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Merged
sdatkinson merged 1 commit into from
Mar 13, 2026
Merged

Formatting #245

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355 changes: 176 additions & 179 deletions NAM/conv1d.cpp
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4 changes: 2 additions & 2 deletions NAM/convnet.cpp
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Expand Up @@ -341,8 +341,8 @@ nam::convnet::ConvNetConfig nam::convnet::parse_config_json(const nlohmann::json
// ConvNetConfig::create()
std::unique_ptr<nam::DSP> nam::convnet::ConvNetConfig::create(std::vector<float> weights, double sampleRate)
{
return std::make_unique<nam::convnet::ConvNet>(in_channels, out_channels, channels, dilations, batchnorm, activation,
weights, sampleRate, groups);
return std::make_unique<nam::convnet::ConvNet>(
in_channels, out_channels, channels, dilations, batchnorm, activation, weights, sampleRate, groups);
}

// Config parser for ConfigParserRegistry
Expand Down
115 changes: 58 additions & 57 deletions NAM/dsp.cpp
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Expand Up @@ -498,7 +498,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int f = 0; f < num_frames; f++)
{
const float in_val = input_ptr[f * in_stride];
output_ptr[f * 2] = w0 * in_val;
output_ptr[f * 2] = w0 * in_val;
output_ptr[f * 2 + 1] = w1 * in_val;
}
}
Expand All @@ -508,7 +508,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int f = 0; f < num_frames; f++)
{
const float in_val = input_ptr[f * in_stride];
output_ptr[f * 3] = w0 * in_val;
output_ptr[f * 3] = w0 * in_val;
output_ptr[f * 3 + 1] = w1 * in_val;
output_ptr[f * 3 + 2] = w2 * in_val;
}
Expand All @@ -520,7 +520,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int f = 0; f < num_frames; f++)
{
const float in_val = input_ptr[f * in_stride];
output_ptr[f * 4] = w0 * in_val;
output_ptr[f * 4] = w0 * in_val;
output_ptr[f * 4 + 1] = w1 * in_val;
output_ptr[f * 4 + 2] = w2 * in_val;
output_ptr[f * 4 + 3] = w3 * in_val;
Expand Down Expand Up @@ -567,7 +567,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float* __restrict__ in_col = input_ptr + f * in_stride;
const float i0 = in_col[0];
const float i1 = in_col[1];
output_ptr[f * 2] = w00 * i0 + w01 * i1;
output_ptr[f * 2] = w00 * i0 + w01 * i1;
output_ptr[f * 2 + 1] = w10 * i0 + w11 * i1;
}
}
Expand All @@ -584,7 +584,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float i1 = in_col[1];
const float i2 = in_col[2];
const float i3 = in_col[3];
output_ptr[f * 2] = w00 * i0 + w01 * i1 + w02 * i2 + w03 * i3;
output_ptr[f * 2] = w00 * i0 + w01 * i1 + w02 * i2 + w03 * i3;
output_ptr[f * 2 + 1] = w10 * i0 + w11 * i1 + w12 * i2 + w13 * i3;
}
}
Expand All @@ -595,8 +595,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int f = 0; f < num_frames; f++)
{
const float* __restrict__ in_col = input_ptr + f * in_stride;
output_ptr[f] = w0 * in_col[0] + w1 * in_col[1]
+ w2 * in_col[2] + w3 * in_col[3];
output_ptr[f] = w0 * in_col[0] + w1 * in_col[1] + w2 * in_col[2] + w3 * in_col[3];
}
}
else if (out_ch == 4 && in_ch == 2)
Expand All @@ -608,7 +607,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float* __restrict__ in_col = input_ptr + f * in_stride;
const float i0 = in_col[0];
const float i1 = in_col[1];
output_ptr[f * 4] = w00 * i0 + w01 * i1;
output_ptr[f * 4] = w00 * i0 + w01 * i1;
output_ptr[f * 4 + 1] = w10 * i0 + w11 * i1;
output_ptr[f * 4 + 2] = w20 * i0 + w21 * i1;
output_ptr[f * 4 + 3] = w30 * i0 + w31 * i1;
Expand All @@ -628,7 +627,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float i0 = in_col[0];
const float i1 = in_col[1];
const float i2 = in_col[2];
output_ptr[f * 3] = w00 * i0 + w01 * i1 + w02 * i2 + b0;
output_ptr[f * 3] = w00 * i0 + w01 * i1 + w02 * i2 + b0;
output_ptr[f * 3 + 1] = w10 * i0 + w11 * i1 + w12 * i2 + b1;
output_ptr[f * 3 + 2] = w20 * i0 + w21 * i1 + w22 * i2 + b2;
}
Expand All @@ -642,17 +641,17 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float i0 = in_col[0];
const float i1 = in_col[1];
const float i2 = in_col[2];
output_ptr[f * 3] = w00 * i0 + w01 * i1 + w02 * i2;
output_ptr[f * 3] = w00 * i0 + w01 * i1 + w02 * i2;
output_ptr[f * 3 + 1] = w10 * i0 + w11 * i1 + w12 * i2;
output_ptr[f * 3 + 2] = w20 * i0 + w21 * i1 + w22 * i2;
}
}
}
else if (out_ch == 4 && in_ch == 4)
{
const float w00 = weight_ptr[0], w10 = weight_ptr[1], w20 = weight_ptr[2], w30 = weight_ptr[3];
const float w01 = weight_ptr[4], w11 = weight_ptr[5], w21 = weight_ptr[6], w31 = weight_ptr[7];
const float w02 = weight_ptr[8], w12 = weight_ptr[9], w22 = weight_ptr[10], w32 = weight_ptr[11];
const float w00 = weight_ptr[0], w10 = weight_ptr[1], w20 = weight_ptr[2], w30 = weight_ptr[3];
const float w01 = weight_ptr[4], w11 = weight_ptr[5], w21 = weight_ptr[6], w31 = weight_ptr[7];
const float w02 = weight_ptr[8], w12 = weight_ptr[9], w22 = weight_ptr[10], w32 = weight_ptr[11];
const float w03 = weight_ptr[12], w13 = weight_ptr[13], w23 = weight_ptr[14], w33 = weight_ptr[15];
for (int f = 0; f < num_frames; f++)
{
Expand All @@ -661,7 +660,7 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float i1 = in_col[1];
const float i2 = in_col[2];
const float i3 = in_col[3];
output_ptr[f * 4] = w00 * i0 + w01 * i1 + w02 * i2 + w03 * i3;
output_ptr[f * 4] = w00 * i0 + w01 * i1 + w02 * i2 + w03 * i3;
output_ptr[f * 4 + 1] = w10 * i0 + w11 * i1 + w12 * i2 + w13 * i3;
output_ptr[f * 4 + 2] = w20 * i0 + w21 * i1 + w22 * i2 + w23 * i3;
output_ptr[f * 4 + 3] = w30 * i0 + w31 * i1 + w32 * i2 + w33 * i3;
Expand All @@ -677,8 +676,8 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
const float i3 = in_col[3], i4 = in_col[4], i5 = in_col[5];
for (int o = 0; o < 6; o++)
{
out_col[o] = weight_ptr[o] * i0 + weight_ptr[6 + o] * i1 + weight_ptr[12 + o] * i2
+ weight_ptr[18 + o] * i3 + weight_ptr[24 + o] * i4 + weight_ptr[30 + o] * i5;
out_col[o] = weight_ptr[o] * i0 + weight_ptr[6 + o] * i1 + weight_ptr[12 + o] * i2 + weight_ptr[18 + o] * i3
+ weight_ptr[24 + o] * i4 + weight_ptr[30 + o] * i5;
}
}
}
Expand All @@ -693,7 +692,8 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int o = 0; o < 8; o++)
{
out_col[o] = weight_ptr[o] * i0 + weight_ptr[8 + o] * i1 + weight_ptr[16 + o] * i2 + weight_ptr[24 + o] * i3
+ weight_ptr[32 + o] * i4 + weight_ptr[40 + o] * i5 + weight_ptr[48 + o] * i6 + weight_ptr[56 + o] * i7;
+ weight_ptr[32 + o] * i4 + weight_ptr[40 + o] * i5 + weight_ptr[48 + o] * i6
+ weight_ptr[56 + o] * i7;
}
}
}
Expand All @@ -708,7 +708,8 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
for (int o = 0; o < 4; o++)
{
out_col[o] = weight_ptr[o] * i0 + weight_ptr[4 + o] * i1 + weight_ptr[8 + o] * i2 + weight_ptr[12 + o] * i3
+ weight_ptr[16 + o] * i4 + weight_ptr[20 + o] * i5 + weight_ptr[24 + o] * i6 + weight_ptr[28 + o] * i7;
+ weight_ptr[16 + o] * i4 + weight_ptr[20 + o] * i5 + weight_ptr[24 + o] * i6
+ weight_ptr[28 + o] * i7;
}
}
}
Expand Down Expand Up @@ -754,56 +755,56 @@ void nam::Conv1x1::process_(const Eigen::Ref<const Eigen::MatrixXf>& input, cons
#ifdef NAM_USE_INLINE_GEMM
if (!bias_fused)
{
const int out_ch = (int)get_out_channels();
float* __restrict__ output_ptr = _output.data();
const float* __restrict__ bias_ptr = this->_bias.data();
const int out_ch = (int)get_out_channels();
float* __restrict__ output_ptr = _output.data();
const float* __restrict__ bias_ptr = this->_bias.data();

// Specialized paths for common small channel counts
if (out_ch == 2)
{
const float b0 = bias_ptr[0], b1 = bias_ptr[1];
for (int f = 0; f < num_frames; f++)
// Specialized paths for common small channel counts
if (out_ch == 2)
{
const int off = f * 2;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
const float b0 = bias_ptr[0], b1 = bias_ptr[1];
for (int f = 0; f < num_frames; f++)
{
const int off = f * 2;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
}
}
}
else if (out_ch == 3)
{
const float b0 = bias_ptr[0], b1 = bias_ptr[1], b2 = bias_ptr[2];
for (int f = 0; f < num_frames; f++)
else if (out_ch == 3)
{
const int off = f * 3;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
output_ptr[off + 2] += b2;
const float b0 = bias_ptr[0], b1 = bias_ptr[1], b2 = bias_ptr[2];
for (int f = 0; f < num_frames; f++)
{
const int off = f * 3;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
output_ptr[off + 2] += b2;
}
}
}
else if (out_ch == 4)
{
const float b0 = bias_ptr[0], b1 = bias_ptr[1];
const float b2 = bias_ptr[2], b3 = bias_ptr[3];
for (int f = 0; f < num_frames; f++)
else if (out_ch == 4)
{
const int off = f * 4;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
output_ptr[off + 2] += b2;
output_ptr[off + 3] += b3;
const float b0 = bias_ptr[0], b1 = bias_ptr[1];
const float b2 = bias_ptr[2], b3 = bias_ptr[3];
for (int f = 0; f < num_frames; f++)
{
const int off = f * 4;
output_ptr[off] += b0;
output_ptr[off + 1] += b1;
output_ptr[off + 2] += b2;
output_ptr[off + 3] += b3;
}
}
}
else
{
for (int f = 0; f < num_frames; f++)
else
{
float* __restrict__ out_col = output_ptr + f * out_ch;
for (int o = 0; o < out_ch; o++)
for (int f = 0; f < num_frames; f++)
{
out_col[o] += bias_ptr[o];
float* __restrict__ out_col = output_ptr + f * out_ch;
for (int o = 0; o < out_ch; o++)
{
out_col[o] += bias_ptr[o];
}
}
}
}
} // !bias_fused
#else
_output.leftCols(num_frames).colwise() += this->_bias;
Expand Down
4 changes: 2 additions & 2 deletions NAM/dsp.h
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Expand Up @@ -27,8 +27,8 @@
/// \brief Use a sample rate of -1 if we don't know what the model expects to be run at
#define NAM_UNKNOWN_EXPECTED_SAMPLE_RATE -1.0

#if defined(_MSC_VER) && !defined(__llvm__)
#define __restrict__ __restrict
#if defined(_MSC_VER) && !defined(__llvm__)
#define __restrict__ __restrict
#endif

namespace nam
Expand Down
4 changes: 2 additions & 2 deletions NAM/film.h
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Expand Up @@ -123,7 +123,7 @@ class FiLM
int i = 0;
for (; i + 3 < input_dim; i += 4)
{
out_col[i] = in_col[i] * scale_col[i] + shift_col[i];
out_col[i] = in_col[i] * scale_col[i] + shift_col[i];
out_col[i + 1] = in_col[i + 1] * scale_col[i + 1] + shift_col[i + 1];
out_col[i + 2] = in_col[i + 2] * scale_col[i + 2] + shift_col[i + 2];
out_col[i + 3] = in_col[i + 3] * scale_col[i + 3] + shift_col[i + 3];
Expand Down Expand Up @@ -161,7 +161,7 @@ class FiLM
int i = 0;
for (; i + 3 < input_dim; i += 4)
{
out_col[i] = in_col[i] * scale_col[i];
out_col[i] = in_col[i] * scale_col[i];
out_col[i + 1] = in_col[i + 1] * scale_col[i + 1];
out_col[i + 2] = in_col[i + 2] * scale_col[i + 2];
out_col[i + 3] = in_col[i + 3] * scale_col[i + 3];
Expand Down
4 changes: 2 additions & 2 deletions NAM/gating_activations.h
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Expand Up @@ -72,7 +72,7 @@ class GatingActivation
const int input_stride = (int)input.outerStride();
const float* __restrict__ input_ptr = input.derived().data();
float* __restrict__ output_ptr = output.derived().data();
const int output_stride = (int)output.outerStride(); // Column stride for output
const int output_stride = (int)output.outerStride(); // Column stride for output

for (int f = 0; f < num_samples; f++)
{
Expand Down Expand Up @@ -178,7 +178,7 @@ class BlendingActivation
const int input_stride = (int)input.outerStride();
const float* __restrict__ input_ptr = input.derived().data();
float* __restrict__ output_ptr = output.derived().data();
const int output_stride = (int)output.outerStride(); // Column stride for output
const int output_stride = (int)output.outerStride(); // Column stride for output

for (int f = 0; f < num_samples; f++)
{
Expand Down
4 changes: 2 additions & 2 deletions NAM/lstm.cpp
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Expand Up @@ -179,8 +179,8 @@ nam::lstm::LSTMConfig nam::lstm::parse_config_json(const nlohmann::json& config)
// LSTMConfig::create()
std::unique_ptr<nam::DSP> nam::lstm::LSTMConfig::create(std::vector<float> weights, double sampleRate)
{
return std::make_unique<nam::lstm::LSTM>(in_channels, out_channels, num_layers, input_size, hidden_size, weights,
sampleRate);
return std::make_unique<nam::lstm::LSTM>(
in_channels, out_channels, num_layers, input_size, hidden_size, weights, sampleRate);
}

// Config parser for ConfigParserRegistry
Expand Down
8 changes: 4 additions & 4 deletions tools/render.cpp
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Expand Up @@ -38,7 +38,7 @@ bool SaveWavFloat32(const char* fileName, const float* samples, size_t numSample
const uint32_t fmtSize = 16;
out.write("fmt ", 4);
out.write(reinterpret_cast<const char*>(&fmtSize), 4);
const uint16_t audioFormat = 3; // IEEE float
const uint16_t audioFormat = 3; // IEEE float
out.write(reinterpret_cast<const char*>(&audioFormat), 2);
const uint16_t numChannels = 1;
out.write(reinterpret_cast<const char*>(&numChannels), 2);
Expand All @@ -59,7 +59,7 @@ bool SaveWavFloat32(const char* fileName, const float* samples, size_t numSample
return out.good();
}

} // namespace
} // namespace

int main(int argc, char* argv[])
{
Expand Down Expand Up @@ -138,8 +138,8 @@ int main(int argc, char* argv[])
const double expectedRate = model->GetExpectedSampleRate();
if (expectedRate > 0 && std::abs(inputSampleRate - expectedRate) > 0.5)
{
std::cerr << "Error: Input WAV sample rate (" << inputSampleRate
<< " Hz) does not match model expected rate (" << expectedRate << " Hz)\n";
std::cerr << "Error: Input WAV sample rate (" << inputSampleRate << " Hz) does not match model expected rate ("
<< expectedRate << " Hz)\n";
return 1;
}

Expand Down
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