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QGemm takes in quantized A, B, C, and quantization parameters of output Y, in which C and quantization parameters of Y are optional. Its output can be quantized or full precision, which depends on whether quantization parameters of Y exists or not. If quant params of Y are provided, the output will be requantized or is full precision. Comparing with QLinearMatMul and MatMulInteger, QGemm supports transpose, apha and beta attribute. The formula for quantized GEMM is: Y = alpha * scale_a * scale_b * ((A_int8 - zp_a) * (B_int8 - zp_b) + C_int32), in which, C_int32 is quantized with formula: C_int32 = (beta * C) / (alpha * scale_a * scale_b) |
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| .. | ||
| execution_providers/images | ||
| images | ||
| python | ||
| ABI_Dev_Notes.md | ||
| Android_testing.md | ||
| C_API_Guidelines.md | ||
| cmake_guideline.md | ||
| Coding_Conventions_and_Standards.md | ||
| ContribOperators.md | ||
| FAQ.md | ||
| How_To_Update_ONNX_Dev_Notes.md | ||
| Model_Test.md | ||
| NotesOnThreading.md | ||
| ONNX_Runtime_Server_Usage.md | ||
| onnxruntime_dependencies.dot | ||
| onnxruntime_dependencies.png | ||
| onnxruntime_extensions.md | ||
| OperatorKernels.md | ||
| ORTMobilePackageOperatorTypeSupport.md | ||
| PR_Guidelines.md | ||
| Privacy.md | ||
| Python_Dev_Notes.md | ||
| Reduced_Operator_Kernel_build.md | ||
| ReleaseManagement.md | ||
| Roadmap.md | ||
| Server.md | ||
| Versioning.md | ||
| WinML_principles.md | ||
