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Migrate conv2d layer to Tensor

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This commit is contained in:
Matúš Námešný
2025-11-19 20:20:46 +01:00
parent 10c84d75fc
commit dfdfa19022
10 changed files with 226 additions and 290 deletions
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20
src/layers/dense.cpp
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@@ -5,34 +5,30 @@
using namespace CUDANet::Layers;
Dense::Dense(CUDANet::Backend* backend, CUDANet::Shape in, CUDANet::Shape out)
Dense::Dense(CUDANet::Shape in, CUDANet::Shape out, CUDANet::Backend* backend)
: backend(backend),
in_shape(in),
out_shape(out),
weights(
CUDANet::Tensor(Shape{in[0] * out[0]}, CUDANet::DType::FLOAT32, backend)
),
biases(CUDANet::Tensor(Shape{out[0]}, CUDANet::DType::FLOAT32, backend)),
output(CUDANet::Tensor(Shape{out[0]}, CUDANet::DType::FLOAT32, backend)) {
// Allocate memory for weights and biases
out_shape(out) {
if (in.size() != 1) {
throw std::runtime_error(
std::format("Invalid shape. Expected [1], got {}", in)
std::format("Invalid shape. Expected [1], got {}", in_shape)
);
}
if (out.size() != 1) {
throw std::runtime_error(
std::format("Invalid shape. Expected [1], got {}", out)
std::format("Invalid shape. Expected [1], got {}", out_shape)
);
}
auto input_len = in[0];
auto output_len = out[0];
weights = CUDANet::Tensor(Shape{in[0] * out[0]}, CUDANet::DType::FLOAT32, backend);
biases = CUDANet::Tensor(Shape{out[0]}, CUDANet::DType::FLOAT32, backend);
output = CUDANet::Tensor(Shape{out[0]}, CUDANet::DType::FLOAT32, backend);
weights.zero();
biases.zero();
output.zero();
}
Dense::~Dense() {}