desktop (CPU)" {
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litert run "$RESNET_TFLITE" --desktop --cpu --iterations 1
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}
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if (Has-DesktopGpu "$RESNET_TFLITE") {
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Run-Case "Run: ResNet18 FP32 on Desktop (GPU)" {
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litert run "$RESNET_TFLITE" --desktop --gpu --iterations 1
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}
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} else {
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Write-Host ""
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Write-Host "${YELLOW}Desktop GPU delegate is not supported. Skipping Desktop GPU run.${NC}"
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}
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Run-Case "Run: ResNet18 Dynamic INT8 on Desktop (CPU)" {
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litert run "$MODEL_DIR/resnet18/resnet18_int8_dynamic.tflite" --desktop --cpu --iterations 1
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}
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if (Has-AndroidDevice) {
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Write-Host ""
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Write-Host "${GREEN}Android device detected. Running Android inference...${NC}"
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Run-Case "Run: ResNet18 FP32 on Android (CPU)" {
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litert run "$RESNET_TFLITE" --android --cpu --iterations 1
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}
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Run-Case "Run: ResNet18 FP32 on Android (GPU)" {
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litert run "$RESNET_TFLITE" --android --gpu --iterations 1
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}
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Run-Case "Run: ResNet18 Dynamic INT8 on Android (CPU)" {
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litert run "$MODEL_DIR/resnet18/resnet18_int8_dynamic.tflite" --android --cpu --iterations 1
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}
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}
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# --- 4. Benchmark (Android) ---
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if (Has-AndroidDevice) {
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Write-Host ""
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Write-Host "${GREEN}Android device detected. Running Android benchmarks...${NC}"
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Run-Case "Benchmark: ResNet18 FP32 on Android (CPU)" {
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litert benchmark "$RESNET_TFLITE" --android
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}
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Run-Case "Benchmark: ResNet18 FP32 on Android (GPU)" {
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litert benchmark "$RESNET_TFLITE" --android --gpu
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}
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Run-Case "Benchmark: ResNet18 Dynamic INT8 on Android" {
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litert benchmark "$MODEL_DIR/resnet18/resnet18_int8_dynamic.tflite" --android
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}
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} else {
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Write-Host ""
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Write-Host "${YELLOW}No Android device detected. Skipping benchmarks (litert benchmark only supports Android/GCP).${NC}"
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}
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# --- 5. Compile (AOT Compilation) ---
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Run-Case "Compile: ResNet18 FP32 for Qualcomm sm8750 NPU" {
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litert compile "$RESNET_TFLITE" --target sm8750 --output-dir "$MODEL_DIR/resnet18"
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}
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# --- 6. Visualize (Model Explorer) ---
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# Run-Case "Visualize: Launch Model Explorer in the background" {
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# litert visualize "$RESNET_TFLITE"
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# }
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# Run-Case "Visualize: Stop all Model Explorer servers" {
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# litert visualize --stop-all
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# }
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# --- Summary Report ---
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Print-SummaryReport "ResNet"

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