kendryte-standalone-sdk/lib/nncase/v0/runtime/cpu/cpu_ops.cpp

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5.1 KiB
C++

/* Copyright 2019-2020 Canaan Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <kernels/cpu/cpu_kernels.h>
#include <runtime/kernel_registry.h>
#include <runtime/cpu/cpu_ops_body.h>
using namespace nncase;
using namespace nncase::runtime;
namespace nncase
{
namespace runtime
{
namespace cpu
{
kernel_call_result cpu_conv2d(cpu_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
{
auto input = interpreter.memory_at<float>(options.input);
auto output = interpreter.memory_at<float>(options.output);
kernels::cpu::conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.out_channels, options.filter_h,
options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation);
return kcr_done;
}
kernel_call_result cpu_depthwise_conv2d(cpu_depthwise_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
{
auto input = interpreter.memory_at<float>(options.input);
auto output = interpreter.memory_at<float>(options.output);
kernels::cpu::depthwise_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.filter_h,
options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation);
return kcr_done;
}
runtime::kernel_call_result cpu_reduce_window2d(cpu_reduce_window2d_options &options, interpreter_t &interpreter, runtime::interpreter_step_t step)
{
auto input = interpreter.memory_at<float>(options.input);
auto output = interpreter.memory_at<float>(options.output);
auto reduce = [&](auto binary_op, auto window_op) {
kernels::cpu::reduce_window2d(input.data(), output.data(), options.init_value, options.in_shape, options.filter_h, options.filter_w, options.stride_h,
options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w, options.fused_activation, binary_op, window_op);
};
switch (options.reduce_op)
{
case reduce_mean:
reduce([](auto a, auto b) { return a + b; }, [](auto v, auto k) { return v / k; });
return runtime::kcr_done;
case reduce_min:
reduce([](auto a, auto b) { return std::min(a, b); }, [](auto v, auto k) { return v; });
return runtime::kcr_done;
case reduce_max:
reduce([](auto a, auto b) { return std::max(a, b); }, [](auto v, auto k) { return v; });
return kcr_done;
default:
return kcr_error;
}
}
kernel_call_result cpu_quantized_conv2d(cpu_quantized_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
{
auto input = interpreter.memory_at<uint8_t>(options.input);
auto output = interpreter.memory_at<uint8_t>(options.output);
kernels::cpu::quantized_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.out_channels, options.filter_h,
options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w,
options.input_offset, options.filter_offset, options.output_mul, options.output_shift, options.output_offset);
return kcr_done;
}
kernel_call_result cpu_quantized_depthwise_conv2d(cpu_quantized_depthwise_conv2d_options &options, interpreter_t &interpreter, interpreter_step_t step)
{
auto input = interpreter.memory_at<uint8_t>(options.input);
auto output = interpreter.memory_at<uint8_t>(options.output);
kernels::cpu::quantized_depthwise_conv2d(input.data(), output.data(), options.weights.data(), options.bias.data(), options.in_shape, options.filter_h,
options.filter_w, options.stride_h, options.stride_w, options.dilation_h, options.dilation_w, options.padding_h, options.padding_w,
options.input_offset, options.filter_offset, options.output_mul, options.output_shift, options.output_offset);
return kcr_done;
}
}
}
}