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Def conv - jit fixed #17

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yury-intel Jul 29, 2021
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yury-intel Jul 30, 2021
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yury-intel Aug 2, 2021
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146 changes: 104 additions & 42 deletions inference-engine/src/mkldnn_plugin/nodes/mkldnn_def_conv_node.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,7 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
reg64_t reg_ow_pos = rdx;
reg64_t aux_reg_output = reg_ow_pos;
reg64_t reg_dg_iter = reg_output;
reg64_t reg_gr_iter = rsp;
reg64_t aux_reg_input = rax;
reg64_t aux2_reg_input = reg_kernel;
reg64_t reg_ic_iter = rbx;
Expand Down Expand Up @@ -163,6 +164,10 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
for (size_t d = 0; d < vlen / sizeof(int32_t); ++d) {
dd(1);
}

for (size_t d = 0; d < vlen / sizeof(int32_t); ++d) {
dd(-1);
}
}

void apply_filter(int ow_step, int oc_blocks_step, int oc_step, int ic_step) {
Expand Down Expand Up @@ -359,16 +364,32 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
cvtsi2ss(xmm_ih_im, reg_tmp_32);
addss(xmm_ih_im, xmm_map_h);

movss(xmm_tmp, xmm_ih_im);
cmpss(xmm_tmp, table_val(0), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);
if (jcp_.with_bi_pad) {
movss(xmm_tmp, xmm_ih_im);
cvtps2dq(xmm_tmp, xmm_tmp);
cmpss(xmm_tmp, table_val(6), 0x0e);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);

movss(xmm_tmp, xmm_ih_im);
cvtps2dq(xmm_tmp, xmm_tmp);
cmpss(xmm_tmp, table_val(1), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);
} else {
movss(xmm_tmp, xmm_ih_im);
cmpss(xmm_tmp, table_val(0), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);

cmpss(xmm_ih_im, table_val(1), 1);
movq(reg_tmp_64, xmm_ih_im);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);
cmpss(xmm_ih_im, table_val(1), 1);
movq(reg_tmp_64, xmm_ih_im);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);
}


size_t def_off_w = ((2 * (kh * jcp_.kw + kw) + 1) * jcp_.oh * jcp_.ow) + ow;
Expand All @@ -387,16 +408,33 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
cvtsi2ss(xmm_iw_im, reg_tmp_32);
addss(xmm_iw_im, xmm_map_w);

movss(xmm_tmp, xmm_iw_im);
cmpss(xmm_tmp, table_val(0), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);
if (jcp_.with_bi_pad) {
movss(xmm_tmp, xmm_iw_im);
cvtps2dq(xmm_tmp, xmm_tmp);
cmpss(xmm_tmp, table_val(6), 0x0e);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);

movss(xmm_tmp, xmm_iw_im);
cvtps2dq(xmm_tmp, xmm_tmp);
cmpss(xmm_tmp, table_val(2), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);
} else {
movss(xmm_tmp, xmm_iw_im);
cmpss(xmm_tmp, table_val(0), 1);
movq(reg_tmp_64, xmm_tmp);
cmp(reg_tmp_32, 0);
jne(init_with_zeros, T_NEAR);

cmpss(xmm_iw_im, table_val(2), 1);
movq(reg_tmp_64, xmm_iw_im);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);
}

cmpss(xmm_iw_im, table_val(2), 1);
movq(reg_tmp_64, xmm_iw_im);
cmp(reg_tmp_32, 0);
je(init_with_zeros, T_NEAR);

// interpolation calculation

Expand Down Expand Up @@ -853,7 +891,6 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
L(oc_unrolled_loop); {
cmp(reg_oc_work, jcp_.nb_oc_blocking * jcp_.oc_block);
jl(oc_main_loop, T_NEAR);

ic_loop(ow_step, jcp_.nb_oc_blocking, jcp_.oc_block);
store_output(ow_step, jcp_.nb_oc_blocking, jcp_.oc_block);

Expand All @@ -869,7 +906,6 @@ struct jit_uni_def_conv_kernel_f32 : public jit_uni_def_conv_kernel, public jit_
L(oc_main_loop); {
cmp(reg_oc_work, jcp_.oc_block);
jl(oc_tail, T_NEAR);

ic_loop(ow_step, 1, jcp_.oc_block);
store_output(ow_step, 1, jcp_.oc_block);

Expand Down Expand Up @@ -967,6 +1003,12 @@ void MKLDNNDeformableConvolutionNode::initSupportedPrimitiveDescriptors() {
if (!supportedPrimitiveDescriptors.empty())
return;

const int simd_w = mayiuse(cpu::x64::avx512_common) ? 16 : 8;
if (group != 1 && (((getParentEdgeAt(0)->getDims()[1] / group) % simd_w != 0)
|| ((getChildEdgeAt(0)->getDims()[1] / group) % simd_w != 0))) {
enforceRef = true;
}

size_t inputsNumber = getOriginalInputsNumber();
InferenceEngine::LayerConfig config;
config.dynBatchSupport = false;
Expand All @@ -987,7 +1029,9 @@ void MKLDNNDeformableConvolutionNode::initSupportedPrimitiveDescriptors() {
config.outConfs[0].inPlace = -1;

impl_desc_type impl_type;
if (mayiuse(cpu::x64::avx512_common)) {
if (enforceRef) {
impl_type = impl_desc_type::ref;
} else if (mayiuse(cpu::x64::avx512_common)) {
impl_type = impl_desc_type::jit_avx512;
} else if (mayiuse(cpu::x64::avx2)) {
impl_type = impl_desc_type::jit_avx2;
Expand All @@ -997,8 +1041,8 @@ void MKLDNNDeformableConvolutionNode::initSupportedPrimitiveDescriptors() {
impl_type = impl_desc_type::ref;
}

if (mayiuse(cpu::x64::sse41)) {
// optimzed implementation
if (!enforceRef && mayiuse(cpu::x64::sse41)) {
// optimized implementation
auto dataFormat = memory::format_tag::nhwc;
auto offFormat = memory::format_tag::nchw;
auto weiFormat = group > 1 ? mayiuse(avx512_common) ? memory::format_tag::gOIhw16i16o : memory::format_tag::gOIhw8i8o
Expand Down Expand Up @@ -1062,9 +1106,9 @@ void MKLDNNDeformableConvolutionNode::createPrimitive() {
jcp.oh = dstDims[2];
jcp.ow = dstDims[3];

bool with_groups = group > 1;
jcp.kh = weiDims[with_groups + 2];
jcp.kw = weiDims[with_groups + 3];
// bool with_groups = group > 1;
jcp.kh = weiDims[2];
jcp.kw = weiDims[3];

jcp.t_pad = paddingL[0];
jcp.l_pad = paddingL[1];
Expand Down Expand Up @@ -1097,7 +1141,9 @@ void MKLDNNDeformableConvolutionNode::createPrimitive() {

jcp.nthr = dnnl_get_max_threads();

if (mayiuse(cpu::x64::avx512_common)) {
if (enforceRef) {
return;
} else if (mayiuse(cpu::x64::avx512_common)) {
def_conv_kernel.reset(new jit_uni_def_conv_kernel_f32<cpu::x64::avx512_common>(jcp));
} else if (mayiuse(cpu::x64::avx2)) {
def_conv_kernel.reset(new jit_uni_def_conv_kernel_f32<cpu::x64::avx2>(jcp));
Expand Down Expand Up @@ -1147,7 +1193,7 @@ void MKLDNNDeformableConvolutionNode::executeReference(const float* src, const f

for (int ic = 0; ic < IC; ic++) {
const float *data_im_ptr = src + mb * src_strides[0] + (g * IC + ic) * src_strides[1] + h_in * src_strides[2] + w_in * src_strides[3];
const int deformable_group_index = ic / channel_per_deformable_group;
const int deformable_group_index = (IC * g + ic) / channel_per_deformable_group;
const float *data_offset_ptr = offsets + mb * off_strides[0] + (deformable_group_index * 2 * KH * KW) * off_strides[1];
const float *modulation_offset_ptr = nullptr;
if (modulation != nullptr) {
Expand All @@ -1165,22 +1211,38 @@ void MKLDNNDeformableConvolutionNode::executeReference(const float* src, const f

const float h_im = h_in + map_h; // absolute pixel index with offset
const float w_im = w_in + map_w; // absolute pixel index with offset
if (h_im >= 0 && w_im >= 0 && h_im < IH && w_im < IW) {
const int cur_height = IH - h_in;
const int cur_width = IW - w_in;
int h_low = std::max(static_cast<int>(floorf(map_h)), 0);
int w_low = std::max(static_cast<int>(floorf(map_w)), 0);
int h_high = with_bi_pad ? h_low + 1 : std::min(static_cast<int>(ceilf(map_h)), cur_height - 1);
int w_high = with_bi_pad ? w_low + 1 : std::min(static_cast<int>(ceilf(map_w)), cur_width - 1);
bool skip_compute;
if (with_bilinear_pad) {
skip_compute = !(static_cast<int>(w_im) > -1 &&
static_cast<int>(w_im) < IW &&
static_cast<int>(h_im) > -1 &&
static_cast<int>(h_im) < IH);
} else {
skip_compute = !(w_im >= 0 &&
w_im < IW &&
h_im >= 0 &&
h_im < IH);
}
if (!skip_compute) {
const int cur_h_end = IH - h_in;
const int cur_w_end = IW - w_in;
int h_low = with_bi_pad ? static_cast<int>(floorf(map_h)) :
std::max(static_cast<int>(floorf(map_h)), 0);
int w_low = with_bi_pad ? static_cast<int>(floorf(map_w)) :
std::max(static_cast<int>(floorf(map_w)), 0);
const int cur_h_start = h_low + h_in;
const int cur_w_start = w_low + w_in;
int h_high = with_bi_pad ? h_low + 1 : std::min(static_cast<int>(ceilf(map_h)), cur_h_end - 1);
int w_high = with_bi_pad ? w_low + 1 : std::min(static_cast<int>(ceilf(map_w)), cur_w_end - 1);

float lh = map_h - h_low;
float lw = map_w - w_low;
float hh = 1 - lh, hw = 1 - lw;

float v1 = (w_low >= 0 && h_low >= 0) ? data_im_ptr[h_low * src_strides[2] + w_low * src_strides[3]] : 0.0f;
float v2 = (w_high < cur_width && h_low >= 0) ? data_im_ptr[h_low * src_strides[2] + w_high * src_strides[3]] : 0.0f;
float v3 = (w_low >= 0 && h_high < cur_height) ? data_im_ptr[h_high * src_strides[2] + w_low * src_strides[3]] : 0.0f;
float v4 = (w_high < cur_width && h_high < cur_height) ? data_im_ptr[h_high * src_strides[2] + w_high * src_strides[3]] : 0.0f;
float v1 = (cur_w_start >= 0 && cur_h_start >= 0) ? data_im_ptr[h_low * src_strides[2] + w_low * src_strides[3]] : 0.0f;
float v2 = (w_high < cur_w_end && cur_h_start >= 0) ? data_im_ptr[h_low * src_strides[2] + w_high * src_strides[3]] : 0.0f;
float v3 = (cur_w_start >= 0 && h_high < cur_h_end) ? data_im_ptr[h_high * src_strides[2] + w_low * src_strides[3]] : 0.0f;
float v4 = (w_high < cur_w_end && h_high < cur_h_end) ? data_im_ptr[h_high * src_strides[2] + w_high * src_strides[3]] : 0.0f;
float w1 = hh * hw, w2 = hh * lw, w3 = lh * hw, w4 = lh * lw;

float val = (w1 * v1 + w2 * v2 + w3 * v3 + w4 * v4);
Expand All @@ -1192,8 +1254,8 @@ void MKLDNNDeformableConvolutionNode::executeReference(const float* src, const f
modulation_scalar = modulation_offset_ptr[modulation_index];
}

const float weight = with_groups ? weights[g * wei_strides[0] + oc * wei_strides[1] + ic * wei_strides[2] + kh * wei_strides[3] +
kw * wei_strides[4]]
const float weight = with_groups ? weights[(g + oc / G) * wei_strides[0] + ic * wei_strides[1] + kh * wei_strides[2] +
kw * wei_strides[3]]
: weights[oc * wei_strides[0] + ic * wei_strides[1] + kh * wei_strides[2] + kw * wei_strides[3]];
d += val * weight * modulation_scalar;
}
Expand All @@ -1205,7 +1267,7 @@ void MKLDNNDeformableConvolutionNode::executeReference(const float* src, const f
};

parallel_nd(G, MB, OC, OH, OW,
[&](int g, int mb, int oc, int oh, int ow) {
[&](int g, int mb, int oc, int oh, int ow) {
dst[mb * dst_strides[0] + (g * OC + oc) * dst_strides[1] + oh * dst_strides[2] + ow * dst_strides[3]] = ker(g, mb, oc, oh, ow);
});
}
Expand Down
1 change: 1 addition & 0 deletions inference-engine/src/mkldnn_plugin/nodes/mkldnn_def_conv_node.h
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,7 @@ class MKLDNNDeformableConvolutionNode : public MKLDNNNode {
bool canBeInPlace() const override {
return false;
}
bool enforceRef = false;

InferenceEngine::Precision getRuntimePrecision() const override;

Expand Down