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Results 1 - 2 of 2 for AffineQuantizedOpInterface (0.24 sec)

  1. tensorflow/compiler/mlir/lite/transforms/prepare_quantize_dynamic_range.cc

        int bit_width = quant_specs_.GetQuantizationTypeWidth();
    
        Operation* quantize_op = quant_op.first;
        int quantize_operand_num = quant_op.second;
    
        auto affine_user = dyn_cast<AffineQuantizedOpInterface>(quantize_op);
    
        bool op_with_per_axis_support = false;
    
        if (!llvm::dyn_cast_or_null<CustomOp>(quantize_op)) {
          bool op_with_narrow_range =
              affine_user &&
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 20.8K bytes
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  2. tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.cc

      // FC and Conv* ops. Restriction for the weight can be relaxed if there are
      // needs for adjusting scale of variable weights.
      auto affine_op = dyn_cast<AffineQuantizedOpInterface>(op);
      auto bias_op = op->getOperand(bias_index).getDefiningOp<arith::ConstantOp>();
      if (!affine_op || !bias_op || input_indices.size() != 2) return false;
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 38.1K bytes
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