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未验证 提交 e439268f 编写于 作者: Z zhaoyang-star 提交者： GitHub
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[Cherry-pick][Bugfix][OpenCL] fix depthwise_conv2d_3x3 with dilation > 1 (#4281) (#4325) 

* [Bugfix][OpenCL] fix depthwise_conv2d_3x3 with dilation > 1 (#4281)
Co-authored-by: Nysh329 <ysh329@users.noreply.github.com>
上级 623758ac
隐藏空白更改
内联 并排
Showing with 183 addition and 71 deletion
lite/backends/opencl/cl_kernel/image/depthwise_conv2d_kernel.cl
浏览文件 @ e439268f
......@@ -48,7 +48,7 @@ __kernel void depth_conv2d_3x3(
int2 ouput_pos_in_one_block = (int2)(out_w, out_nh_in_one_batch);
int2 in_pos_in_one_block =
ouput_pos_in_one_block * stride_xy + (int2)(offset, offset);
ouput_pos_in_one_block * stride_xy + (int2)(offset + dilation - 1, offset + dilation - 1);
#ifdef BIASE_CH
CL_DTYPE4 output =
......@@ -77,13 +77,13 @@ __kernel void depth_conv2d_3x3(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1,
pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - dilation,
pos_in_input_block.y + in_pos_in_one_block.y - dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 ||
in_pos_in_one_block.y - 1 < 0 ||
in_pos_in_one_block.x - 1 >= input_width ||
in_pos_in_one_block.y - 1 >= input_height)
(ushort4)((in_pos_in_one_block.x - dilation < 0 ||
in_pos_in_one_block.y - dilation < 0 ||
in_pos_in_one_block.x - dilation >= input_width ||
in_pos_in_one_block.y - dilation >= input_height)
<< 15));
inputs[1] = select(
......@@ -91,45 +91,37 @@ __kernel void depth_conv2d_3x3(
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x,
pos_in_input_block.y + in_pos_in_one_block.y - 1)),
pos_in_input_block.y + in_pos_in_one_block.y - dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - 1 < 0 ||
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y - dilation < 0 ||
in_pos_in_one_block.x >= input_width ||
in_pos_in_one_block.y - 1 >= input_height)
in_pos_in_one_block.y - dilation >= input_height)
<< 15));
inputs[2] = select(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1,
pos_in_input_block.y + in_pos_in_one_block.y - 1)),
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + dilation,
pos_in_input_block.y + in_pos_in_one_block.y - dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 ||
in_pos_in_one_block.y - 1 < 0 ||
in_pos_in_one_block.x + 1 >= input_width ||
in_pos_in_one_block.y - 1 >= input_height)
(ushort4)((in_pos_in_one_block.x + dilation < 0 ||
in_pos_in_one_block.y - dilation < 0 ||
in_pos_in_one_block.x + dilation >= input_width ||
in_pos_in_one_block.y - dilation >= input_height)
<< 15));
inputs[3] = select(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - dilation,
pos_in_input_block.y + in_pos_in_one_block.y)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 || in_pos_in_one_block.y < 0 ||
in_pos_in_one_block.x - 1 >= input_width ||
(ushort4)((in_pos_in_one_block.x - dilation < 0 || in_pos_in_one_block.y < 0 ||
in_pos_in_one_block.x - dilation >= input_width ||
in_pos_in_one_block.y >= input_height)
<< 15));
/*
if (output_pos.x == 112 && output_pos.y == 0) {
CL_DTYPE4 input1 = inputs[3];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 3 - %v4hlf \n", in);
printf(" --- %d ---\n", in_pos_in_one_block.x - 1);
}
*/
inputs[4] = select(
READ_IMG_TYPE(CL_DTYPE_CHAR,
......@@ -147,11 +139,11 @@ __kernel void depth_conv2d_3x3(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + dilation,
pos_in_input_block.y + in_pos_in_one_block.y)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 || in_pos_in_one_block.y < 0 ||
in_pos_in_one_block.x + 1 >= input_width ||
(ushort4)((in_pos_in_one_block.x + dilation < 0 || in_pos_in_one_block.y < 0 ||
in_pos_in_one_block.x + dilation >= input_width ||
in_pos_in_one_block.y >= input_height)
<< 15));
......@@ -159,13 +151,13 @@ __kernel void depth_conv2d_3x3(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - 1,
pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(int2)(pos_in_input_block.x + in_pos_in_one_block.x - dilation,
pos_in_input_block.y + in_pos_in_one_block.y + dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x - 1 < 0 ||
in_pos_in_one_block.y + 1 < 0 ||
in_pos_in_one_block.x - 1 >= input_width ||
in_pos_in_one_block.y + 1 >= input_height)
(ushort4)((in_pos_in_one_block.x - dilation < 0 ||
in_pos_in_one_block.y + dilation < 0 ||
in_pos_in_one_block.x - dilation >= input_width ||
in_pos_in_one_block.y + dilation >= input_height)
<< 15));
inputs[7] = select(
......@@ -173,24 +165,24 @@ __kernel void depth_conv2d_3x3(
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x,
pos_in_input_block.y + in_pos_in_one_block.y + 1)),
pos_in_input_block.y + in_pos_in_one_block.y + dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + 1 < 0 ||
(ushort4)((in_pos_in_one_block.x < 0 || in_pos_in_one_block.y + dilation < 0 ||
in_pos_in_one_block.x >= input_width ||
in_pos_in_one_block.y + 1 >= input_height)
in_pos_in_one_block.y + dilation >= input_height)
<< 15));
inputs[8] = select(
READ_IMG_TYPE(CL_DTYPE_CHAR,
input,
sampler,
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + 1,
pos_in_input_block.y + in_pos_in_one_block.y + 1)),
(int2)(pos_in_input_block.x + in_pos_in_one_block.x + dilation,
pos_in_input_block.y + in_pos_in_one_block.y + dilation)),
(CL_DTYPE4)(0.0f),
(ushort4)((in_pos_in_one_block.x + 1 < 0 ||
in_pos_in_one_block.y + 1 < 0 ||
in_pos_in_one_block.x + 1 >= input_width ||
in_pos_in_one_block.y + 1 >= input_height)
(ushort4)((in_pos_in_one_block.x + dilation < 0 ||
in_pos_in_one_block.y + dilation < 0 ||
in_pos_in_one_block.x + dilation >= input_width ||
in_pos_in_one_block.y + dilation >= input_height)
<< 15));
CL_DTYPE4 filters[9];
......@@ -221,14 +213,18 @@ __kernel void depth_conv2d_3x3(
/*
if (output_pos.x == 112 && output_pos.y == 0) {
if (output_pos.x == 0 && output_pos.y == 0) {
for (int i = 0; i < 9; ++i) {
CL_DTYPE4 input1 = inputs[i];
float4 in = (float4)(input1.x, input1.y, input1.z, input1.w);
printf(" input4 %d - %v4hlf \n", i, in);
printf(" input4[%d]: %v4hlf \n", i, in);
}
for (int i = 0; i < 9; ++i) {
CL_DTYPE4 filters1 = filters[i];
float4 f = (float4)(filters1.x, filters1.y, filters1.z, filters1.w);
printf(" weights4[%d]: %v4hlf \n", i, f);
}
float4 out = (float4)(output.x, output.y, output.z, output.w);
printf(" depth wise output output4 = %v4hlf \n", out);
printf(" pos_in_input_block -x %d \n ", pos_in_input_block.x);
......
lite/kernels/opencl/depthwise_conv2d_image_compute_test.cc
浏览文件 @ e439268f
......@@ -32,6 +32,93 @@ namespace lite {
// #define TEST_DEPTHWISE_CONV_IMAGE_BASIC
#define TEST_DEPTHWISE_CONV_IMAGE_3X3
template <typename Dtype1, typename Dtype2>
static void conv_basic(const Dtype1* din,
Dtype2* dout,
int num,
int chout,
int hout,
int wout,
int chin,
int hin,
int win,
const Dtype1* weights,
const Dtype2* bias,
int group,
int kernel_w,
int kernel_h,
int stride_w,
int stride_h,
int dila_w,
int dila_h,
int pad_w,
int pad_h,
bool flag_bias,
bool flag_relu) {
CHECK(!flag_relu);
auto src_data = din;
auto dst_data_ref = dout;
auto weights_data = weights;
auto with_bias = flag_bias;
auto bias_data = bias;
int in_num = num;
int out_channels = chout;
int out_h = hout;
int out_w = wout;
int in_channel = chin;
int in_h = hin;
int in_w = win;
int out_c_group = out_channels / group;
int in_c_group = in_channel / group;
for (int n = 0; n < in_num; ++n) {
for (int g = 0; g < group; ++g) {
for (int oc = 0; oc < out_c_group; ++oc) {
for (int oh = 0; oh < out_h; ++oh) {
for (int ow = 0; ow < out_w; ++ow) {
int out_idx = n * group * out_c_group * out_h * out_w +
g * out_c_group * out_h * out_w + oc * out_h * out_w +
oh * out_w + ow;
Dtype2 bias_d =
with_bias ? (bias_data[g * out_c_group + oc]) : (Dtype2)0;
dst_data_ref[out_idx] = bias_d;
for (int ic = 0; ic < in_c_group; ++ic) {
for (int kh = 0; kh < kernel_h; ++kh) {
for (int kw = 0; kw < kernel_w; ++kw) {
int iw = ow * stride_w - pad_w + kw * (dila_w);
int ih = oh * stride_h - pad_h + kh * (dila_h);
if (iw < 0 || iw >= in_w) continue;
if (ih < 0 || ih >= in_h) continue;
int iidx = n * in_channel * in_h * in_w +
g * in_c_group * in_h * in_w + ic * in_h * in_w +
ih * in_w + iw;
int widx =
g * out_c_group * in_c_group * kernel_h * kernel_w +
oc * in_c_group * kernel_h * kernel_w +
ic * kernel_h * kernel_w + kh * kernel_w + kw;
dst_data_ref[out_idx] += src_data[iidx] * weights_data[widx];
/*
if (out_idx == 0) {
VLOG(5) << "src[" << iidx << "]: " << src_data[iidx]
<< "\tweights[" << widx << "]: "
<< weights_data[widx]
<< "\tdst[" << out_idx << "]: "
<< dst_data_ref[out_idx];
*/
}
}
}
}
}
}
}
}
}
template <typename T, int STRIDE_H = 1, int STRIDE_W = 1>
void depth_conv(const T* input_data,
const lite::DDim& input_dims,
......@@ -384,11 +471,14 @@ TEST(depthwise_conv2d, compute_basic) {
#ifdef TEST_DEPTHWISE_CONV_IMAGE_3X3
// #define LOOP_TEST
TEST(depthwise_conv2d, compute_image2d_3x3) {
const int fc = 1;
const int fw = 3;
const int fh = fw;
int dilation = 1;
int stride = 1;
int pad = 0;
const int dilation = 4;
const int stride = 2;
const int pad = 2;
const bool bias_flag = false;
const bool relu_flag = false;
#ifdef LOOP_TEST
// for (int batch_size = 1; batch_size < 2; ++batch_size) {
for (int oc = 4; oc < 10; oc += 1) { // oc = ic
......@@ -399,12 +489,18 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
const int ih = 112;
const int iw = 112;
#endif
stride = (stride == 1) ? 2 : 1;
// pad = (pad == 0) ? 1 : 0;
const int fb = oc;
const int ic = oc;
const int oh = ConvOutputSize(ih, fh, dilation, pad, pad, stride);
const int ow = ConvOutputSize(iw, fw, dilation, pad, pad, stride);
if (oh <= 0 || ow <= 0) {
#ifdef LOOP_TEST
continue;
#else
LOG(FATAL) << "Output tensor of depthwise conv is illegal!"
<< "Please check your input dims and conv params";
#endif
}
LOG(INFO) << "to get kernel ...";
auto kernels =
......@@ -417,7 +513,7 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
auto kernel = std::move(kernels.front());
LOG(INFO) << "get kernel";
lite::Tensor input, filter, output;
lite::Tensor input, filter, bias, output;
operators::ConvParam param;
param.x = &input;
param.filter = &filter;
......@@ -428,6 +524,8 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
param.strides = std::vector<int>{stride, stride};
std::vector<int> dilations = {dilation, dilation};
param.dilations = std::make_shared<std::vector<int>>(dilations);
param.bias = bias_flag ? &bias : nullptr;
param.fuse_relu = relu_flag;
std::unique_ptr<KernelContext> context(new KernelContext);
context->As<OpenCLContext>().InitOnce();
......@@ -442,9 +540,11 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
const DDim& input_dim =
lite::DDim{std::vector<int64_t>({1, ic, ih, iw})};
const DDim& filter_dim =
lite::DDim{std::vector<int64_t>({fb, 1, 3, 3})};
lite::DDim{std::vector<int64_t>({fb, fc, fh, fw})};
const DDim& output_dim =
lite::DDim{std::vector<int64_t>({1, oc, oh, ow})};
// element wise bias
const DDim bias_dim = DDim(std::vector<DDim::value_type>{oc});
input.Resize(input_dim);
filter.Resize(filter_dim);
output.Resize(output_dim);
......@@ -460,6 +560,14 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
for (auto& f : filter_v) {
f = gen(engine);
}
std::vector<float> bias_v;
if (bias_flag) {
bias.Resize(bias_dim);
bias_v.resize(bias_dim.production());
for (auto& b : bias_v) {
b = gen(engine);
}
}
LOG(INFO) << "prepare input";
CLImageConverterDefault* default_converter =
......@@ -496,21 +604,29 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
lite::Tensor out_ref;
out_ref.Resize(output_dim);
auto* out_ref_data = out_ref.mutable_data<float>(TARGET(kARM));
if (stride == 1) {
depth_conv<float, 1, 1>(input_v.data(),
input.dims(),
filter_v.data(),
filter.dims(),
out_ref_data,
out_ref.dims());
} else if (stride == 2) {
depth_conv<float, 2, 2>(input_v.data(),
input.dims(),
filter_v.data(),
filter.dims(),
out_ref_data,
out_ref.dims());
}
conv_basic<float, float>(input_v.data(),
out_ref_data,
1,
oc,
oh,
ow,
ic,
ih,
iw,
filter_v.data(),
bias_v.data(),
param.groups,
fw,
fh,
stride,
stride,
dilation,
dilation,
pad,
pad,
bias_flag,
relu_flag);
const size_t cl_image2d_row_pitch{0};
const size_t cl_image2d_slice_pitch{0};
......@@ -538,7 +654,7 @@ TEST(depthwise_conv2d, compute_image2d_3x3) {
EXPECT_FALSE(relative_diff > FP16_MAX_DIFF &&
abs_diff > FP16_ABS_DIFF);
if (relative_diff > FP16_MAX_DIFF && abs_diff > FP16_ABS_DIFF) {
LOG(FATAL) << "error idx:" << i << "output_v[" << i
LOG(FATAL) << "error idx:" << i << " output_v[" << i
<< "]:" << output_v[i] << " "
"out_ref_data["
<< i << "]:" << out_ref_data[i];
......
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