message: Remove quantized versiaon of Div till fixing it.
diff: @@ -1973,53 +1973,6 @@ void BroadcastDiv(const T* input1_data, const Dims<4>& input1_dims,
  }
  }
  -inline void BroadcastDiv(const uint8* input1_data, const Dims<4>& input1_dims,
  - int32 input1_offset, const uint8* input2_data,
  - const Dims<4>& input2_dims, int32 input2_offset,
  - int32 output_offset, int32 output_multiplier,
  - int output_shift, int32 output_activation_min,
  - int32 output_activation_max, uint8* output_data,
  - const Dims<4>& output_dims) {
  - gemmlowp::ScopedProfilingLabel label("BroadcastDiv/8bit");
  -
  - NdArrayDesc<4> desc1;
  - NdArrayDesc<4> desc2;
  - NdArrayDescsForElementwiseBroadcast(input1_dims, input2_dims, &desc1, &desc2);
  -
  - // In Tensorflow, the dimensions are canonically named (batch_number, row,
  - // col, channel), with extents (batches, height, width, depth), with the
  - // trailing dimension changing most rapidly (channels has the smallest stride,
  - // typically 1 element).
  - //
  - // In generated C code, we store arrays with the dimensions reversed. The
  - // first dimension has smallest stride.
  - //
  - // We name our variables by their Tensorflow convention, but generate C code
  - // nesting loops such that the innermost loop has the smallest stride for the
  - // best cache behavior.
  - for (int b = 0; b < ArraySize(output_dims, 3); ++b) {
  - for (int y = 0; y < ArraySize(output_dims, 2); ++y) {
  - for (int x = 0; x < ArraySize(output_dims, 1); ++x) {
  - for (int c = 0; c < ArraySize(output_dims, 0); ++c) {
  - const int32 input1_val =
  - input1_offset + input1_data[SubscriptToIndex(desc1, c, x, y, b)];
  - const int32 input2_val =
  - input2_offset + input2_data[SubscriptToIndex(desc2, c, x, y, b)];
  - const int32 unclamped_result =
  - output_offset +
  - MultiplyByQuantizedMultiplierSmallerThanOne(
  - input1_val / input2_val, output_multiplier, output_shift);
  - const int32 clamped_output =
  - std::min(output_activation_max,
  - std::max(output_activation_min, unclamped_result));
  - output_data[Offset(output_dims, c, x, y, b)] =
  - static_cast<uint8>(clamped_output);
  - }
  - }
  - }
  - }
  -}
  -
  // TODO(aselle): This is not actually optimized yet.
  inline void Sub(const float* input1_data, const Dims<4>& input1_dims,
  const float* input2_data, const Dims<4>& input2_dims,
  