mirror of
https://github.com/saymrwulf/onnxruntime.git
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e066fca777
### Description
#### 1. Adds `TensorQuantOverrides` extra option
Allows specifying a dictionary of tensor-level quantization overrides:
```
TensorQuantOverrides = dictionary :
Default is {}. Set tensor quantization overrides. The key is a tensor name and the value is a
list of dictionaries. For per-tensor quantization, the list contains a single dictionary. For
per-channel quantization, the list contains a dictionary for each channel in the tensor.
Each dictionary contains optional overrides with the following keys and values.
'quant_type' = QuantType : The tensor's quantization data type.
'scale' = Float : The scale value to use. Must also specify `zero_point` if set.
'zero_point' = Int : The zero-point value to use. Must also specify `scale` is set.
'symmetric' = Bool : If the tensor should use symmetric quantization. Invalid if also
set `scale` or `zero_point`.
'reduce_range' = Bool : If the quantization range should be reduced. Invalid if also
set `scale` or `zero_point`.
'rmax' = Float : Override the maximum real tensor value in calibration data.
Invalid if also set `scale` or `zero_point`.
'rmin' = Float : Override the minimum real tensor value in calibration data.
Invalid if also set `scale` or `zero_point`.
```
- All of the options are optional.
- Some combinations are invalid.
- Ex: `rmax` and `rmin` are unnecessary if the `zero_point` and `scale`
are also specified.
Example for per-tensor quantization overrides:
```Python3
extra_options = {
"TensorQuantOverrides": {
"SIG_OUT": [{"scale": 1.0, "zero_point": 127}],
"WGT": [{"quant_type": quantization.QuantType.QInt8, "symmetric": True, "reduce_range": True}],
"BIAS": [{"quant_type": quantization.QuantType.QInt8, "symmetric": True, "reduce_range": True}],
},
}
```
Example for per-channel quantization overrides (Conv weight and bias):
```Python3
extra_options = {
"TensorQuantOverrides": {
"WGT": [
{
"quant_type": quantization.QuantType.QUInt8,
"rmin": 0.0,
"rmax": 2.5,
"reduce_range": True,
},
{
"quant_type": quantization.QuantType.QUInt8,
"rmin": 0.2,
"rmax": 2.55,
"reduce_range": False,
},
],
"BIAS": [
{"zero_point": 0, "scale": 0.000621},
{"zero_point": 0, "scale": 0.23},
],
},
}
```
#### 2. Adds utilities to get the default QDQ configs for QNN EP
Added a `quantization.execution_providers.qnn.get_qnn_qdq_config` method
that inspects the model and returns suitable quantization
configurations.
Example usage:
```python3
from quantization import quantize, QuantType
from quantization.execution_providers.qnn import get_qnn_qdq_config
qnn_config = get_qnn_qdq_config(input_model_path,
data_reader,
activation_type=QuantType.QUInt16,
weight_type=QuantType.QUInt8)
quantize(input_model_path,
output_model_path,
qnn_config)
```
### Motivation and Context
Make it possible to create more QDQ models that run on QNN EP.
---------
Signed-off-by: adrianlizarraga <adlizarraga@microsoft.com>
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| .. | ||
| external | ||
| patches | ||
| tensorboard | ||
| adjust_global_compile_flags.cmake | ||
| CMakeLists.txt | ||
| CMakeSettings.json | ||
| codeconv.runsettings | ||
| deps.txt | ||
| deps_update_and_upload.py | ||
| EnableVisualStudioCodeAnalysis.props | ||
| gdk_toolchain.cmake | ||
| Info.plist.in | ||
| libonnxruntime.pc.cmake.in | ||
| linux_arm32_crosscompile_toolchain.cmake | ||
| linux_arm64_crosscompile_toolchain.cmake | ||
| nuget_helpers.cmake | ||
| onnxruntime.cmake | ||
| onnxruntime_codegen_tvm.cmake | ||
| onnxruntime_common.cmake | ||
| onnxruntime_compile_triton_kernel.cmake | ||
| onnxruntime_config.h.in | ||
| onnxruntime_csharp.cmake | ||
| onnxruntime_flatbuffers.cmake | ||
| onnxruntime_framework.cmake | ||
| onnxruntime_framework.natvis | ||
| onnxruntime_fuzz_test.cmake | ||
| onnxruntime_graph.cmake | ||
| onnxruntime_ios.toolchain.cmake | ||
| onnxruntime_java.cmake | ||
| onnxruntime_java_unittests.cmake | ||
| onnxruntime_kernel_explorer.cmake | ||
| onnxruntime_language_interop_ops.cmake | ||
| onnxruntime_mlas.cmake | ||
| onnxruntime_nodejs.cmake | ||
| onnxruntime_objectivec.cmake | ||
| onnxruntime_opschema_lib.cmake | ||
| onnxruntime_optimizer.cmake | ||
| onnxruntime_providers.cmake | ||
| onnxruntime_providers_acl.cmake | ||
| onnxruntime_providers_armnn.cmake | ||
| onnxruntime_providers_azure.cmake | ||
| onnxruntime_providers_cann.cmake | ||
| onnxruntime_providers_coreml.cmake | ||
| onnxruntime_providers_cpu.cmake | ||
| onnxruntime_providers_cuda.cmake | ||
| onnxruntime_providers_dml.cmake | ||
| onnxruntime_providers_dnnl.cmake | ||
| onnxruntime_providers_js.cmake | ||
| onnxruntime_providers_migraphx.cmake | ||
| onnxruntime_providers_nnapi.cmake | ||
| onnxruntime_providers_openvino.cmake | ||
| onnxruntime_providers_qnn.cmake | ||
| onnxruntime_providers_rknpu.cmake | ||
| onnxruntime_providers_rocm.cmake | ||
| onnxruntime_providers_tensorrt.cmake | ||
| onnxruntime_providers_tvm.cmake | ||
| onnxruntime_providers_vitisai.cmake | ||
| onnxruntime_providers_webnn.cmake | ||
| onnxruntime_providers_xnnpack.cmake | ||
| onnxruntime_pyop.cmake | ||
| onnxruntime_python.cmake | ||
| onnxruntime_rocm_hipify.cmake | ||
| onnxruntime_session.cmake | ||
| onnxruntime_snpe_provider.cmake | ||
| onnxruntime_training.cmake | ||
| onnxruntime_unittests.cmake | ||
| onnxruntime_util.cmake | ||
| onnxruntime_webassembly.cmake | ||
| precompiled_header.cmake | ||
| Sdl.ruleset | ||
| set_winapi_family_desktop.h | ||
| target_delayload.cmake | ||
| uwp_stubs.h | ||
| wcos_rules_override.cmake | ||
| winml.cmake | ||
| winml_cppwinrt.cmake | ||
| winml_sdk_helpers.cmake | ||
| winml_unittests.cmake | ||