GitOrigin-RevId: 51e025973f
tags/v1.2.0
| @@ -43,6 +43,12 @@ pdef('Axis').add_fields('int32', 'axis', 0) | |||
| Doc('NCHW4_NCHW32', 'NCHW4_NCHW32 means input tensors are nchw4 layout, output tensor is nchw32 layout'), | |||
| Doc('NCHW32_NCHW4', 'NCHW32_NCHW4 means input tensors are nchw32 layout, output tensor is nchw4 layout'), | |||
| Doc('NCHW4_NCHW', 'NCHW4_NCHW means input tensors are nchw4 layout, output tensor is nchw layout'), | |||
| Doc('NHWC_NCHW', 'NHWC_NCHW means input tensors are nhwc layout, ' | |||
| 'output tensor is nchw layout'), | |||
| Doc('NHWC_NCHW4_IC_SMALL', 'NHWC_NCHW4_IC_SMALL means input tensors are nhwc(c < 4) layout, ' | |||
| 'output tensor is nchw4 layout, padding c=4'), | |||
| Doc('NCHW_NCHW4_IC_SMALL', 'NCHW_NCHW4_IC_SMALL means input tensors are nchw(c < 4) layout, ' | |||
| 'output tensor is nchw4 layout, padding c=4'), | |||
| Doc('CHWN4', 'CHWN4 is currently only used on Nvidia platform for fast implementation ' | |||
| 'of convolution using CUDA/SASS. The channels are splitted to groups of 4 channels.')) | |||
| ) | |||
| @@ -6,7 +6,8 @@ | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, | |||
| * software distributed under the License is distributed on an | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or | |||
| * implied. | |||
| */ | |||
| #include "megdnn/oprs.h" | |||
| @@ -14,20 +15,17 @@ | |||
| namespace megdnn { | |||
| void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| const TensorLayout &mat, | |||
| const TensorLayout &mat_idx, | |||
| const TensorLayout &dst) | |||
| { | |||
| void WarpPerspectiveBase::check_layout_fwd(const TensorLayout& src, | |||
| const TensorLayout& mat, | |||
| const TensorLayout& mat_idx, | |||
| const TensorLayout& dst) { | |||
| megdnn_assert_contiguous(mat); | |||
| megdnn_assert_contiguous(src); | |||
| megdnn_assert_contiguous(dst); | |||
| auto errmsg = [&]() { | |||
| return megdnn_layout_msg(src) + ", " + | |||
| megdnn_layout_msg(mat) + ", " + | |||
| megdnn_layout_msg(mat_idx) + ", " + | |||
| megdnn_layout_msg(dst) + ", " + | |||
| param_msg(); | |||
| return megdnn_layout_msg(src) + ", " + megdnn_layout_msg(mat) + ", " + | |||
| megdnn_layout_msg(mat_idx) + ", " + megdnn_layout_msg(dst) + | |||
| ", " + param_msg(); | |||
| }; | |||
| MEGDNN_MARK_USED_VAR(errmsg); | |||
| if (param().format == param::WarpPerspective::Format::NHWCD4 || | |||
| @@ -35,9 +33,17 @@ void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| megdnn_assert(src.ndim == 5_z, "%s", errmsg().c_str()); | |||
| megdnn_assert(dst.ndim == 5_z, "%s", errmsg().c_str()); | |||
| } else if (param().format == | |||
| param::WarpPerspective::Format::NHWC_NCHW4_IC_SMALL || | |||
| param().format == | |||
| param::WarpPerspective::Format::NCHW_NCHW4_IC_SMALL) { | |||
| megdnn_assert(src.ndim == 4_z, "%s", errmsg().c_str()); | |||
| megdnn_assert(dst.ndim == 5_z, "%s", errmsg().c_str()); | |||
| } else { | |||
| megdnn_assert(param().format == param::WarpPerspective::Format::NHWC || | |||
| param().format == param::WarpPerspective::Format::NCHW); | |||
| param().format == param::WarpPerspective::Format::NCHW || | |||
| param().format == | |||
| param::WarpPerspective::Format::NHWC_NCHW); | |||
| megdnn_assert(src.ndim == 4_z, "%s", errmsg().c_str()); | |||
| megdnn_assert(dst.ndim == 4_z, "%s", errmsg().c_str()); | |||
| } | |||
| @@ -45,7 +51,7 @@ void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| megdnn_assert(dst.shape[0] == mat.shape[0], "%s", errmsg().c_str()); | |||
| if (mat_idx.ndim) { | |||
| megdnn_assert(mat_idx.dtype == dtype::Int32() && mat_idx.ndim == 1, | |||
| "%s", errmsg().c_str()); | |||
| "%s", errmsg().c_str()); | |||
| megdnn_assert(mat.shape[0] == mat_idx.shape[0], "%s", errmsg().c_str()); | |||
| megdnn_assert_contiguous(mat_idx); | |||
| } else { | |||
| @@ -54,35 +60,103 @@ void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| megdnn_assert(mat.shape[1] == 3_z, "%s", errmsg().c_str()); | |||
| megdnn_assert(mat.shape[2] == 3_z, "%s", errmsg().c_str()); | |||
| if (param().format == param::WarpPerspective::Format::NCHW) { | |||
| megdnn_assert( | |||
| src.dtype.enumv() == DTypeEnum::Float32 || | |||
| MEGDNN_FLOAT16_SELECT( | |||
| (src.dtype.enumv() == DTypeEnum::Float16 || | |||
| src.dtype.enumv() == DTypeEnum::BFloat16), | |||
| false) || | |||
| src.dtype.enumv() == DTypeEnum::Int8 || | |||
| src.dtype.enumv() == DTypeEnum::Uint8 || | |||
| (src.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.dtype.enumv() == DTypeEnum::Quantized8Asymm), | |||
| "WarpPerspective NCHW input dtype should be " | |||
| "Float32/Int8/Uint8/QInt8/QUint8" MEGDNN_FLOAT16_SELECT( | |||
| "/Float16/BFloat16", "") "."); | |||
| megdnn_assert( | |||
| (src.dtype.category() == DTypeCategory::FLOAT && | |||
| (src.dtype == mat.dtype || | |||
| mat.dtype.enumv() == DTypeEnum::Float32)) || | |||
| ((src.dtype.category() == DTypeCategory::INT || | |||
| src.dtype.category() == DTypeCategory::QUANTIZED) && | |||
| mat.dtype.enumv() == DTypeEnum::Float32), | |||
| "The input to WarpPerspective is in NCHW format, in this " | |||
| "case, if the input dtype is floating point, the " | |||
| "transformation matrix should have same dtype as the " | |||
| "input, otherwise, it should be in Float32, %s given.", | |||
| mat.dtype.name()); | |||
| if (src.format == dst.format && dst.dtype == src.dtype) { | |||
| if (param().format == param::WarpPerspective::Format::NCHW) { | |||
| megdnn_assert( | |||
| src.dtype.enumv() == DTypeEnum::Float32 || | |||
| MEGDNN_FLOAT16_SELECT( | |||
| (src.dtype.enumv() == DTypeEnum::Float16 || | |||
| src.dtype.enumv() == DTypeEnum::BFloat16), | |||
| false) || | |||
| src.dtype.enumv() == DTypeEnum::Int8 || | |||
| src.dtype.enumv() == DTypeEnum::Uint8 || | |||
| (src.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.dtype.enumv() == DTypeEnum::Quantized8Asymm), | |||
| "WarpPerspective NCHW input dtype should be " | |||
| "Float32/Int8/Uint8/QInt8/QUint8" MEGDNN_FLOAT16_SELECT( | |||
| "/Float16/BFloat16", "") "."); | |||
| megdnn_assert( | |||
| (src.dtype.category() == DTypeCategory::FLOAT && | |||
| (src.dtype == mat.dtype || | |||
| mat.dtype.enumv() == DTypeEnum::Float32)) || | |||
| ((src.dtype.category() == DTypeCategory::INT || | |||
| src.dtype.category() == | |||
| DTypeCategory::QUANTIZED) && | |||
| mat.dtype.enumv() == DTypeEnum::Float32), | |||
| "The input to WarpPerspective is in NCHW format, in this " | |||
| "case, if the input dtype is floating point, the " | |||
| "transformation matrix should have same dtype as the " | |||
| "input, otherwise, it should be in Float32, %s given.", | |||
| mat.dtype.name()); | |||
| megdnn_assert(src.shape[1] == dst.shape[1], "%s", errmsg().c_str()); | |||
| megdnn_assert(dst.dtype == src.dtype); | |||
| megdnn_assert(src.shape[1] == dst.shape[1], "%s", errmsg().c_str()); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::TRANSPARENT); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| } else if (param().format == param::WarpPerspective::Format::NHWC) { | |||
| megdnn_assert(src.shape[3] == dst.shape[3], "%s", errmsg().c_str()); | |||
| } else if (param().format == param::WarpPerspective::Format::NCHW4) { | |||
| megdnn_assert(src.dtype.enumv() == DTypeEnum::QuantizedS8, | |||
| "src expected QuantizedS8, but got %s", | |||
| src.dtype.name()); | |||
| megdnn_assert(mat.dtype == dtype::Float32(), | |||
| "matrix dtype expected float, got %s", | |||
| mat.dtype.name()); | |||
| megdnn_assert(src.shape[4] == 4 && dst.shape[4] == 4); | |||
| megdnn_assert(src.shape[1] == dst.shape[1], "%s", errmsg().c_str()); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::TRANSPARENT); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| } else { | |||
| megdnn_assert(param().format == | |||
| param::WarpPerspective::Format::NHWCD4); | |||
| megdnn_assert( | |||
| src.dtype == dtype::Float32() || | |||
| MEGDNN_FLOAT16_SELECT( | |||
| (src.dtype == dtype::Float16() || | |||
| src.dtype == dtype::BFloat16()), | |||
| false) || | |||
| src.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.dtype.enumv() == DTypeEnum::Quantized8Asymm, | |||
| "WarpPerspective NHWCD4 input dtype should be " | |||
| "Float32" MEGDNN_FLOAT16_SELECT( | |||
| "/Float16/BFloat16", | |||
| "") ",QunatizedS8, Quantized8Asymm."); | |||
| megdnn_assert( | |||
| (src.dtype == mat.dtype || mat.dtype == dtype::Float32()), | |||
| "The input to WarpPerspective is in NHWCD4 format, in this " | |||
| "case, if the input dtype is floating point, the " | |||
| "transformation matrix should have same dtype as the " | |||
| "input, %s given.", | |||
| mat.dtype.name()); | |||
| //! number of channels is same | |||
| megdnn_assert(src.shape[2] == dst.shape[2], "%s", errmsg().c_str()); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::TRANSPARENT); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| } | |||
| } else if (param().format == | |||
| param::WarpPerspective::Format::NHWC_NCHW4_IC_SMALL || | |||
| param().format == | |||
| param::WarpPerspective::Format::NCHW_NCHW4_IC_SMALL) { | |||
| megdnn_assert((src.dtype.enumv() == DTypeEnum::Quantized8Asymm || | |||
| src.dtype.enumv() == DTypeEnum::Uint8), | |||
| "src expected Quantized8Asymm or Uint8, but got %s", | |||
| src.dtype.name()); | |||
| megdnn_assert(mat.dtype == dtype::Float32(), | |||
| "matrix dtype expected float, got %s", mat.dtype.name()); | |||
| megdnn_assert(dst.shape[4] == 4); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| @@ -90,16 +164,14 @@ void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| param::WarpPerspective::BorderMode::TRANSPARENT); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| } else if (param().format == param::WarpPerspective::Format::NHWC) { | |||
| megdnn_assert(src.shape[3] == dst.shape[3], "%s", errmsg().c_str()); | |||
| } else if (param().format == param::WarpPerspective::Format::NCHW4) { | |||
| megdnn_assert(dst.dtype == src.dtype); | |||
| megdnn_assert(src.dtype.enumv() == DTypeEnum::QuantizedS8, | |||
| "src expected QuantizedS8, but got %s", src.dtype.name()); | |||
| } else if (param().format == param::WarpPerspective::Format::NHWC_NCHW) { | |||
| megdnn_assert((src.dtype.enumv() == DTypeEnum::Quantized8Asymm || | |||
| src.dtype.enumv() == DTypeEnum::Uint8), | |||
| "src expected Quantized8Asymm or Uint8, but got %s", | |||
| src.dtype.name()); | |||
| megdnn_assert(mat.dtype == dtype::Float32(), | |||
| "matrix dtype expected float, got %s", mat.dtype.name()); | |||
| megdnn_assert(src.shape[4] == 4 && dst.shape[4] == 4); | |||
| megdnn_assert(src.shape[1] == dst.shape[1], "%s", errmsg().c_str()); | |||
| megdnn_assert(src.shape[3] == dst.shape[1], "%s", errmsg().c_str()); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| @@ -108,40 +180,14 @@ void WarpPerspectiveBase::check_layout_fwd(const TensorLayout &src, | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| } else { | |||
| megdnn_assert(param().format == param::WarpPerspective::Format::NHWCD4); | |||
| megdnn_assert( | |||
| src.dtype == dtype::Float32() || | |||
| MEGDNN_FLOAT16_SELECT((src.dtype == dtype::Float16() || | |||
| src.dtype == dtype::BFloat16()), | |||
| false) || | |||
| src.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.dtype.enumv() == DTypeEnum::Quantized8Asymm, | |||
| "WarpPerspective NHWCD4 input dtype should be " | |||
| "Float32" MEGDNN_FLOAT16_SELECT( | |||
| "/Float16/BFloat16", | |||
| "") ",QunatizedS8, Quantized8Asymm."); | |||
| megdnn_assert( | |||
| (src.dtype == mat.dtype || mat.dtype == dtype::Float32()), | |||
| "The input to WarpPerspective is in NHWCD4 format, in this " | |||
| "case, if the input dtype is floating point, the " | |||
| "transformation matrix should have same dtype as the " | |||
| "input, %s given.", | |||
| mat.dtype.name()); | |||
| megdnn_assert(dst.dtype == src.dtype); | |||
| //! number of channels is same | |||
| megdnn_assert(src.shape[2] == dst.shape[2], "%s", errmsg().c_str()); | |||
| megdnn_assert(param().imode == | |||
| param::WarpPerspective::InterpolationMode::LINEAR); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::TRANSPARENT); | |||
| megdnn_assert(param().bmode != | |||
| param::WarpPerspective::BorderMode::ISOLATED); | |||
| megdnn_assert(param().format == param::WarpPerspective::Format::NCHW); | |||
| megdnn_assert((src.dtype.enumv() == DTypeEnum::Quantized8Asymm || | |||
| src.dtype.enumv() == DTypeEnum::Uint8) && | |||
| dst.dtype.enumv() == DTypeEnum::Float32); | |||
| } | |||
| megdnn_assert(src.format == dst.format); | |||
| } | |||
| std::string WarpPerspectiveBase::param_msg() const | |||
| { | |||
| std::string WarpPerspectiveBase::param_msg() const { | |||
| std::string res; | |||
| res.append(megdnn_mangle("imode=")); | |||
| switch (param().imode) { | |||
| @@ -191,31 +237,25 @@ std::string WarpPerspectiveBase::param_msg() const | |||
| return res; | |||
| } | |||
| int WarpPerspectiveBase::get_real_coord(int p, int len) | |||
| { | |||
| int WarpPerspectiveBase::get_real_coord(int p, int len) { | |||
| auto bmode = param().bmode; | |||
| if( (unsigned)p < (unsigned)len ) | |||
| if ((unsigned)p < (unsigned)len) | |||
| ; | |||
| else if( bmode == BorderMode::REPLICATE ) | |||
| else if (bmode == BorderMode::REPLICATE) | |||
| p = p < 0 ? 0 : len - 1; | |||
| else if( bmode == BorderMode::REFLECT || bmode == BorderMode::REFLECT_101 ) | |||
| { | |||
| else if (bmode == BorderMode::REFLECT || bmode == BorderMode::REFLECT_101) { | |||
| int delta = (bmode == BorderMode::REFLECT_101); | |||
| if( len == 1 ) | |||
| if (len == 1) | |||
| return 0; | |||
| do | |||
| { | |||
| if( p < 0 ) | |||
| do { | |||
| if (p < 0) | |||
| p = -p - 1 + delta; | |||
| else | |||
| p = len - 1 - (p - len) - delta; | |||
| } | |||
| while( (unsigned)p >= (unsigned)len ); | |||
| } | |||
| else if( bmode == BorderMode::WRAP ) | |||
| { | |||
| if( p < 0 ) | |||
| p -= ((p-len+1)/len)*len; | |||
| } while ((unsigned)p >= (unsigned)len); | |||
| } else if (bmode == BorderMode::WRAP) { | |||
| if (p < 0) | |||
| p -= ((p - len + 1) / len) * len; | |||
| /* | |||
| if( p >= len ) | |||
| p %= len; | |||
| @@ -223,18 +263,16 @@ int WarpPerspectiveBase::get_real_coord(int p, int len) | |||
| while (p >= len) { | |||
| p -= len; | |||
| } | |||
| } | |||
| else if( bmode == BorderMode::CONSTANT ) | |||
| } else if (bmode == BorderMode::CONSTANT) | |||
| p = -1; | |||
| return p; | |||
| } | |||
| void WarpPerspectiveForward::check_exec(const TensorLayout &src, | |||
| const TensorLayout &mat, | |||
| const TensorLayout &mat_idx, | |||
| const TensorLayout &dst, | |||
| size_t workspace_in_bytes) | |||
| { | |||
| void WarpPerspectiveForward::check_exec(const TensorLayout& src, | |||
| const TensorLayout& mat, | |||
| const TensorLayout& mat_idx, | |||
| const TensorLayout& dst, | |||
| size_t workspace_in_bytes) { | |||
| check_exec_allow_nhwc_mat_idx(src, mat, mat_idx, dst, workspace_in_bytes); | |||
| } | |||
| @@ -248,7 +286,10 @@ void WarpPerspectiveForward::check_exec_allow_nhwc_mat_idx( | |||
| megdnn_assert(workspace_in_bytes >= required_workspace_in_bytes); | |||
| if (param().format != Param::Format::NHWC && | |||
| param().format != Param::Format::NCHW && | |||
| param().format != Param::Format::NCHW4) { | |||
| param().format != Param::Format::NCHW4 && | |||
| param().format != Param::Format::NHWC_NCHW && | |||
| param().format != Param::Format::NHWC_NCHW4_IC_SMALL && | |||
| param().format != Param::Format::NCHW_NCHW4_IC_SMALL) { | |||
| megdnn_assert(!mat_idx.ndim, | |||
| "mat_idx not supported for current format"); | |||
| } | |||
| @@ -263,7 +304,8 @@ void WarpPerspectiveBackwardData::check_exec(const TensorLayout& mat, | |||
| megdnn_assert(grad.dtype == dtype::Float32() MEGDNN_INC_FLOAT16( | |||
| || grad.dtype == dtype::BFloat16()), | |||
| "Backward WarpPerspective only supports Float32/BFloat16."); | |||
| auto required_workspace_in_bytes = get_workspace_in_bytes(mat, mat_idx, diff, grad); | |||
| auto required_workspace_in_bytes = | |||
| get_workspace_in_bytes(mat, mat_idx, diff, grad); | |||
| megdnn_assert(workspace_in_bytes >= required_workspace_in_bytes); | |||
| } | |||
| @@ -283,6 +325,6 @@ void WarpPerspectiveBackwardMat::check_exec(const TensorLayout& src, | |||
| megdnn_assert(workspace_in_bytes >= required_workspace_in_bytes); | |||
| } | |||
| } // namespace megdnn | |||
| } // namespace megdnn | |||
| // vim: syntax=cpp.doxygen | |||
| @@ -12,6 +12,7 @@ | |||
| #pragma once | |||
| #include <cuda_runtime_api.h> | |||
| #include "src/common/cv/enums.h" | |||
| #include "src/cuda/utils.cuh" | |||
| #include "megcore_cdefs.h" | |||
| namespace megdnn { | |||
| @@ -34,6 +35,22 @@ void forward_proxy_nchw4(const ctype* src, const float* mat, const int* mat_idx, | |||
| megcore::AsyncErrorInfo* error_info, | |||
| void* error_tracker, cudaStream_t stream); | |||
| template <typename src_dtype, typename src_ctype, typename dst_ctype> | |||
| void forward_proxy_quint8_dimshuffle_typecvt_nchw4( | |||
| bool is_nhwc, const src_ctype* src, const float* mat, | |||
| const int* mat_idx, dst_ctype* dst, int N_SRC, int N_MAT, int C, int IH, | |||
| int IW, int OH, int OW, src_ctype bval, DTypeParamImpl<src_dtype> param, | |||
| BorderMode bmode, megcore::AsyncErrorInfo* error_info, | |||
| void* error_tracker, cudaStream_t stream); | |||
| template <typename src_dtype, typename src_ctype, typename dst_ctype> | |||
| void forward_proxy_quint8_dimshuffle_typecvt_nchw( | |||
| bool is_nhwc, const src_ctype* src, const float* mat, | |||
| const int* mat_idx, dst_ctype* dst, int N_SRC, int N_MAT, int C, int IH, | |||
| int IW, int OH, int OW, src_ctype bval, DTypeParamImpl<src_dtype> param, | |||
| BorderMode bmode, megcore::AsyncErrorInfo* error_info, | |||
| void* error_tracker, cudaStream_t stream); | |||
| void backward_data_proxy(const float* mat, const int* midx, const float* diff, | |||
| float* grad, float* workspace, int N, int N_SRC, int C, | |||
| int IH, int IW, int OH, int OW, float bval, | |||
| @@ -6,7 +6,8 @@ | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, | |||
| * software distributed under the License is distributed on an | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or | |||
| * implied. | |||
| */ | |||
| #include "src/cuda/warp_perspective/opr_impl.h" | |||
| #include "src/cuda/warp_perspective/warp_perspective_cv.cuh" | |||
| @@ -166,6 +167,30 @@ void WarpPerspectiveForwardImpl::exec(_megdnn_tensor_in ssrc, | |||
| IW = src.layout.shape[3]; | |||
| OH = dst.layout.shape[2]; | |||
| OW = dst.layout.shape[3]; | |||
| } else if (param().format == Param::Format::NHWC_NCHW) { | |||
| C = src.layout.shape[3]; | |||
| IH = src.layout.shape[1]; | |||
| IW = src.layout.shape[2]; | |||
| OH = dst.layout.shape[2]; | |||
| OW = dst.layout.shape[3]; | |||
| } else if (param().format == Param::Format::NHWC_NCHW4_IC_SMALL) { | |||
| C = src.layout.shape[3]; | |||
| IH = src.layout.shape[1]; | |||
| IW = src.layout.shape[2]; | |||
| OH = dst.layout.shape[2]; | |||
| OW = dst.layout.shape[3]; | |||
| megdnn_assert( | |||
| (C == 1) || (C == 3), | |||
| "NHWC_NCHW4_IC_SMALL only support C == 1 or C == 3"); | |||
| } else if (param().format == Param::Format::NCHW_NCHW4_IC_SMALL) { | |||
| C = src.layout.shape[1]; | |||
| IH = src.layout.shape[2]; | |||
| IW = src.layout.shape[3]; | |||
| OH = dst.layout.shape[2]; | |||
| OW = dst.layout.shape[3]; | |||
| megdnn_assert( | |||
| (C == 1) || (C == 3), | |||
| "NCHW_NCHW4_IC_SMALL only support C == 1 or C == 3"); | |||
| } else { | |||
| megdnn_assert( | |||
| param().format == param::WarpPerspective::Format::NCHW, | |||
| @@ -180,55 +205,123 @@ void WarpPerspectiveForwardImpl::exec(_megdnn_tensor_in ssrc, | |||
| "unsupported interpolation mode for NCHW format"); | |||
| auto bval = param().border_val; | |||
| auto bmode = warp_perspective::get_bmode(param().bmode); | |||
| if (src.layout.dtype == dtype::Float32{}) { | |||
| warp_perspective::forward_proxy( | |||
| is_nhwc, src.ptr<dt_float32>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_float32>(), src.layout[0], mat.layout[0], C, | |||
| IH, IW, OH, OW, bval, bmode, async_error_info(handle()), | |||
| m_error_tracker, stream); | |||
| } else if (MEGDNN_FLOAT16_SELECT( | |||
| src.layout.dtype == dtype::Float16(), false)) { | |||
| if (src.layout.dtype == dst.layout.dtype) { | |||
| if (src.layout.dtype == dtype::Float32{}) { | |||
| warp_perspective::forward_proxy( | |||
| is_nhwc, src.ptr<dt_float32>(), | |||
| mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_float32>(), src.layout[0], mat.layout[0], | |||
| C, IH, IW, OH, OW, bval, bmode, | |||
| async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } else if (MEGDNN_FLOAT16_SELECT( | |||
| src.layout.dtype == dtype::Float16(), | |||
| false)) { | |||
| #ifndef MEGDNN_DISABLE_FLOAT16 | |||
| warp_perspective::forward_proxy( | |||
| is_nhwc, src.ptr<dt_float16>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_float16>(), src.layout[0], mat.layout[0], C, | |||
| IH, IW, OH, OW, static_cast<dt_float16>(bval), bmode, | |||
| async_error_info(handle()), m_error_tracker, stream); | |||
| warp_perspective::forward_proxy( | |||
| is_nhwc, src.ptr<dt_float16>(), | |||
| mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_float16>(), src.layout[0], mat.layout[0], | |||
| C, IH, IW, OH, OW, static_cast<dt_float16>(bval), | |||
| bmode, async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| #endif | |||
| } else if (src.layout.dtype == dtype::Uint8()) { | |||
| warp_perspective::forward_proxy<dt_uint8>( | |||
| is_nhwc, src.ptr<dt_uint8>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_uint8>(), src.layout[0], mat.layout[0], C, | |||
| IH, IW, OH, OW, bval, bmode, async_error_info(handle()), | |||
| m_error_tracker, stream); | |||
| } else if (src.layout.dtype == dtype::Int8()) { | |||
| megdnn_assert( | |||
| !is_nhwc, | |||
| "WarpPerspective on CUDA does not support NHWC + Int8"); | |||
| warp_perspective::forward_proxy<dt_int8>( | |||
| false, src.ptr<dt_int8>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_int8>(), src.layout[0], mat.layout[0], C, IH, | |||
| IW, OH, OW, | |||
| bval /* implicit float -> int8 conversion, should be | |||
| safe */ | |||
| , | |||
| bmode, async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } else if (src.layout.dtype.enumv() == DTypeEnum::QuantizedS8) { | |||
| megdnn_assert(param().format == Param::Format::NCHW4, | |||
| "WarpPerspective on CUDA supports NCHW4 + " | |||
| "QuantizedS8 only"); | |||
| warp_perspective::forward_proxy_nchw4<dt_int8>( | |||
| src.compatible_ptr<dt_int8>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.compatible_ptr<dt_int8>(), src.layout[0], | |||
| mat.layout[0], C, IH, IW, OH, OW, bval, bmode, | |||
| async_error_info(handle()), m_error_tracker, stream); | |||
| } else if (src.layout.dtype == dtype::Uint8()) { | |||
| warp_perspective::forward_proxy<dt_uint8>( | |||
| is_nhwc, src.ptr<dt_uint8>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_uint8>(), src.layout[0], mat.layout[0], | |||
| C, IH, IW, OH, OW, bval, bmode, | |||
| async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } else if (src.layout.dtype == dtype::Int8()) { | |||
| megdnn_assert(!is_nhwc, | |||
| "WarpPerspective on CUDA does not support " | |||
| "NHWC + Int8"); | |||
| warp_perspective::forward_proxy<dt_int8>( | |||
| false, src.ptr<dt_int8>(), mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.ptr<dt_int8>(), src.layout[0], mat.layout[0], C, | |||
| IH, IW, OH, OW, | |||
| bval /* implicit float -> int8 conversion, | |||
| should be safe */ | |||
| , | |||
| bmode, async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } else if (src.layout.dtype.enumv() == DTypeEnum::QuantizedS8) { | |||
| megdnn_assert(param().format == Param::Format::NCHW4, | |||
| "WarpPerspective on CUDA supports NCHW4 + " | |||
| "QuantizedS8 only"); | |||
| warp_perspective::forward_proxy_nchw4<dt_int8>( | |||
| src.compatible_ptr<dt_int8>(), | |||
| mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() : nullptr, | |||
| dst.compatible_ptr<dt_int8>(), src.layout[0], | |||
| mat.layout[0], C, IH, IW, OH, OW, bval, bmode, | |||
| async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } | |||
| } else if ((src.layout.dtype.enumv() == | |||
| DTypeEnum::Quantized8Asymm || | |||
| src.layout.dtype.enumv() == DTypeEnum::Uint8)) { | |||
| uint8_t zero_point = 0; | |||
| float scale = 1.f; | |||
| if (src.layout.dtype.enumv() == DTypeEnum::Quantized8Asymm) { | |||
| zero_point = | |||
| src.layout.dtype.param<dtype::Quantized8Asymm>() | |||
| .zero_point; | |||
| scale = src.layout.dtype.param<dtype::Quantized8Asymm>() | |||
| .scale; | |||
| } else if (src.layout.dtype.enumv() == DTypeEnum::Uint8 && | |||
| dst.layout.dtype.enumv() == DTypeEnum::QuantizedS8) { | |||
| zero_point = 128; | |||
| scale = 1.f; | |||
| } | |||
| DTypeParamImpl<dt_quint8> src_dtype_param(scale, zero_point); | |||
| if ((dst.layout.dtype.enumv() == DTypeEnum::QuantizedS8 && | |||
| dst.layout.dtype.param<dtype::QuantizedS8>().scale == | |||
| scale) && | |||
| ((param().format == Param::Format::NCHW_NCHW4_IC_SMALL) || | |||
| (param().format == Param::Format::NHWC_NCHW4_IC_SMALL))) { | |||
| bool is_nhwc_ic_small = | |||
| (param().format == | |||
| Param::Format::NHWC_NCHW4_IC_SMALL); | |||
| warp_perspective:: | |||
| forward_proxy_quint8_dimshuffle_typecvt_nchw4< | |||
| dt_quint8, dt_uint8, dt_int8>( | |||
| is_nhwc_ic_small, | |||
| src.compatible_ptr<dt_uint8>(), | |||
| mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() | |||
| : nullptr, | |||
| dst.compatible_ptr<dt_int8>(), | |||
| src.layout[0], mat.layout[0], C, IH, IW, OH, | |||
| OW, bval, src_dtype_param, bmode, | |||
| async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } else { | |||
| megdnn_assert( | |||
| ((dst.layout.dtype.enumv() == DTypeEnum::Float32) && | |||
| ((param().format == Param::Format::NCHW) || | |||
| (param().format == Param::Format::NHWC_NCHW))), | |||
| "invalid format for Quantized8Asymm input"); | |||
| bool is_nhwc = (param().format == Param::Format::NHWC_NCHW); | |||
| warp_perspective:: | |||
| forward_proxy_quint8_dimshuffle_typecvt_nchw< | |||
| dt_quint8, dt_uint8, dt_float32>( | |||
| is_nhwc, src.compatible_ptr<dt_uint8>(), | |||
| mat.ptr<dt_float32>(), | |||
| mat_idx.raw_ptr ? mat_idx.ptr<int>() | |||
| : nullptr, | |||
| dst.compatible_ptr<dt_float32>(), | |||
| src.layout[0], mat.layout[0], C, IH, IW, OH, | |||
| OW, bval, src_dtype_param, bmode, | |||
| async_error_info(handle()), m_error_tracker, | |||
| stream); | |||
| } | |||
| } else { | |||
| megdnn_throw(ssprintf("unsupported dtype: %s", | |||
| src.layout.dtype.name())); | |||
| @@ -249,6 +249,162 @@ void WarpPerspectiveForwardImpl::kern_naive_nhwcd4( | |||
| MIDOUT_END(); | |||
| } | |||
| template <typename ctype, typename dst_ctype, typename mtype> | |||
| void WarpPerspectiveForwardImpl::kern_naive_dimshuffle_typecvt( | |||
| const KernParam<ctype, mtype>& kern_param, size_t task_id) { | |||
| MEGDNN_MARK_USED_VAR(kern_param); | |||
| MIDOUT_BEGIN(megdnn_naive_warpperspective, ctype, mtype, midout_iv(2)) { | |||
| UNPACK_WARP_PERSPECTIVE_FWD_KERN_PARAM(kern_param); | |||
| MEGDNN_MARK_USED_VAR(N_MAT); | |||
| //! strides of C, H, W on src and dst | |||
| size_t sstrd[3], dstrd[3]; | |||
| auto set_sstrd = [&](size_t s0, size_t s1, size_t s2) { | |||
| sstrd[0] = s0; | |||
| sstrd[1] = s1; | |||
| sstrd[2] = s2; | |||
| }; | |||
| auto set_dstrd = [&](size_t s0, size_t s1, size_t s2) { | |||
| dstrd[0] = s0; | |||
| dstrd[1] = s1; | |||
| dstrd[2] = s2; | |||
| }; | |||
| switch (kern_param.format) { | |||
| case Format::NCHW: | |||
| case Format::NCHW_NCHW4_IC_SMALL: | |||
| set_sstrd(IH * IW, IW, 1); | |||
| set_dstrd(OH * OW, OW, 1); | |||
| break; | |||
| case Format::NHWC_NCHW: | |||
| case Format::NHWC_NCHW4_IC_SMALL: | |||
| set_sstrd(1, IW * C, C); | |||
| set_dstrd(OH * OW, OW, 1); | |||
| break; | |||
| default: | |||
| megdnn_throw("bad format"); | |||
| } | |||
| uint8_t zero_point = 0; | |||
| float scale = 1.f; | |||
| bool is_dst_float = kern_param.dst_dtype.enumv() == DTypeEnum::Float32; | |||
| if (kern_param.src_dtype.enumv() == | |||
| DTypeTrait<dtype::Quantized8Asymm>::enumv) { | |||
| auto dtype_param = | |||
| kern_param.src_dtype | |||
| .template param<dtype::Quantized8Asymm>(); | |||
| zero_point = dtype_param.zero_point; | |||
| scale = dtype_param.scale; | |||
| } else if (kern_param.src_dtype.enumv() == DTypeEnum::Uint8) { | |||
| zero_point = | |||
| (kern_param.dst_dtype.enumv() == DTypeEnum::QuantizedS8) | |||
| ? 128 | |||
| : 0; | |||
| scale = 1.f; | |||
| } | |||
| dst_ctype* dst_ptr = reinterpret_cast<dst_ctype*>(dptr); | |||
| bool is_dst_nchw4 = | |||
| (kern_param.format == Format::NCHW_NCHW4_IC_SMALL) || | |||
| (kern_param.format == Format::NHWC_NCHW4_IC_SMALL); | |||
| auto visit_src = [&sptr, sstrd](size_t c, int h, int w) -> float { | |||
| return sptr[sstrd[0] * c + sstrd[1] * h + sstrd[2] * w]; | |||
| }; | |||
| auto visit_src_bd = [&sptr, sstrd, border_val](size_t c, int h, | |||
| int w) -> float { | |||
| if (h != -1 && w != -1) { | |||
| return sptr[sstrd[0] * c + sstrd[1] * h + sstrd[2] * w]; | |||
| } else | |||
| return border_val; | |||
| }; | |||
| auto visit_dst = [&dst_ptr, dstrd, is_dst_nchw4](size_t c, int h, | |||
| int w) -> dst_ctype& { | |||
| if (!is_dst_nchw4) | |||
| return dst_ptr[dstrd[0] * c + dstrd[1] * h + dstrd[2] * w]; | |||
| else | |||
| return dst_ptr[((dstrd[0] * (c >> 2) + dstrd[1] * h + | |||
| dstrd[2] * w) | |||
| << 2) + | |||
| (c & 0b11)]; | |||
| }; | |||
| rounding::RoundingConverter<dst_ctype> output_converter; | |||
| auto orig_sptr = sptr; | |||
| size_t n = task_id / OH; | |||
| size_t oh = task_id % OH; | |||
| mptr = mptr + n * 3 * 3; | |||
| dst_ptr = is_dst_nchw4 ? (dst_ptr + n * OH * OW * 4) | |||
| : (dst_ptr + n * C * OH * OW); | |||
| if (midx_ptr) { | |||
| size_t idx = midx_ptr[n]; | |||
| megdnn_assert( | |||
| idx < N_SRC, | |||
| "mat_idx out of bound: mat_idx[%zu]=%zu src_batch=%zu", n, | |||
| idx, N_SRC); | |||
| sptr = orig_sptr + idx * (C * IH * IW); | |||
| } else if (n) { | |||
| sptr += n * C * IH * IW; | |||
| } | |||
| rep(ow, OW) { | |||
| float numeratorw = mptr[0] * ow + mptr[1] * oh + mptr[2]; | |||
| float numeratorh = mptr[3] * ow + mptr[4] * oh + mptr[5]; | |||
| float denominator = mptr[6] * ow + mptr[7] * oh + mptr[8]; | |||
| float alphaw = numeratorw / denominator; | |||
| float alphah = numeratorh / denominator; | |||
| int iw0 = get_real_coord(std::floor(alphaw) + 0, IW); | |||
| int iw1 = get_real_coord(std::floor(alphaw) + 1, IW); | |||
| int ih0 = get_real_coord(std::floor(alphah) + 0, IH); | |||
| int ih1 = get_real_coord(std::floor(alphah) + 1, IH); | |||
| alphaw -= floor(alphaw); | |||
| alphah -= floor(alphah); | |||
| if (bmode != BorderMode::CONSTANT) { | |||
| rep(c, C) { | |||
| auto val = | |||
| visit_src(c, ih0, iw0) * (1.0f - alphaw) * | |||
| (1.0f - alphah) + | |||
| visit_src(c, ih0, iw1) * alphaw * (1.0f - alphah) + | |||
| visit_src(c, ih1, iw0) * (1.0f - alphaw) * alphah + | |||
| visit_src(c, ih1, iw1) * alphaw * alphah; | |||
| val = is_dst_float ? (val - zero_point) * scale | |||
| : val - zero_point; | |||
| visit_dst(c, oh, ow) = output_converter(val); | |||
| } | |||
| } else { | |||
| rep(c, C) { | |||
| auto val = visit_src_bd(c, ih0, iw0) * (1.0f - alphaw) * | |||
| (1.0f - alphah) + | |||
| visit_src_bd(c, ih0, iw1) * alphaw * | |||
| (1.0f - alphah) + | |||
| visit_src_bd(c, ih1, iw0) * (1.0f - alphaw) * | |||
| alphah + | |||
| visit_src_bd(c, ih1, iw1) * alphaw * alphah; | |||
| val = std::isfinite(val) ? val : border_val; | |||
| val = is_dst_float ? (val - zero_point) * scale | |||
| : val - zero_point; | |||
| visit_dst(c, oh, ow) = output_converter(val); | |||
| } | |||
| } | |||
| if (is_dst_nchw4) { | |||
| for (auto c = C; c < 4; ++c) { | |||
| visit_dst(c, oh, ow) = 0; | |||
| } | |||
| } | |||
| } | |||
| } | |||
| MIDOUT_END(); | |||
| } | |||
| #define INST(ctype, drc_ctype, mtype) \ | |||
| template void WarpPerspectiveForwardImpl::kern_naive_dimshuffle_typecvt< \ | |||
| ctype, drc_ctype, mtype>(const KernParam<ctype, mtype>&, size_t); | |||
| INST(uint8_t, int8_t, float); | |||
| INST(uint8_t, float, float); | |||
| #undef INST | |||
| void WarpPerspectiveForwardImpl::exec(_megdnn_tensor_in src, | |||
| _megdnn_tensor_in mat, | |||
| _megdnn_tensor_in mat_idx, | |||
| @@ -320,6 +476,65 @@ void WarpPerspectiveForwardImpl::exec(_megdnn_tensor_in src, | |||
| src.layout.dtype.name()) | |||
| .c_str()); | |||
| } | |||
| bool is_fusion_dtype = src.layout.dtype.enumv() != dst.layout.dtype.enumv(); | |||
| bool is_u8_or_qu8_in = | |||
| src.layout.dtype.enumv() == DTypeTrait<dtype::Uint8>::enumv || | |||
| src.layout.dtype.enumv() == | |||
| DTypeTrait<dtype::Quantized8Asymm>::enumv; | |||
| if (is_fusion_dtype && is_u8_or_qu8_in && | |||
| ((param().format == Format::NCHW_NCHW4_IC_SMALL) || | |||
| (param().format == Format::NHWC_NCHW4_IC_SMALL) || | |||
| (param().format == Format::NHWC_NCHW) || | |||
| (param().format == Format::NCHW))) { | |||
| if (src.layout.dtype.enumv() == | |||
| DTypeTrait<dtype::Quantized8Asymm>::enumv || | |||
| src.layout.dtype.enumv() == DTypeTrait<dtype::Uint8>::enumv) { | |||
| float scale = 1.f; | |||
| if (src.layout.dtype.enumv() == | |||
| DTypeTrait<dtype::Quantized8Asymm>::enumv) { | |||
| scale = src.layout.dtype.param<dtype::Quantized8Asymm>().scale; | |||
| } | |||
| auto kparam = KernParam<uint8_t, float>::from_tensors( | |||
| param().format, param().bmode, param().border_val, src, mat, | |||
| mat_idx, dst, workspace); | |||
| if (dst.layout.dtype.enumv() == DTypeTrait<dtype::Float32>::enumv) { | |||
| auto run = [kparam, this](size_t index, size_t) { | |||
| kern_naive_dimshuffle_typecvt<uint8_t, float, float>(kparam, | |||
| index); | |||
| }; | |||
| MEGDNN_DISPATCH_MULTI_THREAD_CPU_KERN_OPR(run, | |||
| kparam.oh * batch); | |||
| return; | |||
| } else if ((dst.layout.dtype.enumv() == | |||
| DTypeTrait<dtype::QuantizedS8>::enumv) && | |||
| (dst.layout.dtype.param<dtype::QuantizedS8>().scale == | |||
| scale)) { | |||
| auto run = [kparam, this](size_t index, size_t) { | |||
| kern_naive_dimshuffle_typecvt<uint8_t, int8_t, float>( | |||
| kparam, index); | |||
| }; | |||
| MEGDNN_DISPATCH_MULTI_THREAD_CPU_KERN_OPR(run, | |||
| kparam.oh * batch); | |||
| return; | |||
| } else { | |||
| megdnn_throw(ssprintf("Unsupported DType in " | |||
| "WarpPerspective Dimshuffle Typecvt: %s", | |||
| src.layout.dtype.name()) | |||
| .c_str()); | |||
| } | |||
| } | |||
| megdnn_throw(ssprintf("Unsupported input DType in " | |||
| "WarpPerspective: %s", | |||
| src.layout.dtype.name()) | |||
| .c_str()); | |||
| } | |||
| if (warp::is_cv_available(src.layout, mat.layout, dst.layout, param().imode, | |||
| param().format)) { | |||
| MIDOUT_BEGIN(megdnn_naive_warpperspective, void) { | |||
| @@ -331,12 +546,12 @@ void WarpPerspectiveForwardImpl::exec(_megdnn_tensor_in src, | |||
| megdnn_assert(warp::is_dnn_available(src.layout, mat.layout, dst.layout, | |||
| param().imode, param().format)); | |||
| /*! | |||
| * We currently use floating point for all WarpPerspective computation, | |||
| * so even if the input ctype is one of the integer type, mtype should | |||
| * always be float32. | |||
| * We currently use floating point for all WarpPerspective | |||
| * computation, so even if the input ctype is one of the integer | |||
| * type, mtype should always be float32. | |||
| * | |||
| * \warning It's different with \c WarpAffine, with mtype be float16 if | |||
| * input type is float16. | |||
| * \warning It's different with \c WarpAffine, with mtype be float16 | |||
| * if input type is float16. | |||
| */ | |||
| DISPATCH_ST(dtype::Float32, float, float, KERN); | |||
| @@ -26,6 +26,7 @@ protected: | |||
| float border_val; | |||
| size_t n_src, n_mat, c, ih, iw, oh, ow; | |||
| ctype *sptr, *dptr; | |||
| DType src_dtype, dst_dtype; | |||
| mtype* mptr; | |||
| int* midx_ptr; //!< can be null | |||
| Workspace workspace; | |||
| @@ -41,6 +42,8 @@ protected: | |||
| ret.bmode = bmode; | |||
| ret.border_val = border_val; | |||
| ret.n_src = src.layout.shape[0]; | |||
| ret.src_dtype = src.layout.dtype; | |||
| ret.dst_dtype = dst.layout.dtype; | |||
| if (mat_idx.raw_ptr) { | |||
| megdnn_assert(mat_idx.layout.ndim == 1); | |||
| ret.n_mat = mat_idx.layout.shape[0]; | |||
| @@ -50,7 +53,8 @@ protected: | |||
| ret.n_mat = ret.n_src; | |||
| ret.midx_ptr = nullptr; | |||
| } | |||
| if (format == Format::NCHW) { | |||
| if (format == Format::NCHW || | |||
| format == Format::NCHW_NCHW4_IC_SMALL) { | |||
| ret.c = src.layout.shape[1]; | |||
| ret.ih = src.layout.shape[2]; | |||
| ret.iw = src.layout.shape[3]; | |||
| @@ -62,6 +66,13 @@ protected: | |||
| ret.iw = src.layout.shape[2]; | |||
| ret.oh = dst.layout.shape[1]; | |||
| ret.ow = dst.layout.shape[2]; | |||
| } else if (format == Format::NHWC_NCHW || | |||
| format == Format::NHWC_NCHW4_IC_SMALL) { | |||
| ret.c = src.layout.shape[3]; | |||
| ret.ih = src.layout.shape[1]; | |||
| ret.iw = src.layout.shape[2]; | |||
| ret.oh = dst.layout.shape[2]; | |||
| ret.ow = dst.layout.shape[3]; | |||
| } else if (format == Format::NCHW4) { | |||
| ret.c = src.layout.shape[1] * 4; | |||
| ret.ih = src.layout.shape[2]; | |||
| @@ -76,15 +87,16 @@ protected: | |||
| ret.oh = dst.layout.shape[1]; | |||
| ret.ow = dst.layout.shape[3]; | |||
| } | |||
| if (src.layout.dtype.enumv() == DTypeEnum::Float32 || | |||
| MEGDNN_FLOAT16_SELECT( | |||
| (src.layout.dtype.enumv() == DTypeEnum::Float16 || | |||
| src.layout.dtype.enumv() == DTypeEnum::BFloat16), | |||
| false) || | |||
| src.layout.dtype.enumv() == DTypeEnum::Int8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::Uint8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::Quantized8Asymm) { | |||
| if ((src.layout.dtype.enumv() == DTypeEnum::Float32 || | |||
| MEGDNN_FLOAT16_SELECT( | |||
| (src.layout.dtype.enumv() == DTypeEnum::Float16 || | |||
| src.layout.dtype.enumv() == DTypeEnum::BFloat16), | |||
| false) || | |||
| src.layout.dtype.enumv() == DTypeEnum::Int8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::Uint8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::QuantizedS8 || | |||
| src.layout.dtype.enumv() == DTypeEnum::Quantized8Asymm) && | |||
| (src.layout.dtype == dst.layout.dtype)) { | |||
| ret.sptr = src.compatible_ptr<ctype>(); | |||
| ret.mptr = mat.ptr<mtype>(); | |||
| ret.dptr = dst.compatible_ptr<ctype>(); | |||
| @@ -92,6 +104,13 @@ protected: | |||
| ret.sptr = src.compatible_ptr<ctype>(); | |||
| ret.mptr = mat.ptr<mtype>(); | |||
| ret.dptr = dst.compatible_ptr<ctype>(); | |||
| } else if ((src.layout.dtype.enumv() == DTypeEnum::Uint8 || | |||
| src.layout.dtype.enumv() == | |||
| DTypeEnum::Quantized8Asymm) && | |||
| src.layout.dtype.enumv() != dst.layout.dtype.enumv()) { | |||
| ret.sptr = src.compatible_ptr<ctype>(); | |||
| ret.mptr = mat.ptr<mtype>(); | |||
| ret.dptr = reinterpret_cast<ctype*>(dst.raw_ptr); | |||
| } else { | |||
| ret.sptr = nullptr; | |||
| ret.mptr = nullptr; | |||
| @@ -122,6 +141,9 @@ private: | |||
| template <typename ctype, typename mtype> | |||
| void kern_naive_nhwcd4(const KernParam<ctype, mtype>& kern_param, | |||
| size_t task_id); | |||
| template <typename ctype, typename dst_ctype, typename mtype> | |||
| void kern_naive_dimshuffle_typecvt( | |||
| const KernParam<ctype, mtype>& kern_param, size_t task_id); | |||
| }; | |||
| class WarpPerspectiveBackwardDataImpl : public WarpPerspectiveBackwardData { | |||
| @@ -23,8 +23,7 @@ using namespace megdnn; | |||
| using namespace test; | |||
| class NanMatRNG : public RNG { | |||
| void gen(const TensorND& tensor_) override | |||
| { | |||
| void gen(const TensorND& tensor_) override { | |||
| auto& gen = RandomState::generator(); | |||
| std::uniform_real_distribution<dt_float32> pdist3(1.9f, 2.1f); | |||
| std::uniform_real_distribution<dt_float32> pdist(0.9f, 1.1f); | |||
| @@ -335,6 +334,144 @@ TEST_F(CUDA, WARP_PERSPECTIVE_NCHW4) { | |||
| } | |||
| } | |||
| TEST_F(CUDA, WARP_PERSPECTIVE_NCHW_NCHW4_IC_SMALL) { | |||
| using Param = WarpPerspective::Param; | |||
| WarpPerspective::Param param; | |||
| Checker<WarpPerspectiveForward> checker(handle_cuda()); | |||
| WarpPerspectiveMatRNG rng; | |||
| param.format = Param::Format::NCHW_NCHW4_IC_SMALL; | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(0, dtype::Quantized8Asymm(0.1f, 128)); | |||
| checker.set_dtype(2, dtype::QuantizedS8(0.1f)); | |||
| for (auto bmode : {WarpPerspective::BorderMode::WRAP, | |||
| WarpPerspective::BorderMode::REFLECT, | |||
| WarpPerspective::BorderMode::REPLICATE, | |||
| WarpPerspective::BorderMode::CONSTANT}) { | |||
| param.border_val = 0.3f; | |||
| param.bmode = bmode; | |||
| param.imode = Param::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{2, 3, 10, 11}, {2, 3, 3}, {2, 1, 11, 12, 4}}); | |||
| checker.execs({{1, 3, 25, 510}, {1, 3, 3}, {1, 1, 25, 25, 4}}); | |||
| checker.execs({{1, 3, 25, 25}, {1, 3, 3}, {1, 1, 51, 51, 4}}); | |||
| checker.execs({{1, 3, 51, 51}, {1, 3, 3}, {1, 1, 25, 25, 4}}); | |||
| } | |||
| { | |||
| Checker<WarpPerspective, WarpPerspectiveMatIdxProxy> checker( | |||
| handle_cuda()); | |||
| constexpr int N_SRC = 5; | |||
| UniformIntRNG mat_idx_rng{0, N_SRC - 1}; | |||
| checker.set_dtype(0, dtype::Quantized8Asymm(0.1f, 128)); | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(2, dtype::Int32()); | |||
| checker.set_rng(2, &mat_idx_rng); | |||
| checker.set_dtype(3, dtype::QuantizedS8(0.1f)); | |||
| param.bmode = WarpPerspective::Param::BorderMode::REFLECT; | |||
| param.imode = param::WarpPerspective::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{N_SRC, 3, 10, 11}, {2, 3, 3}, {2}, {2, 1, 11, 12, 4}}); | |||
| checker.execs( | |||
| {{N_SRC, 3, 17, 13}, {123, 3, 3}, {123}, {123, 1, 16, 15, 4}}); | |||
| } | |||
| } | |||
| TEST_F(CUDA, WARP_PERSPECTIVE_NHWC_NCHW4_IC_SMALL) { | |||
| using Param = WarpPerspective::Param; | |||
| WarpPerspective::Param param; | |||
| Checker<WarpPerspectiveForward> checker(handle_cuda()); | |||
| WarpPerspectiveMatRNG rng; | |||
| param.format = Param::Format::NHWC_NCHW4_IC_SMALL; | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(0, dtype::Uint8()); | |||
| checker.set_dtype(2, dtype::QuantizedS8(1.f)); | |||
| for (auto bmode : {WarpPerspective::BorderMode::WRAP, | |||
| WarpPerspective::BorderMode::REFLECT, | |||
| WarpPerspective::BorderMode::REPLICATE, | |||
| WarpPerspective::BorderMode::CONSTANT}) { | |||
| param.border_val = 0.3f; | |||
| param.bmode = bmode; | |||
| param.imode = Param::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{2, 10, 11, 3}, {2, 3, 3}, {2, 1, 11, 12, 4}}); | |||
| checker.execs({{1, 25, 510, 3}, {1, 3, 3}, {1, 1, 25, 25, 4}}); | |||
| checker.execs({{1, 25, 25, 3}, {1, 3, 3}, {1, 1, 51, 51, 4}}); | |||
| checker.execs({{1, 51, 51, 3}, {1, 3, 3}, {1, 1, 25, 25, 4}}); | |||
| } | |||
| { | |||
| Checker<WarpPerspective, WarpPerspectiveMatIdxProxy> checker( | |||
| handle_cuda()); | |||
| constexpr int N_SRC = 5; | |||
| UniformIntRNG mat_idx_rng{0, N_SRC - 1}; | |||
| checker.set_dtype(0, dtype::Uint8()); | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(2, dtype::Int32()); | |||
| checker.set_rng(2, &mat_idx_rng); | |||
| checker.set_dtype(3, dtype::QuantizedS8(1.f)); | |||
| param.bmode = WarpPerspective::Param::BorderMode::REFLECT; | |||
| param.imode = param::WarpPerspective::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{N_SRC, 10, 11, 3}, {2, 3, 3}, {2}, {2, 1, 11, 12, 4}}); | |||
| checker.execs( | |||
| {{N_SRC, 17, 13, 3}, {123, 3, 3}, {123}, {123, 1, 16, 15, 4}}); | |||
| } | |||
| } | |||
| TEST_F(CUDA, WARP_PERSPECTIVE_NHWC_NCHW) { | |||
| using Param = WarpPerspective::Param; | |||
| WarpPerspective::Param param; | |||
| Checker<WarpPerspectiveForward> checker(handle_cuda()); | |||
| WarpPerspectiveMatRNG rng; | |||
| param.format = Param::Format::NHWC_NCHW; | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(0, dtype::Uint8()); | |||
| checker.set_dtype(2, dtype::Float32()); | |||
| for (auto bmode : {WarpPerspective::BorderMode::WRAP, | |||
| WarpPerspective::BorderMode::REFLECT, | |||
| WarpPerspective::BorderMode::REPLICATE, | |||
| WarpPerspective::BorderMode::CONSTANT}) { | |||
| param.border_val = 0.3f; | |||
| param.bmode = bmode; | |||
| param.imode = Param::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{2, 10, 11, 3}, {2, 3, 3}, {2, 3, 11, 12}}); | |||
| checker.execs({{1, 25, 510, 3}, {1, 3, 3}, {1, 3, 25, 25}}); | |||
| checker.execs({{1, 25, 25, 3}, {1, 3, 3}, {1, 3, 51, 51}}); | |||
| checker.execs({{1, 51, 51, 3}, {1, 3, 3}, {1, 3, 25, 25}}); | |||
| } | |||
| { | |||
| Checker<WarpPerspective, WarpPerspectiveMatIdxProxy> checker( | |||
| handle_cuda()); | |||
| constexpr int N_SRC = 5; | |||
| UniformIntRNG mat_idx_rng{0, N_SRC - 1}; | |||
| checker.set_dtype(0, dtype::Uint8()); | |||
| checker.set_rng(1, &rng); | |||
| checker.set_dtype(2, dtype::Int32()); | |||
| checker.set_rng(2, &mat_idx_rng); | |||
| checker.set_dtype(3, dtype::Float32()); | |||
| param.bmode = WarpPerspective::Param::BorderMode::REFLECT; | |||
| param.imode = param::WarpPerspective::InterpolationMode::LINEAR; | |||
| checker.set_param(param); | |||
| checker.set_epsilon(1 + 1e-3); | |||
| checker.execs({{N_SRC, 10, 11, 3}, {2, 3, 3}, {2}, {2, 3, 11, 12}}); | |||
| checker.execs( | |||
| {{N_SRC, 17, 13, 3}, {123, 3, 3}, {123}, {123, 3, 16, 15}}); | |||
| } | |||
| } | |||
| TEST_F(CUDA, WARP_PERSPECTIVE_FORWARD_NCHW_INT8) { | |||
| warp_perspective::run_int8_test(handle_cuda()); | |||
| } | |||
| @@ -6,7 +6,8 @@ | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, | |||
| * software distributed under the License is distributed on an | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or | |||
| * implied. | |||
| */ | |||
| #include "megbrain/gopt/framework.h" | |||
| @@ -35,13 +36,13 @@ using namespace gopt; | |||
| /* ================ SubGraph ================ */ | |||
| OperatorNodeBase* SubGraph::Rewriter::auto_replace_outputs( | |||
| OperatorNodeBase *opr) { | |||
| auto &&new_inp = m_opr_new_inp_cache; | |||
| OperatorNodeBase* opr) { | |||
| auto&& new_inp = m_opr_new_inp_cache; | |||
| new_inp.clear(); | |||
| new_inp.reserve(opr->input().size()); | |||
| bool has_replaced_inp = false; | |||
| for (auto i: opr->input()) { | |||
| for (auto i : opr->input()) { | |||
| auto new_var = get_var(i); | |||
| if (new_var != i) { | |||
| has_replaced_inp = true; | |||
| @@ -52,14 +53,14 @@ OperatorNodeBase* SubGraph::Rewriter::auto_replace_outputs( | |||
| } | |||
| if (has_replaced_inp) { | |||
| auto new_opr = serialization::copy_opr_shallow( | |||
| *opr, new_inp, opr->config()); | |||
| auto new_opr = | |||
| serialization::copy_opr_shallow(*opr, new_inp, opr->config()); | |||
| auto &&out0 = opr->output(), &&out1 = new_opr->output(); | |||
| size_t i = 0; | |||
| auto err_msg = [opr, new_opr] { | |||
| return ssprintf("bad opr copy: src=%s{%s} dst=%s{%s}", | |||
| opr->cname(), opr->dyn_typeinfo()->name, | |||
| new_opr->cname(), new_opr->dyn_typeinfo()->name); | |||
| return ssprintf("bad opr copy: src=%s{%s} dst=%s{%s}", opr->cname(), | |||
| opr->dyn_typeinfo()->name, new_opr->cname(), | |||
| new_opr->dyn_typeinfo()->name); | |||
| }; | |||
| MGB_MARK_USED_VAR(err_msg); | |||
| // opr output size mismatch may be caused by: | |||
| @@ -67,33 +68,33 @@ OperatorNodeBase* SubGraph::Rewriter::auto_replace_outputs( | |||
| // 1) other post-insert optimization (e.g. const folding) | |||
| // we can't handle only usable_output here, since some output var with | |||
| // volatile flag could be the graph's endpoint (e.g. RemoteSend) | |||
| for (; i < std::min(out0.size(), out1.size()); ++ i) { | |||
| for (; i < std::min(out0.size(), out1.size()); ++i) { | |||
| bool v0 = out0[i]->contain_flag(VarNode::Flag::VOLATILE_CONTENT), | |||
| v1 = out1[i]->contain_flag(VarNode::Flag::VOLATILE_CONTENT); | |||
| mgb_assert(v0 == v1, "%s", err_msg().c_str()); | |||
| auto &&ins = m_varmap.insert({out0[i], {true, nullptr}}); | |||
| auto&& ins = m_varmap.insert({out0[i], {true, nullptr}}); | |||
| mgb_assert(ins.second || ins.first->second.first, | |||
| "opr output already replaced"); | |||
| // handle repeated call on the same opr | |||
| ins.first->second.second = out1[i]; | |||
| on_var_replaced(out0[i], out1[i], nullptr); | |||
| } | |||
| for (; i < out0.size(); ++ i) { | |||
| for (; i < out0.size(); ++i) { | |||
| mgb_assert(out0[i]->contain_flag(VarNode::Flag::VOLATILE_CONTENT), | |||
| "%s", err_msg().c_str()); | |||
| "%s", err_msg().c_str()); | |||
| } | |||
| for (; i < out1.size(); ++ i) { | |||
| for (; i < out1.size(); ++i) { | |||
| mgb_assert(out1[i]->contain_flag(VarNode::Flag::VOLATILE_CONTENT), | |||
| "%s", err_msg().c_str()); | |||
| "%s", err_msg().c_str()); | |||
| } | |||
| return new_opr; | |||
| } | |||
| return opr; | |||
| } | |||
| void SubGraph::Rewriter::replace_var( | |||
| VarNode *src, VarNode *dst, const char *msg) { | |||
| void SubGraph::Rewriter::replace_var(VarNode* src, VarNode* dst, | |||
| const char* msg) { | |||
| if (src == dst) | |||
| return; | |||
| @@ -103,19 +104,19 @@ void SubGraph::Rewriter::replace_var( | |||
| "dst %s maps back to src %s in SubGraph::Rewriter::replace_var", | |||
| dst->cname(), src->cname()); | |||
| auto &&ins = m_varmap.insert({src, {false, dst}}); | |||
| auto&& ins = m_varmap.insert({src, {false, dst}}); | |||
| if (!ins.second) { | |||
| auto &&old_rep = ins.first->second; | |||
| auto&& old_rep = ins.first->second; | |||
| mgb_assert(old_rep.first || old_rep.second == dst, | |||
| "can not replace a var twice"); | |||
| "can not replace a var twice"); | |||
| old_rep.first = false; | |||
| old_rep.second = dst; | |||
| } | |||
| on_var_replaced(src, dst, msg); | |||
| } | |||
| void SubGraph::Rewriter::on_var_replaced( | |||
| VarNode* src, VarNode* dst, const char* msg) { | |||
| void SubGraph::Rewriter::on_var_replaced(VarNode* src, VarNode* dst, | |||
| const char* msg) { | |||
| if (auto state = m_owner_graph->owner_opt_state()) { | |||
| state->on_var_replaced(src, dst, msg); | |||
| } | |||
| @@ -124,7 +125,7 @@ void SubGraph::Rewriter::on_var_replaced( | |||
| void SubGraph::Rewriter::apply_inplace() const { | |||
| m_owner_graph->m_endpoint_oprs.clear(); | |||
| m_owner_graph->m_endpoint_vars_set.clear(); | |||
| for (auto &&var: m_owner_graph->m_endpoint_vars) { | |||
| for (auto&& var : m_owner_graph->m_endpoint_vars) { | |||
| var = get_var(var.node()); | |||
| m_owner_graph->m_endpoint_oprs.insert(var.node()->owner_opr()); | |||
| m_owner_graph->m_endpoint_vars_set.insert(var.node()); | |||
| @@ -150,33 +151,30 @@ std::pair<bool, VarNode*> SubGraph::Rewriter::get_var_internal(VarNode* var) { | |||
| return it->second = {it_next->second.first & it->second.first, next.second}; | |||
| } | |||
| SubGraph::SubGraph(const SymbolVarArray &endpoint_vars): | |||
| m_endpoint_vars(endpoint_vars) | |||
| { | |||
| SubGraph::SubGraph(const SymbolVarArray& endpoint_vars) | |||
| : m_endpoint_vars(endpoint_vars) { | |||
| mgb_assert(!endpoint_vars.empty(), "endpoints can not be empty"); | |||
| m_comp_graph = endpoint_vars[0].node()->owner_graph(); | |||
| for (auto i: endpoint_vars) { | |||
| for (auto i : endpoint_vars) { | |||
| m_endpoint_oprs.insert(i.node()->owner_opr()); | |||
| m_endpoint_vars_set.insert(i.node()); | |||
| mgb_assert(m_comp_graph == i.node()->owner_graph(), | |||
| "endpoints belong to different computing graphs"); | |||
| "endpoints belong to different computing graphs"); | |||
| } | |||
| } | |||
| void SubGraph::iter( | |||
| const Callback& cb, | |||
| std::shared_ptr<ExtraDep> extra_dep) const { | |||
| void SubGraph::iter(const Callback& cb, | |||
| std::shared_ptr<ExtraDep> extra_dep) const { | |||
| Callback on_opr; | |||
| if (m_owner_opt_state) { | |||
| on_opr = [state=m_owner_opt_state, &cb](OperatorNodeBase *opr) { | |||
| on_opr = [state = m_owner_opt_state, &cb](OperatorNodeBase* opr) { | |||
| state->m_opr_property_flag = OprPropertyFlag::ALL; | |||
| state->m_cur_iter_src_opr = cg::get_opr_root_source_opr(opr); | |||
| state->m_cur_iter_opr_priority = | |||
| opr->node_prop().attribute().priority; | |||
| opr->node_prop().attribute().priority; | |||
| state->m_cur_iter_opr_stream_prop_type = | |||
| state->m_comp_node_opt.stream_prop_type( | |||
| opr->output(0)); | |||
| state->m_comp_node_opt.stream_prop_type(opr->output(0)); | |||
| mgb_assert(state->m_oprs_inserted.empty()); | |||
| cb(opr); | |||
| state->m_opr_property_flag = OprPropertyFlag::NONE; | |||
| @@ -188,19 +186,19 @@ void SubGraph::iter( | |||
| } | |||
| cg::DepOprIter dep_iter{on_opr, std::move(extra_dep)}; | |||
| for (auto i: m_endpoint_oprs) | |||
| for (auto i : m_endpoint_oprs) | |||
| dep_iter.add(i); | |||
| } | |||
| ThinHashMap<VarNode*, size_t> SubGraph::get_var2nr_val_dep_oprs() const { | |||
| ThinHashMap<VarNode*, size_t> ret; | |||
| auto cb = [&](OperatorNodeBase *opr) { | |||
| for (auto &&i: opr->node_prop().dep_map()) { | |||
| auto cb = [&](OperatorNodeBase* opr) { | |||
| for (auto&& i : opr->node_prop().dep_map()) { | |||
| if (OperatorNodeBase::NodeProp::is_device_value_dep(i.second)) { | |||
| ++ ret.at(i.first); | |||
| ++ret.at(i.first); | |||
| } | |||
| } | |||
| for (auto i: opr->output()) { | |||
| for (auto i : opr->output()) { | |||
| if (!i->contain_flag(VarNode::Flag::VOLATILE_CONTENT)) { | |||
| auto ins = ret.insert({i, 0}); | |||
| mgb_assert(ins.second); | |||
| @@ -208,13 +206,13 @@ ThinHashMap<VarNode*, size_t> SubGraph::get_var2nr_val_dep_oprs() const { | |||
| } | |||
| }; | |||
| iter(cb); | |||
| for (auto i: m_endpoint_vars_set) { | |||
| for (auto i : m_endpoint_vars_set) { | |||
| auto iter = ret.find(i); | |||
| if (iter == ret.end()) { | |||
| mgb_assert(i->contain_flag(VarNode::Flag::VOLATILE_CONTENT)); | |||
| ret[i] = 1; | |||
| } else { | |||
| ++ ret.at(i); | |||
| ++ret.at(i); | |||
| } | |||
| } | |||
| return ret; | |||
| @@ -222,10 +220,8 @@ ThinHashMap<VarNode*, size_t> SubGraph::get_var2nr_val_dep_oprs() const { | |||
| /* ================ UniqReaderCheck ================ */ | |||
| UniqReaderCheck::UniqReaderCheck(const SubGraph &graph): | |||
| m_var2nr_val_dep{graph.get_var2nr_val_dep_oprs()} | |||
| { | |||
| } | |||
| UniqReaderCheck::UniqReaderCheck(const SubGraph& graph) | |||
| : m_var2nr_val_dep{graph.get_var2nr_val_dep_oprs()} {} | |||
| void UniqReaderCheck::update_on_opr_auto_replace(OperatorNodeBase* opr, | |||
| OperatorNodeBase* repl_opr) { | |||
| @@ -253,32 +249,30 @@ void UniqReaderCheck::update_on_opr_auto_replace(OperatorNodeBase* opr, | |||
| /* ================ OptState ================ */ | |||
| OptState::OptState( | |||
| const GraphOptimizer *owner_optimizer, const SubGraph& graph): | |||
| m_owner_optimizer{owner_optimizer}, | |||
| m_var_replace_map{ | |||
| const_cast<ThinHashMap<VarNode*, VarNode*>*>( | |||
| &GraphOptimizer::var_replace_map(*graph.comp_graph()))}, | |||
| m_comp_node_opt{graph.comp_graph()->seq_comp_node_optimizer()}, | |||
| m_graph{graph} | |||
| { | |||
| OptState::OptState(const GraphOptimizer* owner_optimizer, const SubGraph& graph) | |||
| : m_owner_optimizer{owner_optimizer}, | |||
| m_var_replace_map{const_cast<ThinHashMap<VarNode*, VarNode*>*>( | |||
| &GraphOptimizer::var_replace_map(*graph.comp_graph()))}, | |||
| m_comp_node_opt{graph.comp_graph()->seq_comp_node_optimizer()}, | |||
| m_graph{graph} { | |||
| mgb_assert(!m_graph.m_owner_opt_state); | |||
| m_var_replace_map->clear(); | |||
| m_graph.m_owner_opt_state = this; | |||
| m_oprs_inserted.clear(); | |||
| auto on_opr_insert = [this](const cg::event::OprInserted &ev) { | |||
| auto on_opr_insert = [this](const cg::event::OprInserted& ev) { | |||
| auto need_src_opr = m_opr_property_flag & OprPropertyFlag::SOURCE_OPR, | |||
| need_priority = m_opr_property_flag & OprPropertyFlag::PRIORITY; | |||
| if (need_src_opr) | |||
| mgb_assert(m_cur_iter_src_opr, "opr %s{%s} created outside from " | |||
| "SubGraph::iter", | |||
| ev.opr->cname(), ev.opr->dyn_typeinfo()->name); | |||
| mgb_assert(m_cur_iter_src_opr, | |||
| "opr %s{%s} created outside from " | |||
| "SubGraph::iter", | |||
| ev.opr->cname(), ev.opr->dyn_typeinfo()->name); | |||
| if (ev.exc || ev.is_dedup) | |||
| return; | |||
| auto &&new_attr = ev.opr->node_prop().attribute(); | |||
| auto &&ins = m_oprs_inserted.insert({ev.opr, OprPropertyFlag::NONE}); | |||
| auto&& new_attr = ev.opr->node_prop().attribute(); | |||
| auto&& ins = m_oprs_inserted.insert({ev.opr, OprPropertyFlag::NONE}); | |||
| mgb_assert(ins.second); | |||
| if (need_src_opr && !new_attr.src_opr) { | |||
| @@ -296,20 +290,22 @@ OptState::OptState( | |||
| auto csp = m_cur_iter_opr_stream_prop_type; | |||
| if (csp.prop_type != cg::SeqCompNodeOptimizer::StreamPropType::NONE) { | |||
| for (auto i: ev.opr->output()) | |||
| for (auto i : ev.opr->output()) | |||
| m_comp_node_opt.register_stream_var(i, csp); | |||
| } | |||
| }; | |||
| m_on_opr_insert_handler = graph.comp_graph()->event().register_receiver< | |||
| cg::event::OprInserted>(on_opr_insert); | |||
| m_on_opr_insert_handler = | |||
| graph.comp_graph() | |||
| ->event() | |||
| .register_receiver<cg::event::OprInserted>(on_opr_insert); | |||
| } | |||
| void OptState::on_var_replaced(VarNode *src, VarNode *dst, const char *msg) { | |||
| void OptState::on_var_replaced(VarNode* src, VarNode* dst, const char* msg) { | |||
| if (src->contain_flag(VarNode::Flag::VOLATILE_CONTENT)) { | |||
| // this can only happen in auto_replace_outputs() | |||
| mgb_assert(dst->contain_flag(VarNode::Flag::VOLATILE_CONTENT) && | |||
| src->owner_opr()->dyn_typeinfo() == | |||
| dst->owner_opr()->dyn_typeinfo()); | |||
| src->owner_opr()->dyn_typeinfo() == | |||
| dst->owner_opr()->dyn_typeinfo()); | |||
| mgb_assert(!msg); | |||
| return; | |||
| } | |||
| @@ -362,7 +358,7 @@ void OptState::on_var_replaced(VarNode *src, VarNode *dst, const char *msg) { | |||
| return f & (InferType::RT_STATIC | InferType::CONST); | |||
| }; | |||
| if (!(norm(it0.shape) == norm(it1.shape) && | |||
| norm(it0.value) <= norm(it1.value))) { | |||
| norm(it0.value) <= norm(it1.value))) { | |||
| suc = false; | |||
| fail_chks.push_back("infer-type"); | |||
| } | |||
| @@ -407,22 +403,21 @@ void OptState::on_var_replaced(VarNode *src, VarNode *dst, const char *msg) { | |||
| #if MGB_ENABLE_LOGGING | |||
| if (msg && m_owner_optimizer->verbosity()) { | |||
| m_log_msg. | |||
| append("\n "). | |||
| append(std::to_string(m_log_nr_item)). | |||
| append(": "). | |||
| append(src->owner_opr()->cname()). | |||
| append(" => "). | |||
| append(dst->owner_opr()->cname()). | |||
| append(" ("). | |||
| append(msg). | |||
| append(")"); | |||
| } | |||
| ++ m_log_nr_item; | |||
| m_log_msg.append("\n ") | |||
| .append(std::to_string(m_log_nr_item)) | |||
| .append(": ") | |||
| .append(src->owner_opr()->cname()) | |||
| .append(" => ") | |||
| .append(dst->owner_opr()->cname()) | |||
| .append(" (") | |||
| .append(msg) | |||
| .append(")"); | |||
| } | |||
| ++m_log_nr_item; | |||
| #endif | |||
| } | |||
| size_t OptState::flush_log(const char *title) { | |||
| size_t OptState::flush_log(const char* title) { | |||
| if (m_owner_optimizer->verbosity() >= 2) { | |||
| if (m_log_msg.empty()) { | |||
| m_log_msg = mgb_cstr_log(" no var replacement logged"); | |||
| @@ -435,42 +430,40 @@ size_t OptState::flush_log(const char *title) { | |||
| return ret; | |||
| } | |||
| void OptState::call_with_opr(OperatorNodeBase *opr, thin_function<void(void)> func, | |||
| void OptState::call_with_opr(OperatorNodeBase* opr, | |||
| thin_function<void(void)> func, | |||
| OprPropertyFlag opr_property_flag) { | |||
| auto src_opr = cg::get_opr_root_source_opr(opr); | |||
| auto opr_priority = opr->node_prop().attribute().priority; | |||
| auto stream_prop_type = m_comp_node_opt.stream_prop_type(opr->output(0)); | |||
| ThinHashMap<OperatorNodeBase*, OprPropertyFlag> oprs_inserted; | |||
| auto swap_properties = [&, | |||
| need_src_opr = opr_property_flag & OprPropertyFlag::SOURCE_OPR, | |||
| need_priority = opr_property_flag & OprPropertyFlag::PRIORITY] { | |||
| if (need_src_opr) { | |||
| std::swap(m_cur_iter_src_opr, src_opr); | |||
| } | |||
| if (need_priority) { | |||
| std::swap(m_cur_iter_opr_priority, opr_priority); | |||
| } | |||
| std::swap(m_cur_iter_opr_stream_prop_type, stream_prop_type); | |||
| std::swap(m_opr_property_flag, opr_property_flag); | |||
| std::swap(m_oprs_inserted, oprs_inserted); | |||
| }; | |||
| auto swap_properties = | |||
| [&, need_src_opr = opr_property_flag & OprPropertyFlag::SOURCE_OPR, | |||
| need_priority = opr_property_flag & OprPropertyFlag::PRIORITY] { | |||
| if (need_src_opr) { | |||
| std::swap(m_cur_iter_src_opr, src_opr); | |||
| } | |||
| if (need_priority) { | |||
| std::swap(m_cur_iter_opr_priority, opr_priority); | |||
| } | |||
| std::swap(m_cur_iter_opr_stream_prop_type, stream_prop_type); | |||
| std::swap(m_opr_property_flag, opr_property_flag); | |||
| std::swap(m_oprs_inserted, oprs_inserted); | |||
| }; | |||
| MGB_TRY { | |||
| swap_properties(); | |||
| func(); | |||
| } MGB_FINALLY({ | |||
| swap_properties(); | |||
| }); | |||
| } | |||
| MGB_FINALLY({ swap_properties(); }); | |||
| } | |||
| /* ================ RecursiveSubGraphRewriteHelper ================ */ | |||
| RecursiveSubGraphRewriteHelper:: | |||
| ~RecursiveSubGraphRewriteHelper() noexcept = default; | |||
| RecursiveSubGraphRewriteHelper::~RecursiveSubGraphRewriteHelper() noexcept = | |||
| default; | |||
| RecursiveSubGraphRewriteHelper::RecursiveSubGraphRewriteHelper(OptState &state): | |||
| m_opt_state{state}, m_rewriter{state.graph().make_rewriter()} | |||
| { | |||
| } | |||
| RecursiveSubGraphRewriteHelper::RecursiveSubGraphRewriteHelper(OptState& state) | |||
| : m_opt_state{state}, m_rewriter{state.graph().make_rewriter()} {} | |||
| void RecursiveSubGraphRewriteHelper::apply() { | |||
| using namespace std::placeholders; | |||
| @@ -479,8 +472,8 @@ void RecursiveSubGraphRewriteHelper::apply() { | |||
| m_rewriter.apply_inplace(); | |||
| } | |||
| void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase *opr) { | |||
| auto on_new_opr = [this](OperatorNodeBase *opr) { | |||
| void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase* opr) { | |||
| auto on_new_opr = [this](OperatorNodeBase* opr) { | |||
| auto repl_opr = m_rewriter.auto_replace_outputs(opr); | |||
| return on_new_opr_check_should_process(opr, repl_opr); | |||
| }; | |||
| @@ -493,8 +486,8 @@ void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase *opr) { | |||
| return; | |||
| mgb_assert(m_opr_stack.empty()); | |||
| m_opr_stack.push_back({ | |||
| orig_out, m_rewriter.get_var(orig_out)->owner_opr()}); | |||
| m_opr_stack.push_back( | |||
| {orig_out, m_rewriter.get_var(orig_out)->owner_opr()}); | |||
| bool first = true; | |||
| while (!m_opr_stack.empty()) { | |||
| @@ -515,9 +508,9 @@ void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase *opr) { | |||
| if (should_process) { | |||
| auto trans = process_opr(cur_out); | |||
| if (trans.valid()) { | |||
| m_opr_stack.push_back({ | |||
| cur_frame.orig_var, trans->result->owner_opr()}); | |||
| for (auto i: reverse_adaptor(trans->internal)) { | |||
| m_opr_stack.push_back( | |||
| {cur_frame.orig_var, trans->result->owner_opr()}); | |||
| for (auto i : reverse_adaptor(trans->internal)) { | |||
| if (i) | |||
| m_opr_stack.push_back({i, i->owner_opr()}); | |||
| } | |||
| @@ -532,7 +525,7 @@ void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase *opr) { | |||
| auto src = cur_frame.orig_var; | |||
| if (m_rewriter.get_var(src) != cur_out) { | |||
| const char *msg = nullptr; | |||
| const char* msg = nullptr; | |||
| if (m_opr_stack.empty()) { | |||
| msg = m_log_msg.c_str(); | |||
| } | |||
| @@ -550,11 +543,12 @@ void RecursiveSubGraphRewriteHelper::on_opr(OperatorNodeBase *opr) { | |||
| GraphOptimizer::~GraphOptimizer() noexcept = default; | |||
| class GraphOptimizer::VarReplaceMapStorage :public UserDataContainer::UserData { | |||
| class GraphOptimizer::VarReplaceMapStorage | |||
| : public UserDataContainer::UserData { | |||
| MGB_TYPEINFO_OBJ_DECL; | |||
| public: | |||
| ThinHashMap<VarNode*, VarNode*> map; | |||
| public: | |||
| ThinHashMap<VarNode*, VarNode*> map; | |||
| }; | |||
| MGB_TYPEINFO_OBJ_IMPL(GraphOptimizer::VarReplaceMapStorage); | |||
| @@ -565,7 +559,7 @@ GraphOptimizer& GraphOptimizer::add_pass(std::unique_ptr<Pass> pass) { | |||
| return *this; | |||
| } | |||
| SubGraph GraphOptimizer::apply(const SubGraph &graph) const { | |||
| SubGraph GraphOptimizer::apply(const SubGraph& graph) const { | |||
| RealTimer timer; | |||
| OptState state{this, graph}; | |||
| @@ -574,38 +568,38 @@ SubGraph GraphOptimizer::apply(const SubGraph &graph) const { | |||
| // first update output var shapes of all oprs | |||
| state.graph().iter(cg::update_output_var_shapes); | |||
| auto &&opt = graph.comp_graph()->options(); | |||
| auto&& opt = graph.comp_graph()->options(); | |||
| auto orig_setting = opt.graph_opt_level; | |||
| Pass *cur_pass = nullptr; | |||
| Pass* cur_pass = nullptr; | |||
| MGB_MARK_USED_VAR(cur_pass); | |||
| MGB_TRY { | |||
| for (auto &&i: m_passes) { | |||
| for (auto&& i : m_passes) { | |||
| state.set_var_replace_check_flag(VarReplaceCheckFlag::CHECK_ALL); | |||
| cur_pass = i.get(); | |||
| opt.graph_opt_level = 1; | |||
| i->apply(state); | |||
| tot_nr_replace += state.flush_log( | |||
| mgb_ssprintf_log( | |||
| "apply optimization pass %s:", i->name()).c_str()); | |||
| mgb_ssprintf_log("apply optimization pass %s:", i->name()) | |||
| .c_str()); | |||
| } | |||
| } MGB_CATCH(std::exception &exc, { | |||
| } | |||
| MGB_CATCH(std::exception & exc, { | |||
| mgb_log_error("error while applying optimization pass %s: %s", | |||
| cur_pass->name(), exc.what()); | |||
| cur_pass->name(), exc.what()); | |||
| opt.graph_opt_level = orig_setting; | |||
| throw; | |||
| }) | |||
| MGB_FINALLY( | |||
| opt.graph_opt_level = orig_setting | |||
| ); | |||
| MGB_FINALLY(opt.graph_opt_level = orig_setting); | |||
| if (verbosity() >= 1) { | |||
| mgb_log_debug("graph optimization: applied %zu passes, " | |||
| mgb_log_debug( | |||
| "graph optimization: applied %zu passes, " | |||
| "total %zu var(s) replaced; time=%.2fms", | |||
| m_passes.size(), tot_nr_replace, timer.get_msecs()); | |||
| } | |||
| return state.graph(); | |||
| } | |||
| const GraphOptimizer& GraphOptimizer::apply_inplace(VarNodeArray &vars) const { | |||
| const GraphOptimizer& GraphOptimizer::apply_inplace(VarNodeArray& vars) const { | |||
| if (m_passes.empty()) { | |||
| // this check is necessary, since OptState would clear | |||
| // var_replace_map() | |||
| @@ -613,7 +607,7 @@ const GraphOptimizer& GraphOptimizer::apply_inplace(VarNodeArray &vars) const { | |||
| } | |||
| auto g = apply({{vars.begin(), vars.end()}}); | |||
| for (size_t i = 0; i < vars.size(); ++ i) { | |||
| for (size_t i = 0; i < vars.size(); ++i) { | |||
| vars[i] = g.endpoint_vars()[i].node(); | |||
| } | |||
| return *this; | |||
| @@ -653,7 +647,7 @@ GraphOptimizer& GraphOptimizer::add_preset_passes( | |||
| #if MGB_JIT | |||
| bool need_jit = false; | |||
| if (comp_graph_opt && (std::abs(comp_graph_opt->graph_opt_level) >= 3 || | |||
| comp_graph_opt->graph_opt.jit)) { | |||
| comp_graph_opt->graph_opt.jit)) { | |||
| need_jit = true; | |||
| } | |||
| if (need_jit && after_grad) { | |||
| @@ -679,7 +673,6 @@ GraphOptimizer& GraphOptimizer::add_preset_passes( | |||
| add_passes_for_optimize_options(*inference_opt); | |||
| } | |||
| if (inference_opt) { | |||
| // merge params to reduce loading time and graph overhead | |||
| add_pass<ParamMergePass>(); | |||
| @@ -689,15 +682,16 @@ GraphOptimizer& GraphOptimizer::add_preset_passes( | |||
| } | |||
| const ThinHashMap<VarNode*, VarNode*>& GraphOptimizer::var_replace_map( | |||
| ComputingGraph &graph) { | |||
| auto storage = graph.options().user_data.get_user_data_or_create< | |||
| VarReplaceMapStorage>(); | |||
| ComputingGraph& graph) { | |||
| auto storage = | |||
| graph.options() | |||
| .user_data.get_user_data_or_create<VarReplaceMapStorage>(); | |||
| return storage->map; | |||
| } | |||
| VarNode* GraphOptimizer::var_replace_lookup(VarNode *var) { | |||
| auto &&map = var_replace_map(*(var->owner_graph())); | |||
| for (; ; ) { | |||
| VarNode* GraphOptimizer::var_replace_lookup(VarNode* var) { | |||
| auto&& map = var_replace_map(*(var->owner_graph())); | |||
| for (;;) { | |||
| auto iter = map.find(var); | |||
| if (iter == map.end()) | |||
| return var; | |||
| @@ -705,7 +699,6 @@ VarNode* GraphOptimizer::var_replace_lookup(VarNode *var) { | |||
| } | |||
| } | |||
| const GraphOptimizer& GraphOptimizer::add_passes_for_optimize_options( | |||
| const cg::GraphCommonOptimizeOptions& options) { | |||
| return add_passes_for_optimize_options( | |||
| @@ -723,12 +716,14 @@ const GraphOptimizer& GraphOptimizer::add_passes_for_optimize_options( | |||
| options.disable_##_option(); \ | |||
| } \ | |||
| } | |||
| cb(fuse_preprocess, {add_pass(FuseNCHW4Int8Preprocess::make());}); | |||
| cb(fuse_preprocess, { | |||
| add_pass(FuseNCHW4Int8Preprocess::make()); | |||
| add_pass<FuseWarpPerspectiveDimshufflePass>(); | |||
| }); | |||
| cb(f16_io_comp, { add_pass(ConvertF32ToF16Pass::make(false)); }); | |||
| cb(f16_io_f32_comp, { add_pass(ConvertF32ToF16Pass::make(true)); }); | |||
| cb(nchw4, { | |||
| add_pass<FuseConvBiasNonlinPass>(); | |||
| add_pass<FuseConvBiasZPass>(); | |||
| @@ -763,6 +758,7 @@ const GraphOptimizer& GraphOptimizer::add_passes_for_optimize_options( | |||
| add_pass<ShuffleShuffleRemovePass>(); | |||
| add_pass<RemoveRedundantTypeCvtPass>(); | |||
| add_pass(FuseNCHW4Int8Preprocess::make()); | |||
| add_pass<FuseWarpPerspectiveDimshufflePass>(); | |||
| }); | |||
| cb(chwn4, { | |||
| add_pass<FuseConvBiasNonlinPass>(); | |||
| @@ -790,9 +786,9 @@ const GraphOptimizer& GraphOptimizer::add_passes_for_optimize_options( | |||
| /* ================ ConstVarPropogateBase ================ */ | |||
| ConstVarPropogate::AddOprResult ConstVarPropogate::add_opr( | |||
| OperatorNodeBase *opr) { | |||
| OperatorNodeBase* opr) { | |||
| using ProfFlag = OperatorNodeBase::NodeProp::Flag; | |||
| auto &&info = m_oprinfo[opr]; | |||
| auto&& info = m_oprinfo[opr]; | |||
| if (info.processed) | |||
| return info.result; | |||
| info.processed = true; | |||
| @@ -819,15 +815,14 @@ ConstVarPropogate::AddOprResult ConstVarPropogate::add_opr( | |||
| if (opr->input().empty()) | |||
| return make_ret(); | |||
| if (opr->node_prop().contain( | |||
| ProfFlag::FORCE_UPDATE_INPUT_VAR | | |||
| ProfFlag::IMPURE_FUNC)) { | |||
| if (opr->node_prop().contain(ProfFlag::FORCE_UPDATE_INPUT_VAR | | |||
| ProfFlag::IMPURE_FUNC)) { | |||
| return make_ret(); | |||
| } | |||
| size_t max_input_size = 0; | |||
| ret.all_const_inp = true; | |||
| for (auto i: opr->input()) { | |||
| for (auto i : opr->input()) { | |||
| auto io = i->owner_opr(); | |||
| auto iter = m_oprinfo.find(io); | |||
| if (iter == m_oprinfo.end()) { | |||
| @@ -835,7 +830,7 @@ ConstVarPropogate::AddOprResult ConstVarPropogate::add_opr( | |||
| iter = m_oprinfo.find(io); | |||
| mgb_assert(iter != m_oprinfo.end()); | |||
| } | |||
| auto &&src = iter->second; | |||
| auto&& src = iter->second; | |||
| if (src.is_const) { | |||
| update_max(max_input_size, src.max_size); | |||
| ret.has_const_inp = true; | |||
| @@ -19,6 +19,7 @@ | |||
| #include "megbrain/opr/utility.h" | |||
| #include "megbrain/serialization/opr_shallow_copy.h" | |||
| #include "megbrain/serialization/serializer.h" | |||
| #include "megbrain/opr/imgproc.h" | |||
| using namespace mgb; | |||
| using namespace gopt; | |||
| @@ -443,4 +444,244 @@ void FuseNCHW4Int8Preprocess::apply(OptState& state) const { | |||
| }; | |||
| state.graph().iter(on_opr); | |||
| rewriter.apply_inplace(); | |||
| } | |||
| /* ==================== FuseWarpPerspectiveDimshufflePass ================= */ | |||
| const char* FuseWarpPerspectiveDimshufflePass::name() const { | |||
| return mgb_cstr_log("Fuse warp perspective dimshuffle pass"); | |||
| } | |||
| void FuseWarpPerspectiveDimshufflePass::apply(OptState& opt) const { | |||
| auto rewriter = opt.graph().make_rewriter(); | |||
| auto uniq_reader_check = UniqReaderCheck{opt.graph()}; | |||
| auto make_new_warp = [&rewriter](opr::WarpPerspective* warp, | |||
| opr::WarpPerspective::Param new_param, | |||
| megdnn::DType dst_dtype, | |||
| SymbolVar& new_warp) { | |||
| OperatorNodeConfig new_config(dst_dtype); | |||
| if (warp->input().size() == 3) { | |||
| auto src = rewriter.get_var(warp->input(0)), | |||
| mat = rewriter.get_var(warp->input(1)), | |||
| out_shape = rewriter.get_var(warp->input(2)); | |||
| new_warp = opr::WarpPerspective::make(src, mat, out_shape, | |||
| new_param, new_config); | |||
| } else { | |||
| mgb_assert(warp->input().size() == 4); | |||
| auto src = rewriter.get_var(warp->input(0)), | |||
| mat = rewriter.get_var(warp->input(1)), | |||
| mat_idx = rewriter.get_var(warp->input(2)), | |||
| out_shape = rewriter.get_var(warp->input(3)); | |||
| new_warp = opr::WarpPerspective::make(src, mat, mat_idx, out_shape, | |||
| new_param, new_config); | |||
| } | |||
| }; | |||
| auto is_warp_nchw = [&uniq_reader_check](OperatorNodeBase* bottom_opr, | |||
| OperatorNodeBase*& top_opr) { | |||
| // check warp | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>(bottom_opr); | |||
| if (warp == nullptr) | |||
| return false; | |||
| auto inp_dtype = warp->input(0)->dtype(); | |||
| bool is_u8_or_qu8 = inp_dtype.enumv() == DTypeEnum::Quantized8Asymm || | |||
| inp_dtype.enumv() == DTypeEnum::Uint8; | |||
| bool is_nchw = warp->param().format == | |||
| megdnn::param::WarpPerspective::Format::NCHW; | |||
| if (!(is_u8_or_qu8 && is_nchw)) | |||
| return false; | |||
| if (!uniq_reader_check(warp->input(0))) | |||
| return false; | |||
| top_opr = warp; | |||
| return true; | |||
| }; | |||
| auto is_warp_nhwc2nchw = [&uniq_reader_check](OperatorNodeBase* bottom_opr, | |||
| OperatorNodeBase*& top_opr) { | |||
| // check shuffle | |||
| auto shuffle = try_cast_as_op<opr::Dimshuffle>(bottom_opr); | |||
| if (shuffle == nullptr) | |||
| return false; | |||
| auto&& shuffle_param = shuffle->param(); | |||
| if (shuffle_param.pattern_len != 4) | |||
| return false; | |||
| bool is_nhwc2nchw = shuffle_param.pattern[0] == 0 && | |||
| shuffle_param.pattern[1] == 3 && | |||
| shuffle_param.pattern[2] == 1 && | |||
| shuffle_param.pattern[3] == 2; | |||
| if (!is_nhwc2nchw) | |||
| return false; | |||
| if (!uniq_reader_check(shuffle->input(0))) | |||
| return false; | |||
| // check warp | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>( | |||
| shuffle->input(0)->owner_opr()); | |||
| if (warp == nullptr) | |||
| return false; | |||
| auto inp_dtype = warp->input(0)->dtype(); | |||
| bool is_u8_or_qu8 = inp_dtype.enumv() == DTypeEnum::Quantized8Asymm || | |||
| inp_dtype.enumv() == DTypeEnum::Uint8; | |||
| bool is_nhwc = warp->param().format == | |||
| megdnn::param::WarpPerspective::Format::NHWC; | |||
| if (!(is_u8_or_qu8 && is_nhwc)) | |||
| return false; | |||
| top_opr = warp; | |||
| return true; | |||
| }; | |||
| auto try_warp_nchw_typecvt = [&rewriter, &uniq_reader_check, &is_warp_nchw, | |||
| &make_new_warp](OperatorNodeBase* opr) { | |||
| // check typecvt | |||
| auto typecvt = try_cast_as_op<opr::TypeCvt>(opr); | |||
| if (typecvt == nullptr) | |||
| return false; | |||
| bool is_to_f32 = | |||
| typecvt->output(0)->dtype().enumv() == DTypeEnum::Float32; | |||
| if (!is_to_f32) | |||
| return false; | |||
| if (!uniq_reader_check(typecvt->input(0))) | |||
| return false; | |||
| OperatorNodeBase* top_opr = nullptr; | |||
| if (!is_warp_nchw(typecvt->input(0)->owner_opr(), top_opr)) | |||
| return false; | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>(top_opr); | |||
| SymbolVar new_warp; | |||
| make_new_warp(warp, warp->param(), opr->output()[0]->dtype(), new_warp); | |||
| rewriter.replace_var(opr->output(0), new_warp.node(), | |||
| mgb_cstr_log("replace warp + typecvt" | |||
| "fuse warp_dimshuffle(NCHW)")); | |||
| return true; | |||
| }; | |||
| auto try_warp_nhwc2nchw_typecvt = [&rewriter, &uniq_reader_check, | |||
| &is_warp_nhwc2nchw, | |||
| &make_new_warp](OperatorNodeBase* opr) { | |||
| // check typecvt | |||
| auto typecvt = try_cast_as_op<opr::TypeCvt>(opr); | |||
| if (typecvt == nullptr) | |||
| return false; | |||
| bool is_to_f32 = | |||
| typecvt->output(0)->dtype().enumv() == DTypeEnum::Float32; | |||
| if (!is_to_f32) | |||
| return false; | |||
| if (!uniq_reader_check(typecvt->input(0))) | |||
| return false; | |||
| OperatorNodeBase* top_opr = nullptr; | |||
| if (!is_warp_nhwc2nchw(typecvt->input(0)->owner_opr(), top_opr)) | |||
| return false; | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>(top_opr); | |||
| opr::WarpPerspective::Param new_param = warp->param(); | |||
| new_param.format = megdnn::param::WarpPerspective::Format::NHWC_NCHW; | |||
| SymbolVar new_warp; | |||
| make_new_warp(warp, new_param, opr->output()[0]->dtype(), new_warp); | |||
| rewriter.replace_var( | |||
| opr->output(0), new_warp.node(), | |||
| mgb_cstr_log("replace conv_bias + dimshuffle + " | |||
| "typecvt to warp_dimshuffle(NHWC_NCHW)")); | |||
| return true; | |||
| }; | |||
| auto try_warp_nhwc2nchw4_typecvt = [&rewriter, &uniq_reader_check, | |||
| &is_warp_nhwc2nchw, | |||
| &make_new_warp](OperatorNodeBase* opr) { | |||
| // check relayout | |||
| auto relayout = try_cast_as_op<opr::RelayoutFormat>(opr); | |||
| if (relayout == nullptr) | |||
| return false; | |||
| bool is_to_q8 = | |||
| relayout->output(0)->dtype().enumv() == DTypeEnum::QuantizedS8; | |||
| bool is_to_nchw2nchw4 = relayout->param().mode == | |||
| opr::RelayoutFormat::Param::Mode::NCHW_NCHW4; | |||
| if (!(is_to_q8 && is_to_nchw2nchw4)) | |||
| return false; | |||
| if (!uniq_reader_check(relayout->input(0))) | |||
| return false; | |||
| OperatorNodeBase* top_opr = nullptr; | |||
| if (!is_warp_nhwc2nchw(relayout->input(0)->owner_opr(), top_opr)) | |||
| return false; | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>(top_opr); | |||
| bool is_small_chn = warp->input(0)->shape()[3] < 4; | |||
| if (!is_small_chn) | |||
| return false; | |||
| opr::WarpPerspective::Param new_param = warp->param(); | |||
| new_param.format = | |||
| megdnn::param::WarpPerspective::Format::NHWC_NCHW4_IC_SMALL; | |||
| SymbolVar new_warp; | |||
| make_new_warp(warp, new_param, opr->output()[0]->dtype(), new_warp); | |||
| rewriter.replace_var( | |||
| opr->output(0), new_warp.node(), | |||
| mgb_cstr_log("replace warp + dimshuffle + relayout(NCHW_NCHW4)" | |||
| "to warp_dimshuffle(NHWC_NCHW4_IC_SMALL)")); | |||
| return true; | |||
| }; | |||
| auto try_warp_nchw2nchw4_typecvt = [&rewriter, &uniq_reader_check, | |||
| &is_warp_nchw, | |||
| &make_new_warp](OperatorNodeBase* opr) { | |||
| // check relayout | |||
| auto relayout = try_cast_as_op<opr::RelayoutFormat>(opr); | |||
| if (relayout == nullptr) | |||
| return false; | |||
| bool is_to_q8 = | |||
| relayout->output(0)->dtype().enumv() == DTypeEnum::QuantizedS8; | |||
| bool is_to_nchw2nchw4 = relayout->param().mode == | |||
| opr::RelayoutFormat::Param::Mode::NCHW_NCHW4; | |||
| if (!(is_to_q8 && is_to_nchw2nchw4)) | |||
| return false; | |||
| if (!uniq_reader_check(relayout->input(0))) | |||
| return false; | |||
| OperatorNodeBase* top_opr = nullptr; | |||
| if (!is_warp_nchw(relayout->input(0)->owner_opr(), top_opr)) | |||
| return false; | |||
| auto warp = try_cast_as_op<opr::WarpPerspective>(top_opr); | |||
| bool is_small_chn = warp->input(0)->shape()[1] < 4; | |||
| if (!is_small_chn) | |||
| return false; | |||
| opr::WarpPerspective::Param new_param = warp->param(); | |||
| new_param.format = | |||
| megdnn::param::WarpPerspective::Format::NCHW_NCHW4_IC_SMALL; | |||
| SymbolVar new_warp; | |||
| make_new_warp(warp, new_param, opr->output()[0]->dtype(), new_warp); | |||
| rewriter.replace_var( | |||
| opr->output(0), new_warp.node(), | |||
| mgb_cstr_log("replace warp + relayout(NCHW_NCHW4)" | |||
| "to warp_dimshuffle(NCHW_NCHW4_IC_SMALL)")); | |||
| return true; | |||
| }; | |||
| auto on_opr = [&try_warp_nchw_typecvt, &try_warp_nhwc2nchw_typecvt, | |||
| &try_warp_nhwc2nchw4_typecvt, &try_warp_nchw2nchw4_typecvt, | |||
| &rewriter](OperatorNodeBase* opr) { | |||
| if (!try_warp_nchw_typecvt(opr) && !try_warp_nhwc2nchw_typecvt(opr) && | |||
| !try_warp_nhwc2nchw4_typecvt(opr) && | |||
| !try_warp_nchw2nchw4_typecvt(opr)) { | |||
| rewriter.auto_replace_outputs(opr); | |||
| } | |||
| }; | |||
| opt.graph().iter(on_opr); | |||
| rewriter.apply_inplace(); | |||
| } | |||
| @@ -172,6 +172,16 @@ namespace gopt { | |||
| m_opr_replace_func; | |||
| }; | |||
| /*! | |||
| * \brief fuse warp perspective and dimshuffle, quint8/uint8 to qint8/float | |||
| */ | |||
| class FuseWarpPerspectiveDimshufflePass : public Pass { | |||
| public: | |||
| const char* name() const override; | |||
| void apply(OptState& opt) const override; | |||
| }; | |||
| /*! | |||
| * \brief fuse deconv and typecvt to a deconv opr | |||
| */ | |||
| @@ -1172,7 +1172,8 @@ TEST(TestGoptInference, ConvertFormatNHWCD4) { | |||
| param.pad_h = param.pad_w = 1; | |||
| auto w2 = mkcvar("w2", {4, 4, 3, 3}), | |||
| y = opr::Convolution::make(elem, w2, param), | |||
| z = opr::AxisAddRemove::make(y, {opr::AxisAddRemove::AxisDesc::make_add(0)}); | |||
| z = opr::AxisAddRemove::make( | |||
| y, {opr::AxisAddRemove::AxisDesc::make_add(0)}); | |||
| SymbolVar y_opt, z_opt; | |||
| auto options = gopt::OptimizeForInferenceOptions{}; | |||
| @@ -3722,5 +3723,65 @@ TEST(TestGoptInference, PreProcessCase1) { | |||
| ASSERT_TRUE(y_opt.node()->owner_opr()->same_type<opr::RelayoutFormat>()); | |||
| } | |||
| TEST(TestGoptInference, WarpAndPreProcessCase) { | |||
| REQUIRE_GPU(1); | |||
| HostTensorGenerator<dtype::Uint8, RandomDistribution::UNIFORM> gen(0, 255); | |||
| auto cn = CompNode::load("gpu0"); | |||
| auto graph = ComputingGraph::make(); | |||
| graph->options().graph_opt_level = 0; | |||
| size_t n = 1; | |||
| size_t c = 3; | |||
| size_t h = 16; | |||
| size_t w = 16; | |||
| auto host_x1 = gen({n, h, w, c}, cn); | |||
| auto x = opr::Host2DeviceCopy::make(*graph, host_x1); | |||
| auto mat_host = std::make_shared<HostTensorND>(cn, TensorShape{n, 3, 3}, | |||
| dtype::Float32()); | |||
| warp_perspective_mat_gen(*mat_host, n, h, w); | |||
| auto mat = opr::Host2DeviceCopy::make(*graph, mat_host).rename("mat"); | |||
| opr::WarpPerspective::Param warp_param; | |||
| warp_param.format = opr::WarpPerspective::Param::Format::NHWC; | |||
| auto x_warp = | |||
| opr::WarpPerspective::make(x, mat, TensorShape{h, w}, warp_param); | |||
| auto x_nchw = opr::Dimshuffle::make(x_warp, {0, 3, 1, 2}, 4, cn); | |||
| auto x_u8 = opr::TypeCvt::make(x_nchw, dtype::Float32(), cn); | |||
| auto x_s8 = x_u8 - 128; | |||
| auto zero = DTypeScalar(dtype::Float32()); | |||
| auto zero_tensor = opr::ImmutableTensor::make(*graph, zero, cn); | |||
| auto pad_channel_tensor = | |||
| opr::Broadcast::make(zero_tensor, {n, 1, h, w}, cn); | |||
| auto paded_x = opr::Concat::make({x_s8, pad_channel_tensor}, 1, cn) | |||
| .reshape({n, 1, 4, h, w}); | |||
| auto nchw4_out = opr::Dimshuffle::make(paded_x, {0, 1, 3, 4, 2}, 5, cn); | |||
| auto result = opr::TypeCvt::make(nchw4_out, dtype::QuantizedS8(1.f)); | |||
| auto y = result; | |||
| SymbolVar y_opt; | |||
| auto options = gopt::OptimizeForInferenceOptions{}; | |||
| options.enable_fuse_preprocess(); | |||
| unpack_vector(gopt::optimize_for_inference({y}, options), y_opt); | |||
| ASSERT_TRUE(y_opt.node()->owner_opr()->same_type<opr::WarpPerspective>()); | |||
| ASSERT_EQ(opr::WarpPerspective::Param::Format::NHWC_NCHW4_IC_SMALL, | |||
| find_opr<opr::WarpPerspective>(y_opt).param().format); | |||
| graph->compile({{y_opt, {}}}) | |||
| ->to_json() | |||
| ->writeto_fpath(output_file( | |||
| "TestGoptInference.WarpAndPreProcessCase.json")); | |||
| HostTensorND host_y_opt, host_y; | |||
| auto func = graph->compile({make_callback_copy(y, host_y), | |||
| make_callback_copy(y_opt, host_y_opt)}); | |||
| func->execute(); | |||
| MGB_ASSERT_TENSOR_NEAR(host_y, host_y_opt, 1e-5); | |||
| } | |||
| #endif | |||
| // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}} | |||
| @@ -47,7 +47,11 @@ SymbolVar WarpPerspectiveForward::make(SymbolVar i0, SymbolVar i1, SymbolVar i2, | |||
| } | |||
| void WarpPerspectiveForward::init_output_dtype() { | |||
| output(0)->dtype(input(0)->dtype()); | |||
| if (config().output_dtype().valid()) { | |||
| output(0)->dtype(config().output_dtype()); | |||
| } else { | |||
| output(0)->dtype(input(0)->dtype()); | |||
| } | |||
| } | |||
| void WarpPerspectiveForward::add_input_layout_constraint() { | |||
| @@ -78,23 +82,40 @@ void WarpPerspectiveForward::outshape_by_symvar_do_get_output_shape( | |||
| mat_idx_shp.to_string().c_str()); | |||
| } | |||
| //! The index of height, e.g.,[b, h, w, c], the height_idx = 1 | |||
| size_t height_idx = 0; | |||
| if (param().format == Param::Format::NCHW || | |||
| param().format == Param::Format::NCHW4) { | |||
| height_idx = 2; | |||
| } else { | |||
| height_idx = 1; | |||
| } | |||
| dest = imgshp; | |||
| dest[0] = matshp[0]; | |||
| if (param().format == Param::Format::NHWCD4) { | |||
| dest.shape[height_idx] = oshp2d.shape[0]; | |||
| dest.shape[height_idx + 2] = oshp2d.shape[1]; | |||
| } else { | |||
| for (int i = 0; i < 2; ++i) | |||
| dest.shape[height_idx + i] = oshp2d.shape[i]; | |||
| switch (param().format) { | |||
| case Param::Format::NCHW_NCHW4_IC_SMALL: | |||
| case Param::Format::NHWC_NCHW4_IC_SMALL: | |||
| dest.ndim = 5; | |||
| dest[0] = matshp[0]; | |||
| dest.shape[1] = 1; | |||
| dest.shape[2] = oshp2d.shape[0]; | |||
| dest.shape[3] = oshp2d.shape[1]; | |||
| dest.shape[4] = 4; | |||
| break; | |||
| case Param::Format::NHWC_NCHW: | |||
| dest[0] = matshp[0]; | |||
| dest.shape[1] = imgshp.shape[3]; | |||
| dest.shape[2] = oshp2d.shape[0]; | |||
| dest.shape[3] = oshp2d.shape[1]; | |||
| break; | |||
| default: | |||
| size_t height_idx = 0; | |||
| if (param().format == Param::Format::NCHW || | |||
| param().format == Param::Format::NCHW4) { | |||
| height_idx = 2; | |||
| } else { | |||
| height_idx = 1; | |||
| } | |||
| dest = imgshp; | |||
| dest[0] = matshp[0]; | |||
| if (param().format == Param::Format::NHWCD4) { | |||
| dest.shape[height_idx] = oshp2d.shape[0]; | |||
| dest.shape[height_idx + 2] = oshp2d.shape[1]; | |||
| } else { | |||
| for (int i = 0; i < 2; ++i) | |||
| dest.shape[height_idx + i] = oshp2d.shape[i]; | |||
| } | |||
| break; | |||
| } | |||
| } | |||