Add Qwen3 1.7B qnn recipe

Qwen-Qwen3-1.7B/QNN/README.md

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+# Qwen3-1.7B Model Optimization
+
+This repository demonstrates the optimization of the [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) model using **post-training quantization (PTQ)** techniques.
+
+### Quantization Python Environment Setup
+Quantization is resource-intensive and requires GPU acceleration. In an x64 Python environment, install the required packages:
+
+```bash
+pip install -r requirements.txt
+
+# Disable CUDA extension build (not required)
+# Linux
+export BUILD_CUDA_EXT=0
+# Windows
+# set BUILD_CUDA_EXT=0
+
+# Install GptqModel from source
+pip install --no-build-isolation git+https://github.com/CodeLinaro/GPTQModel.git@rel_4.2.5
+```
+
+### AOT Compilation Python Environment Setup
+Model compilation using QNN Execution Provider requires a Python environment with onnxruntime-qnn installed. In a separate Python environment, install the required packages:
+
+```bash
+# Install Olive
+pip install olive-ai==0.13.0
+
+# Install ONNX Runtime QNN
+pip install onnxruntime==1.26.0
+pip install onnxruntime-qnn==2.4.0
+```
+
+Replace `/path/to/qnn/env/bin` in the config file with the path to the directory containing your QNN environment's Python executable. This path can be found by running the following command in the environment:
+
+```bash
+# Linux
+command -v python
+# Windows
+# where python
+```
+
+This command will return the path to the Python executable. Set the parent directory of the executable as the `/path/to/qnn/env/bin` in the config file.
+
+### Run the Quantization + Compilation Config
+Activate the **Quantization Python Environment** and run the workflow.
+
+For Snapdragon X Elite:
+
+```bash
+olive run --config x_elite_config.json
+```
+
+For Snapdragon X2 Elite:
+
+```bash
+olive run --config x2_elite_config.json
+```
+
+Olive will run the AOT compilation step in the **AOT Compilation Python Environment** specified in the config file using a subprocess. All other steps will run in the **Quantization Python Environment** natively.
+
+Optimized model saved in: `models/qwen3_1.7B/`
+
+> If optimization fails during context binary generation, rerun the command. The process will resume from the last completed step.
+
+> If the Static Quantization (SQ) pass fails with `Failed to allocate memory buffer of size...`, rerun the command without clearing the cache. Olive will resume from the last completed step and the pass will succeed.

Qwen-Qwen3-1.7B/QNN/requirements.txt

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+datasets
+olive-ai==0.13.0
+onnxruntime-genai-cuda==0.14.1
+onnxruntime-gpu==1.26.0
+optimum
+# newer transformers might have incompatibility with gptq passes
+transformers==4.57.3

Qwen-Qwen3-1.7B/QNN/x2_elite_config.json

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+{
+    "input_model": { "type": "HfModel", "model_path": "Qwen/Qwen3-1.7B" },
+    "systems": {
+        "qnn_system": {
+            "type": "PythonEnvironment",
+            "python_environment_path": "/path/to/qnn/env/bin",
+            "accelerators": [ { "execution_providers": [ "QNNExecutionProvider" ] } ]
+        }
+    },
+    "data_configs": [
+        {
+            "name": "wikitext2_train_joined",
+            "type": "HuggingfaceContainer",
+            "load_dataset_config": { "data_name": "wikitext", "subset": "wikitext-2-raw-v1", "split": "train" },
+            "pre_process_data_config": {
+                "strategy": "join",
+                "add_special_tokens": false,
+                "max_seq_len": 4096,
+                "max_samples": 128
+            }
+        },
+        {
+            "name": "wikitext2_train_act",
+            "type": "HuggingfaceContainer",
+            "load_dataset_config": { "data_name": "wikitext", "subset": "wikitext-2-raw-v1", "split": "train" },
+            "pre_process_data_config": {
+                "strategy": "line-by-line",
+                "add_special_tokens": true,
+                "max_samples": 256,
+                "max_seq_len": 4096
+            }
+        }
+    ],
+    "passes": {
+        "q": { "type": "QuaRot" },
+        "cs": { "type" : "CaptureSplitInfo", "num_splits": 1, "unique_embeds_lm_head_splits": true },
+        "g": {
+            "type": "GptqModel",
+            "bits": 8,
+            "sym": true,
+            "group_size": -1,
+            "lm_head": true,
+            "device": "cuda",
+            "data_config": "wikitext2_train_joined",
+            "dynamic": {
+                "+:.*lm_head*": {"bits": 8, "sym": true, "group_size": 32, "desc_act": false }
+            }
+        },
+        "mb": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "int4_block_size": 32,
+            "int4_accuracy_level": 4,
+            "int4_op_types_to_quantize": [ "Gather" ]
+        },
+        "mq": {
+            "type": "MatMulNBitsToQDQ",
+            "use_int4": true,
+            "add_zero_point": true,
+            "nodes_to_exclude": [ "/lm_head/MatMulNBits" ],
+            "save_as_external_data": true
+        },
+        "gs": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                { "surgeon": "AttentionMaskToSequenceLengths" },
+                { "surgeon": "RemoveGidxFromMatMulNBits" },
+                { "surgeon": "SimplifiedLayerNormToL2Norm" }
+            ],
+            "save_as_external_data": true
+        },
+        "sq": {
+            "type": "OnnxStaticQuantization",
+            "data_config": "wikitext2_train_act",
+            "activation_type": "uint16",
+            "precision": "uint8",
+            "calibration_providers": [ "CUDAExecutionProvider" ],
+            "quant_preprocess": true,
+            "op_types_to_exclude": [ "GatherBlockQuantized", "GroupQueryAttention", "MatMulNBits" ],
+            "save_as_external_data": true
+        },
+        "sp": { "type": "SplitModel" },
+        "st": { "type": "StaticLLM", "batch_size": 1, "context_length": 64 },
+        "cb": {
+            "type": "EPContextBinaryGenerator",
+            "provider_options": {
+                "htp_performance_mode": "burst",
+                "htp_graph_finalization_optimization_mode": "3",
+                "soc_model": "87"
+            },
+            "weight_sharing": true
+        },
+        "cp": { "type": "ComposeOnnxModels" }
+    },
+    "target": "qnn_system",
+    "log_severity_level": 1,
+    "output_dir": "models/qwen3_1.7B",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}

Qwen-Qwen3-1.7B/QNN/x_elite_config.json

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+{
+    "input_model": { "type": "HfModel", "model_path": "Qwen/Qwen3-1.7B" },
+    "systems": {
+        "qnn_system": {
+            "type": "PythonEnvironment",
+            "python_environment_path": "/path/to/qnn/env/bin",
+            "accelerators": [ { "execution_providers": [ "QNNExecutionProvider" ] } ]
+        }
+    },
+    "data_configs": [
+        {
+            "name": "wikitext2_train_joined",
+            "type": "HuggingfaceContainer",
+            "load_dataset_config": { "data_name": "wikitext", "subset": "wikitext-2-raw-v1", "split": "train" },
+            "pre_process_data_config": {
+                "strategy": "join",
+                "add_special_tokens": false,
+                "max_seq_len": 4096,
+                "max_samples": 128
+            }
+        },
+        {
+            "name": "wikitext2_train_act",
+            "type": "HuggingfaceContainer",
+            "load_dataset_config": { "data_name": "wikitext", "subset": "wikitext-2-raw-v1", "split": "train" },
+            "pre_process_data_config": {
+                "strategy": "line-by-line",
+                "add_special_tokens": true,
+                "max_samples": 256,
+                "max_seq_len": 4096
+            }
+        }
+    ],
+    "passes": {
+        "q": { "type": "QuaRot" },
+        "cs": { "type" : "CaptureSplitInfo", "num_splits": 1, "unique_embeds_lm_head_splits": true },
+        "g": {
+            "type": "GptqModel",
+            "bits": 8,
+            "sym": true,
+            "group_size": -1,
+            "lm_head": true,
+            "device": "cuda",
+            "data_config": "wikitext2_train_joined",
+            "dynamic": {
+                "+:.*lm_head*": { "bits": 8, "sym": true, "group_size": 32, "desc_act": false }
+            }
+        },
+        "mb": {
+            "type": "ModelBuilder",
+            "precision": "int4",
+            "int4_block_size": 32,
+            "int4_accuracy_level": 4,
+            "int4_op_types_to_quantize": [ "Gather" ]
+        },
+        "mq": {
+            "type": "MatMulNBitsToQDQ",
+            "use_int4": true,
+            "add_zero_point": true,
+            "nodes_to_exclude": [ "/lm_head/MatMulNBits" ],
+            "save_as_external_data": true
+        },
+        "gs": {
+            "type": "GraphSurgeries",
+            "surgeries": [
+                { "surgeon": "AttentionMaskToSequenceLengths" },
+                { "surgeon": "RemoveGidxFromMatMulNBits" },
+                { "surgeon": "SimplifiedLayerNormToL2Norm" }
+            ],
+            "save_as_external_data": true
+        },
+        "sq": {
+            "type": "OnnxStaticQuantization",
+            "data_config": "wikitext2_train_act",
+            "activation_type": "uint16",
+            "precision": "uint8",
+            "calibration_providers": [ "CUDAExecutionProvider" ],
+            "quant_preprocess": true,
+            "op_types_to_exclude": [ "GatherBlockQuantized", "GroupQueryAttention", "MatMulNBits" ],
+            "save_as_external_data": true
+        },
+        "sp": { "type": "SplitModel" },
+        "st": { "type": "StaticLLM", "batch_size": 1, "context_length": 64 },
+        "cb": {
+            "type": "EPContextBinaryGenerator",
+            "provider_options": {
+                "htp_performance_mode": "burst",
+                "htp_graph_finalization_optimization_mode": "3",
+                "soc_model": "60"
+            },
+            "weight_sharing": true
+        },
+        "cp": { "type": "ComposeOnnxModels" }
+    },
+    "target": "qnn_system",
+    "log_severity_level": 1,
+    "output_dir": "models/qwen3_1.7B",
+    "cache_dir": "cache",
+    "no_artifacts": true
+}