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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/10/13 03:29:19 UTC

[GitHub] [incubator-tvm] anijain2305 commented on a change in pull request #6675: [QNN] Optimize requantize for power of 2 and bug in dequantize

anijain2305 commented on a change in pull request #6675:
URL: https://github.com/apache/incubator-tvm/pull/6675#discussion_r503645960



##########
File path: src/relay/qnn/op/requantize.cc
##########
@@ -155,17 +155,20 @@ Expr RequantizeLower(const Expr& input_tensor, const Expr& input_scale,
     if (!IsEqualScalar(input_scale, output_scale)) {
       int32_t fixed_point_multiplier, shift;
       std::tie(fixed_point_multiplier, shift) = GetFixedPointMultiplierShift(double_multiplier);
-
       const bool is_upward_rounding = (param->rounding == "UPWARD");
 
-      // When using upward rounding (i.e., x.5 rounded to x+1), leverage
-      // the FixedPointMultiply operator
-      scaled_int32_t =
-          (is_upward_rounding
-               ? FixedPointMultiply(scaled_int32_t, fixed_point_multiplier, shift)
-               : FixedPointMultiplyToNearest(scaled_int32_t, double_multiplier, input_shape));
+      if (is_upward_rounding && fixed_point_multiplier == (1 << 30)) {

Review comment:
       So, we use 'frexp' to represent a floating point numbers. It gives a float significant which is between [0.5, 1). For power of 2, it is always 0.5. We convert the float significand into a fixed point 32-bit integer, where decimal point is between the first and second bit. 0.5 in this representation = 1 << 30

##########
File path: src/relay/qnn/op/requantize.cc
##########
@@ -155,17 +155,20 @@ Expr RequantizeLower(const Expr& input_tensor, const Expr& input_scale,
     if (!IsEqualScalar(input_scale, output_scale)) {
       int32_t fixed_point_multiplier, shift;
       std::tie(fixed_point_multiplier, shift) = GetFixedPointMultiplierShift(double_multiplier);
-
       const bool is_upward_rounding = (param->rounding == "UPWARD");
 
-      // When using upward rounding (i.e., x.5 rounded to x+1), leverage
-      // the FixedPointMultiply operator
-      scaled_int32_t =
-          (is_upward_rounding
-               ? FixedPointMultiply(scaled_int32_t, fixed_point_multiplier, shift)
-               : FixedPointMultiplyToNearest(scaled_int32_t, double_multiplier, input_shape));
+      if (is_upward_rounding && fixed_point_multiplier == (1 << 30)) {

Review comment:
       So, we use `frexp` to represent a floating point numbers. It gives a float significant which is between [0.5, 1). For power of 2, it is always 0.5. We convert the float significand into a fixed point 32-bit integer, where decimal point is between the first and second bit. 0.5 in this representation = 1 << 30




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