80 lines
4.5 KiB
C++
80 lines
4.5 KiB
C++
#include <kernels/cpu/cpu_kernels.h>
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#include <runtime/kernel_registry.h>
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#include <targets/cpu/cpu_ops_body.h>
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using namespace nncase;
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using namespace nncase::runtime;
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namespace nncase
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{
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namespace targets
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{
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namespace cpu
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{
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kernel_call_result cpu_conv2d(cpu_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
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{
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auto input = interpreter.memory_at<float>(options.input);
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auto output = interpreter.memory_at<float>(options.output);
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kernels::cpu::conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.out_channels, options.filter_h,
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options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation);
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return kcr_done;
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}
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kernel_call_result cpu_depthwise_conv2d(cpu_depthwise_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
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{
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auto input = interpreter.memory_at<float>(options.input);
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auto output = interpreter.memory_at<float>(options.output);
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kernels::cpu::depthwise_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.filter_h,
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options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation);
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return kcr_done;
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}
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runtime::kernel_call_result cpu_reduce_window2d(cpu_reduce_window2d_options &options, interpreter_t &interpreter, runtime::interpreter_step_t step)
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{
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auto input = interpreter.memory_at<float>(options.input);
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auto output = interpreter.memory_at<float>(options.output);
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auto reduce = [&](auto binary_op, auto window_op) {
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kernels::cpu::reduce_window2d(input.data(), output.data(), options.init_value, options.in_shape, options.filter_h, options.filter_w, options.stride_h,
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options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation, binary_op, window_op);
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};
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switch (options.reduce_op)
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{
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case reduce_mean:
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reduce([](auto a, auto b) { return a + b; }, [](auto v, auto k) { return v / k; });
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return runtime::kcr_done;
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case reduce_min:
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reduce([](auto a, auto b) { return std::min(a, b); }, [](auto v, auto k) { return v; });
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return runtime::kcr_done;
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case reduce_max:
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reduce([](auto a, auto b) { return std::max(a, b); }, [](auto v, auto k) { return v; });
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return kcr_done;
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default:
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return kcr_error;
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}
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}
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kernel_call_result cpu_quantized_conv2d(cpu_quantized_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
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{
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auto input = interpreter.memory_at<uint8_t>(options.input);
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auto output = interpreter.memory_at<uint8_t>(options.output);
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kernels::cpu::quantized_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.out_channels, options.filter_h,
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options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w,
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options.input_offset, options.filter_offset, options.output_mul, options.output_shift, options.output_offset);
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return kcr_done;
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}
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kernel_call_result cpu_quantized_depthwise_conv2d(cpu_quantized_depthwise_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
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{
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auto input = interpreter.memory_at<uint8_t>(options.input);
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auto output = interpreter.memory_at<uint8_t>(options.output);
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kernels::cpu::quantized_depthwise_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.filter_h,
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options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w,
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options.input_offset, options.filter_offset, options.output_mul, options.output_shift, options.output_offset);
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return kcr_done;
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}
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}
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}
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}
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