提交 be055633 编写于 作者: H hjchen2

Fix undefined symbol for ios arm v8

上级 6ce11736
...@@ -19,10 +19,12 @@ limitations under the License. */ ...@@ -19,10 +19,12 @@ limitations under the License. */
#if defined(__ARM_NEON__) || defined(__ARM_NEON) #if defined(__ARM_NEON__) || defined(__ARM_NEON)
#include <arm_neon.h> #include <arm_neon.h>
#endif
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
#ifndef __aarch64__ #ifndef __aarch64__
inline float32_t vmaxvq_f32(float32x4_t r) { inline float32_t vmaxvq_f32(float32x4_t r) {
float32x2_t v = vmax_f32(vget_high_f32(r), vget_low_f32(r)); float32x2_t v = vmax_f32(vget_high_f32(r), vget_low_f32(r));
......
/* 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. */
#if defined(__ARM_NEON__) && defined(__aarch64__)
#include "operators/math/depthwise_conv3x3.h"
#ifdef __ARM_NEON__
#include <arm_neon.h>
#endif
namespace paddle_mobile {
namespace operators {
namespace math {
// template<>
// void DepthwiseConv3x3<int8_t, int32_t>(
// 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.");
// }
template <>
void DepthwiseConv3x3S1<int8_t, int32_t>(const framework::Tensor &input,
const framework::Tensor &filter,
const std::vector<int> &paddings,
framework::Tensor *output) {
PADDLE_MOBILE_THROW_EXCEPTION(
"Depthwise conv3x3 with stride 1 for arm v8 has not been implemented.");
}
template <>
void DepthwiseConv3x3S2<int8_t, int32_t>(const framework::Tensor &input,
const framework::Tensor &filter,
const std::vector<int> &paddings,
framework::Tensor *output) {
PADDLE_MOBILE_THROW_EXCEPTION(
"Depthwise conv3x3 with stride 2 for arm v8 has not been implemented.");
}
} // namespace math
} // namespace operators
} // namespace paddle_mobile
#endif
/* 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. */
// Inspired by https://arxiv.org/abs/1509.09308 and refered from nnpack and ncnn
// project.
#ifdef CONV_OP
#ifdef __aarch64__
#include "operators/math/pad.h"
#include "operators/math/winograd/winograd_transform.h"
namespace paddle_mobile {
namespace operators {
namespace math {
template <>
void winograd_transform_weight<8, 3>(const framework::Tensor &weight,
framework::Tensor *output) {
/*
* w0 = g0
* w1 = ((g0 + g2) + g1) * (-2.0 / 9)
* w2 = ((g0 + g2) - g1) * (-2.0 / 9)
* w3 = ((g0 + 4 * g2) + 2 * g1) * (1.0 / 90)
* w4 = ((g0 + 4 * g2) - 2 * g1) * (1.0 / 90)
* w5 = ((g2 + 4 * g0) + 2 * g1) * (1.0 / 180)
* w6 = ((g2 + 4 * g0) - 2 * g1) * (1.0 / 180)
* w7 = g2
*/
// TODO(hjchen2)
PADDLE_MOBILE_THROW_EXCEPTION(
"Winograd for arm v8 has not been implemented.");
}
template <>
void winograd_transform_input<8, 3>(const framework::Tensor &input,
framework::Tensor *output) {
/*
* x0 = (d0 - d6) + (d4 - d2) * 5.25
* x1 = (d2 + d6) - 4.25 * (d4 + d3) + (d1 + d5)
* x2 = (d2 + d6) - 4.25 * (d4 - d3) - (d1 + d5)
* x3 = (0.25 * d2 - 1.25 * d4 + d6) + (0.5 * d1 - 2.5 * d3 + 2 * d5)
* x4 = (0.25 * d2 - 1.25 * d4 + d6) - (0.5 * d1 - 2.5 * d3 + 2 * d5)
* x5 = (4 * d2 - 5 * d4 + d6) + (2 * d1 - 2.5 * d3 + 0.5 * d5)
* x6 = (4 * d2 - 5 * d4 + d6) - (2 * d1 - 2.5 * d3 + 0.5 * d5)
* x7 = (d7 - d1) + (d3 - d5) * 5.25
*/
// TODO(hjchen2)
PADDLE_MOBILE_THROW_EXCEPTION(
"Winograd for arm v8 has not been implemented.");
}
template <>
void winograd_transform_output<8, 3>(const framework::Tensor &input,
const framework::Tensor &weight,
framework::Tensor *output) {
// TODO(hjchen2)
PADDLE_MOBILE_THROW_EXCEPTION(
"Winograd for arm v8 has not been implemented.");
}
} // namespace math
} // namespace operators
} // namespace paddle_mobile
#endif // __aarch64__
#endif // CONV_OP
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