RTC_[D]CHECK_op: Remove "u" suffix on integer constants

webrtc/modules/audio_processing/beamformer/nonlinear_beamformer.cc

 /*
  *  Copyright (c) 2014 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */
 
@@ skipping 61 matching lines @@
 // To compensate for the attenuation this algorithm introduces to the target
 // signal. It was estimated empirically from a low-noise low-reverberation
 // recording from broadside.
 const float kCompensationGain = 2.f;
 
 // Does conjugate(|norm_mat|) * |mat| * transpose(|norm_mat|). No extra space is
 // used; to accomplish this, we compute both multiplications in the same loop.
 // The returned norm is clamped to be non-negative.
 float Norm(const ComplexMatrix<float>& mat,
            const ComplexMatrix<float>& norm_mat) {
-  RTC_CHECK_EQ(1u, norm_mat.num_rows());
+  RTC_CHECK_EQ(1, norm_mat.num_rows());
   RTC_CHECK_EQ(norm_mat.num_columns(), mat.num_rows());
   RTC_CHECK_EQ(norm_mat.num_columns(), mat.num_columns());
 
   complex<float> first_product = complex<float>(0.f, 0.f);
   complex<float> second_product = complex<float>(0.f, 0.f);
 
   const complex<float>* const* mat_els = mat.elements();
   const complex<float>* const* norm_mat_els = norm_mat.elements();
 
   for (size_t i = 0; i < norm_mat.num_columns(); ++i) {
     for (size_t j = 0; j < norm_mat.num_columns(); ++j) {
       first_product += conj(norm_mat_els[0][j]) * mat_els[j][i];
     }
     second_product += first_product * norm_mat_els[0][i];
     first_product = 0.f;
   }
   return std::max(second_product.real(), 0.f);
 }
 
 // Does conjugate(|lhs|) * |rhs| for row vectors |lhs| and |rhs|.
 complex<float> ConjugateDotProduct(const ComplexMatrix<float>& lhs,
                                    const ComplexMatrix<float>& rhs) {
-  RTC_CHECK_EQ(1u, lhs.num_rows());
-  RTC_CHECK_EQ(1u, rhs.num_rows());
+  RTC_CHECK_EQ(1, lhs.num_rows());
+  RTC_CHECK_EQ(1, rhs.num_rows());
   RTC_CHECK_EQ(lhs.num_columns(), rhs.num_columns());
 
   const complex<float>* const* lhs_elements = lhs.elements();
   const complex<float>* const* rhs_elements = rhs.elements();
 
   complex<float> result = complex<float>(0.f, 0.f);
   for (size_t i = 0; i < lhs.num_columns(); ++i) {
     result += conj(lhs_elements[0][i]) * rhs_elements[0][i];
   }
 
@@ skipping 14 matching lines @@
       float abs_value = std::abs(mat_els[i][j]);
       sum_squares += abs_value * abs_value;
     }
   }
   return sum_squares;
 }
 
 // Does |out| = |in|.' * conj(|in|) for row vector |in|.
 void TransposedConjugatedProduct(const ComplexMatrix<float>& in,
                                  ComplexMatrix<float>* out) {
-  RTC_CHECK_EQ(1u, in.num_rows());
+  RTC_CHECK_EQ(1, in.num_rows());
   RTC_CHECK_EQ(out->num_rows(), in.num_columns());
   RTC_CHECK_EQ(out->num_columns(), in.num_columns());
   const complex<float>* in_elements = in.elements()[0];
   complex<float>* const* out_elements = out->elements();
   for (size_t i = 0; i < out->num_rows(); ++i) {
     for (size_t j = 0; j < out->num_columns(); ++j) {
       out_elements[i][j] = in_elements[i] * conj(in_elements[j]);
     }
   }
 }
@@ skipping 290 matching lines @@
 
 bool NonlinearBeamformer::is_target_present() { return is_target_present_; }
 
 void NonlinearBeamformer::ProcessAudioBlock(const complex_f* const* input,
                                             size_t num_input_channels,
                                             size_t num_freq_bins,
                                             size_t num_output_channels,
                                             complex_f* const* output) {
   RTC_CHECK_EQ(kNumFreqBins, num_freq_bins);
   RTC_CHECK_EQ(num_input_channels_, num_input_channels);
-  RTC_CHECK_EQ(0u, num_output_channels);
+  RTC_CHECK_EQ(0, num_output_channels);
 
   // Calculating the post-filter masks. Note that we need two for each
   // frequency bin to account for the positive and negative interferer
   // angle.
   for (size_t i = low_mean_start_bin_; i <= high_mean_end_bin_; ++i) {
     eig_m_.CopyFromColumn(input, i, num_input_channels_);
     float eig_m_norm_factor = std::sqrt(SumSquares(eig_m_));
     if (eig_m_norm_factor != 0.f) {
       eig_m_.Scale(1.f / eig_m_norm_factor);
     }
@@ skipping 125 matching lines @@
                    new_mask_ + high_mean_end_bin_ + 1);
   if (new_mask_[quantile] > kMaskTargetThreshold) {
     is_target_present_ = true;
     interference_blocks_count_ = 0;
   } else {
     is_target_present_ = interference_blocks_count_++ < hold_target_blocks_;
   }
 }
 
 }  // namespace webrtc