requantize就是再量化，是再一次量化。在刚才我们可以看到从FP32到int8是quantize量化，然后从int8到fp32是dequantize，从中间有一个过程，是int32到int8，这个量化与前面的量化过程无关，是requantize。最后得到的int8要转化成fp32，和第一次量化是一次逆向的量化转换，所以被称为dequantize，也就是反...
requantize网络再量化 网络释义 1. 再量化 9、MP3解码流程 - xixilive的日志 - 网易博客 ... 霍夫曼解码 Huffman decoding 再量化 Requantize 再排序 Reorder ... xixilive.blog.163.com|基于9个网页 隐私声明 法律声明 广告 反馈 © 2025 Microsoft...
I believe OpenVINO supports QuantizeLinear/DeauantizeLinear layers and ONNX format models. However, the model using QuantizeLinear/DeauantizeLinear layers (=Model1) gives different results depending on the OpenVINO 2021.4 and 2022.3. For comparison, the model that ...
Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVINO™ toolkit 2021.4.2 : -54.98152 Result when using OpenVINO™ toolkit 2022.3 : -54.981552 We do notice the results are different when using the ONNX model that uses QuantizeLin...
The solution in this reland CL is using uint64_t instead of size_t for intermediate calculation result. Besides, this reland CL also fixes a minor data limited error of quantize_linear_zero_point for DirectML backend. Original change's description: ...
webnn: add int4 and uint4 support for quantizeLinear and dequantizeLinear This CL also adds some WPT conformance tests to verify the implementation. Bug: 40206287 Change-Id: Ieb8ce3ae2182388ae7cc98cd1fc8e3d2dcd9c7d2 Cq-Include-Trybots: luci.chromium.try:win11-blink-rel, mac14.arm64-blink...
Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVINO™ toolkit 2021.4.2 : -54.98152 Result when using OpenVINO™ toolkit 2022.3 : -54.981552 We do notice the results are different when using the ONNX model that use...
Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVINO™ toolkit 2021.4.2 : -54.98152 Result when using OpenVINO™ toolkit 2022.3 : -54.981552 We do notice the results are different when using the ONNX model that uses QuantizeLi...
Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVINO™ toolkit 2021.4.2 : -54.98152 Result when using OpenVINO™ toolkit 2022.3 : -54.981552 We do notice the results are different when using the ONNX model that uses QuantizeLin...
Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVINO™ toolkit 2021.4.2 : -54.98152 Result when using OpenVINO™ toolkit 2022.3 : -54.981552 We do notice the results are different when using the ONNX model that uses QuantizeLin...