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提交 d6d3def7 编写于 作者: H hjchen2
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Implement int8 depthwise conv3x3s1

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src/operators/math/depthwise_conv3x3_int8.cpp 0 → 100644
浏览文件 @ d6d3def7
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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 "operators/math/depthwise_conv3x3_int8.h"
namespace paddle_mobile {
namespace operators {
namespace math {
void DepthwiseConv3x3_int8(const framework::Tensor *input,
const framework::Tensor *filter,
const std::vector<int> &strides,
framework::Tensor *output) {
PADDLE_MOBILE_THROW_EXCEPTION(
"Depthwise conv with generic strides has not been implemented.");
}
void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
const framework::Tensor &filter,
framework::Tensor *output) {
const int8_t *input_data = input.data<int8_t>();
const int8_t *filter_data = filter.data<int8_t>();
int32_t *out_data = output->mutable_data<int32_t>();
// make sure that batch size is 1
int input_c = input.dims()[1];
int input_h = input.dims()[2];
int input_w = input.dims()[3];
int output_c = output->dims()[1];
int output_h = output->dims()[2];
int output_w = output->dims()[3];
int image_size = input_h * input_w;
int out_image_size = output_h * output_w;
memset(out_data, 0, output_c * out_image_size * sizeof(int32_t));
#if __aarch64__
// TODO(hjchen2)
#else
#pragma omp parallel for
for (int g = 0; g < input_c; ++g) {
const int8_t* input_ptr0 = input_data + g * image_size;
const int8_t* input_ptr1 = input_ptr0 + input_w;
const int8_t* input_ptr2 = input_ptr1 + input_w;
const int8_t* input_ptr3 = input_ptr2 + input_w;
const int8_t* input_ptr4 = input_ptr3 + input_w;
const int8_t* input_ptr5 = input_ptr4 + input_w;
const int8_t* filter_ptr = filter_data + g * 9;
int32_t* output_ptr0 = out_data + g * out_image_size;
int32_t* output_ptr1 = output_ptr0 + output_w;
int32_t* output_ptr2 = output_ptr1 + output_w;
int32_t* output_ptr3 = output_ptr2 + output_w;
for (int h = 0; h < input_h - 5 /*(input_h - 2) - 3*/; h += 4) {
int loop = (input_w - 2) / 6;
int remain = input_w - loop * 6;
asm volatile(
"vld1.32 {q0}, [%[filter_ptr]] \n"
"vmovl.s8 q14, d0 \n"
"vmovl.s8 q15, d1 \n"
"vdup.s16 d0, d28[0] \n"
"vdup.s16 d1, d28[1] \n"
"vdup.s16 d2, d28[2] \n"
"vdup.s16 d3, d28[3] \n"
"vdup.s16 d4, d29[0] \n"
"vdup.s16 d5, d29[1] \n"
"vdup.s16 d6, d29[2] \n"
"vdup.s16 d7, d29[3] \n"
"vdup.s16 d8, d30[0] \n"
:
: [filter_ptr] "r"(filter_ptr)
: "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
asm volatile(
"mov r0, #6 \n"
"cmp %[loop], #0 \n"
"ble start_remain_%= \n"
// loop 8 widths
"loop_4h8w_%=: \n"
"vld1.32 {d9}, [%[input_ptr0]], r0 \n"
"vld1.32 {d10}, [%[input_ptr1]], r0 \n"
"vld1.32 {d11}, [%[input_ptr2]], r0 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q10, d14, d0 \n"
"vmlal.s16 q10, d16, d1 \n"
"vmlal.s16 q10, d18, d2 \n"
"vmull.s16 q11, d15, d0 \n"
"vmlal.s16 q11, d17, d1 \n"
"vmlal.s16 q11, d19, d2 \n"
"vext.s8 d12, d10, #1 \n"
"vext.s8 d13, d10, #2 \n"
"vmovl.s8 q7, d10 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q12, d14, d0 \n"
"vmlal.s16 q12, d16, d1 \n"
"vmlal.s16 q12, d18, d2 \n"
"vmull.s16 q13, d15, d0 \n"
"vmlal.s16 q13, d17, d1 \n"
"vmlal.s16 q13, d19, d2 \n"
"vmlal.s16 q10, d14, d3 \n"
"vmlal.s16 q10, d16, d4 \n"
"vmlal.s16 q10, d18, d5 \n"
"vmull.s16 q11, d15, d3 \n"
"vmlal.s16 q11, d17, d4 \n"
"vmlal.s16 q11, d19, d5 \n"
"vext.s8 d12, d11, #1 \n"
"vext.s8 d13, d11, #2 \n"
"vmovl.s8 q7, d10 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q14, d14, d0 \n"
"vmlal.s16 q14, d16, d1 \n"
"vmlal.s16 q14, d18, d2 \n"
"vmull.s16 q15, d15, d0 \n"
"vmlal.s16 q15, d17, d1 \n"
"vmlal.s16 q15, d19, d2 \n"
"vmlal.s16 q12, d14, d3 \n"
"vmlal.s16 q12, d16, d4 \n"
"vmlal.s16 q12, d18, d5 \n"
"vmull.s16 q13, d15, d3 \n"
"vmlal.s16 q13, d17, d4 \n"
"vmlal.s16 q13, d19, d5 \n"
"vmlal.s16 q10, d14, d6 \n"
"vmlal.s16 q10, d16, d7 \n"
"vmlal.s16 q10, d18, d8 \n"
"vmull.s16 q11, d15, d6 \n"
"vmlal.s16 q11, d17, d7 \n"
"vmlal.s16 q11, d19, d8 \n"
// store row 0, reuse q10/q11
"vst1.32 {d20-d22}, [%[output_ptr0]]! \n"
"vld1.32 {d9}, [%[input_ptr3]], r0 \n"
"vld1.32 {d10}, [%[input_ptr4]], r0 \n"
"vld1.32 {d11}, [%[input_ptr5]], r0 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q10, d14, d0 \n"
"vmlal.s16 q10, d16, d1 \n"
"vmlal.s16 q10, d18, d2 \n"
"vmull.s16 q11, d15, d0 \n"
"vmlal.s16 q11, d17, d1 \n"
"vmlal.s16 q11, d19, d2 \n"
"vmlal.s16 q12, d14, d6 \n"
"vmlal.s16 q12, d16, d7 \n"
"vmlal.s16 q12, d18, d8 \n"
"vmlal.s16 q13, d15, d6 \n"
"vmlal.s16 q13, d17, d7 \n"
"vmlal.s16 q13, d19, d8 \n"
// store row 1
"vst1.32 {d24-d26}, [%[output_ptr1]]! \n"
"vmlal.s16 q14, d14, d3 \n"
"vmlal.s16 q14, d16, d4 \n"
"vmlal.s16 q14, d18, d5 \n"
"vmlal.s16 q15, d15, d3 \n"
"vmlal.s16 q15, d17, d4 \n"
"vmlal.s16 q15, d19, d5 \n"
"vext.s8 d12, d10, #1 \n"
"vext.s8 d13, d10, #2 \n"
"vmovl.s8 q7, d10 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmlal.s16 q10, d14, d3 \n"
"vmlal.s16 q10, d16, d4 \n"
"vmlal.s16 q10, d18, d5 \n"
"vmull.s16 q11, d15, d3 \n"
"vmlal.s16 q11, d17, d4 \n"
"vmlal.s16 q11, d19, d5 \n"
"vmull.s16 q14, d14, d6 \n"
"vmlal.s16 q14, d16, d7 \n"
"vmlal.s16 q14, d18, d8 \n"
"vmull.s16 q15, d15, d6 \n"
"vmlal.s16 q15, d17, d7 \n"
"vmlal.s16 q15, d19, d8 \n"
// store row 2
"vst1.32 {d24-d26}, [%[output_ptr2]]! \n"
"vext.s8 d12, d11, #1 \n"
"vext.s8 d13, d11, #2 \n"
"vmovl.s8 q7, d10 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q10, d14, d6 \n"
"vmlal.s16 q10, d16, d7 \n"
"vmlal.s16 q10, d18, d8 \n"
"vmull.s16 q11, d15, d6 \n"
"vmlal.s16 q11, d17, d7 \n"
"vmlal.s16 q11, d19, d8 \n"
// store row 3
"vst1.32 {d20-d22}, [%[output_ptr3]]! \n"
"subs %[loop], #1 \n"
"bne loop_4h8w_%= \n"
"start_remain_%=: \n"
"cmp %[remain], #0 \n"
"ble end_%= \n"
"mov r0, %[remain] \n"
"add r0, #2 \n"
"vld1.32 {d9}, [%[input_ptr0]], r0 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q10, d14, d0 \n"
"vmlal.s16 q10, d16, d1 \n"
"vmlal.s16 q10, d18, d2 \n"
"vld1.32 {d9}, [%[input_ptr1]], r0 \n"
"vmull.s16 q11, d15, d0 \n"
"vmlal.s16 q11, d17, d1 \n"
"vmlal.s16 q11, d19, d2 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q12, d14, d0 \n"
"vmlal.s16 q12, d16, d1 \n"
"vmlal.s16 q12, d18, d2 \n"
"vmull.s16 q13, d15, d0 \n"
"vmlal.s16 q13, d17, d1 \n"
"vmlal.s16 q13, d19, d2 \n"
"vmlal.s16 q10, d14, d3 \n"
"vmlal.s16 q10, d16, d4 \n"
"vmlal.s16 q10, d18, d5 \n"
"vld1.32 {d9}, [%[input_ptr2]], r0 \n"
"vmull.s16 q11, d15, d3 \n"
"vmlal.s16 q11, d17, d4 \n"
"vmlal.s16 q11, d19, d5 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q14, d14, d0 \n"
"vmlal.s16 q14, d16, d1 \n"
"vmlal.s16 q14, d18, d2 \n"
"vmull.s16 q15, d15, d0 \n"
"vmlal.s16 q15, d17, d1 \n"
"vmlal.s16 q15, d19, d2 \n"
"vmlal.s16 q12, d14, d3 \n"
"vmlal.s16 q12, d16, d4 \n"
"vmlal.s16 q12, d18, d5 \n"
"vmull.s16 q13, d15, d3 \n"
"vmlal.s16 q13, d17, d4 \n"
"vmlal.s16 q13, d19, d5 \n"
"vmlal.s16 q10, d14, d6 \n"
"vmlal.s16 q10, d16, d7 \n"
"vmlal.s16 q10, d18, d8 \n"
"vld1.32 {d9}, [%[input_ptr3]], r0 \n"
"vmull.s16 q11, d15, d6 \n"
"vmlal.s16 q11, d17, d7 \n"
"vmlal.s16 q11, d19, d8 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q5, d14, d0 \n"
"vmlal.s16 q5, d16, d1 \n"
"vmlal.s16 q5, d18, d2 \n"
"vmull.s16 q6, d15, d0 \n"
"vmlal.s16 q6, d17, d1 \n"
"vmlal.s16 q6, d19, d2 \n"
"vmlal.s16 q12, d14, d6 \n"
"vmlal.s16 q12, d16, d7 \n"
"vmlal.s16 q12, d18, d8 \n"
"vmlal.s16 q13, d15, d6 \n"
"vmlal.s16 q13, d17, d7 \n"
"vmlal.s16 q13, d19, d8 \n"
"vmlal.s16 q14, d14, d3 \n"
"vmlal.s16 q14, d16, d4 \n"
"vmlal.s16 q14, d18, d5 \n"
"vld1.32 {d9}, [%[input_ptr4]], r0 \n"
"vmlal.s16 q15, d15, d3 \n"
"vmlal.s16 q15, d17, d4 \n"
"vmlal.s16 q15, d19, d5 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmlal.s16 q5, d14, d3 \n"
"vmlal.s16 q5, d16, d4 \n"
"vmlal.s16 q5, d18, d5 \n"
"vmull.s16 q6, d15, d3 \n"
"vmlal.s16 q6, d17, d4 \n"
"vmlal.s16 q6, d19, d5 \n"
"vmull.s16 q14, d14, d6 \n"
"vmlal.s16 q14, d16, d7 \n"
"vmlal.s16 q14, d18, d8 \n"
"vld1.32 {d9}, [%[input_ptr5]], r0 \n"
"vmull.s16 q15, d15, d6 \n"
"vmlal.s16 q15, d17, d7 \n"
"vmlal.s16 q15, d19, d8 \n"
"vext.s8 d12, d9, #1 \n"
"vext.s8 d13, d9, #2 \n"
"vmovl.s8 q7, d9 \n"
"vmovl.s8 q8, d12 \n"
"vmovl.s8 q9, d13 \n"
"vmull.s16 q5, d14, d6 \n"
"vmlal.s16 q5, d16, d7 \n"
"vmlal.s16 q5, d18, d8 \n"
"vmull.s16 q6, d15, d6 \n"
"vmlal.s16 q6, d17, d7 \n"
"vmlal.s16 q6, d19, d8 \n"
"cmp %[remain], #4 \n"
"blt store_4h2w_%= \n"
"vst1.32 {q10}, [%[output_ptr0]]! \n"
"vst1.32 {q12}, [%[output_ptr1]]! \n"
"vst1.32 {q14}, [%[output_ptr2]]! \n"
"vst1.32 {q5}, [%[output_ptr3]]! \n"
"cmp %[remain], #5 \n"
"blt end_%= \n"
"vst1.32 {d22[0]}, [%[output_ptr0]]! \n"
"vst1.32 {d26[0]}, [%[output_ptr1]]! \n"
"vst1.32 {d30[0]}, [%[output_ptr2]]! \n"
"vst1.32 {d12[0]}, [%[output_ptr3]]! \n"
"b end_%= \n"
"store_4h2w_%=: \n"
"cmp %[remain], #2 \n"
"blt store_4h1w_%= \n"
"vst1.32 {d20}, [%[output_ptr0]]! \n"
"vst1.32 {d24}, [%[output_ptr1]]! \n"
"vst1.32 {d28}, [%[output_ptr2]]! \n"
"vst1.32 {d10}, [%[output_ptr3]]! \n"
"cmp %[remain], #3 \n"
"blt end_%= \n"
"vst1.32 {d21[0]}, [%[output_ptr0]]! \n"
"vst1.32 {d25[0]}, [%[output_ptr1]]! \n"
"vst1.32 {d27[0]}, [%[output_ptr2]]! \n"
"vst1.32 {d11[0]}, [%[output_ptr3]]! \n"
"b end_%= \n"
"store_4h1w_%=: \n"
"cmp %[remain], #1 \n"
"blt end_%= \n"
"vst1.32 {d20[0]}, [%[output_ptr0]]! \n"
"vst1.32 {d24[0]}, [%[output_ptr1]]! \n"
"vst1.32 {d28[0]}, [%[output_ptr2]]! \n"
"vst1.32 {d10[0]}, [%[output_ptr3]]! \n"
"end_%=: \n"
: [output_ptr0] "+r"(output_ptr0), [output_ptr1] "+r"(output_ptr1),
[output_ptr2] "+r"(output_ptr2), [output_ptr3] "+r"(output_ptr3),
[input_ptr0] "+r"(input_ptr0), [input_ptr1] "+r"(input_ptr1),
[input_ptr2] "+r"(input_ptr2), [input_ptr3] "+r"(input_ptr3),
[input_ptr4] "+r"(input_ptr4), [input_ptr5] "+r"(input_ptr5)
: [loop] "r"(loop), [remain] "r"(remain)
: "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
"q9", "q10", "q11", "q12", "q13", "q14", "q15", "r0");
}
// remain height
int start_h = (input_h - 2) & 0xFFFC;
for (int h = start_h; h < input_h; ++h) {
// TODO(hjchen2)
}
}
#endif // __aarch64__
}
} // namespace math
} // namespace operators
} // namespace paddle_mobile
src/operators/math/depthwise_conv3x3_int8.h 0 → 100644
浏览文件 @ d6d3def7
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
#pragma once
#include <vector>
#include "framework/tensor.h"
namespace paddle_mobile {
namespace operators {
namespace math {
void DepthwiseConv3x3_int8(const framework::Tensor *input,
const framework::Tensor *filter,
const std::vector<int> &strides,
framework::Tensor *output);
void DepthwiseConv3x3s1_int8(const framework::Tensor *input,
const framework::Tensor *filter,
framework::Tensor *output);
void DepthwiseConv3x3s2_int8(const framework::Tensor *input,
const framework::Tensor *filter,
framework::Tensor *output);
} // namespace math
} // namespace operators
} // namespace paddle_mobile
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