Skip to content

N
ngraph
Commit 3a312344 authored by Sergey Shalnov's avatar Sergey Shalnov Committed by Scott Cyphers
Browse files
Options

IntelGPU backend: Use clDNN ConvolutionBackpropData in operations partially (#2110)

parent 82f23b38
Hide whitespace changes
Inline Side-by-side
Showing with 93 additions and 25 deletions
src/ngraph/runtime/intelgpu/intelgpu_backend.cpp
View file @ 3a312344
......@@ -22,9 +22,12 @@
#include <CPP/activation_grad.hpp>
#include <CPP/arg_max_min.hpp>
#include <CPP/batch_norm.hpp>
#include <CPP/border.hpp>
#include <CPP/broadcast.hpp>
#include <CPP/concatenation.hpp>
#include <CPP/convolution.hpp>
#include <CPP/convolution_grad_input.hpp>
#include <CPP/crop.hpp>
#include <CPP/data.hpp>
#include <CPP/eltwise.hpp>
#include <CPP/input_layout.hpp>
......@@ -1360,10 +1363,9 @@ bool runtime::intelgpu::IntelGPUBackend::compile(shared_ptr<Function> func)
// clDNN has quite limited support for Convolution operation
// following are the checks to go with workaround
if ((win_stride.size() > 2) || (pad_below.size() > 2 || pad_above.size() > 2) ||
(pad_below.at(0) != pad_above.at(0) || pad_below.at(1) != pad_above.at(1)) ||
(win_dilation.size() > 2) ||
(data_dilation.size() > 2 || data_dilation.at(0) != 1 || data_dilation.at(1) != 1))
if ((win_stride.size() > 2) || (pad_below.size() > 2) || (pad_above.size() > 2) ||
(win_dilation.size() > 2) || (data_dilation.size() > 2) ||
(data_dilation.at(0) != 1) || (data_dilation.at(1) != 1))
{
do_convolution_operation(topology,
get_input_name(op, 0),
......@@ -1387,12 +1389,33 @@ bool runtime::intelgpu::IntelGPUBackend::compile(shared_ptr<Function> func)
}
else
{
const cldnn::tensor input_offset(0, 0, -pad_below.at(1), -pad_below.at(0));
cldnn::tensor::value_type input_offset_x = -pad_below.at(1);
cldnn::tensor::value_type input_offset_y = -pad_below.at(0);
std::string op_input_name = get_input_name(op, 0);
if ((pad_below.at(0) != pad_above.at(0)) || (pad_below.at(1) != pad_above.at(1)))
{
// Different input padding for operation workarounded by adding aux layer
const cldnn::tensor border_pad_above(0, 0, pad_below.at(1), pad_below.at(0));
const cldnn::tensor border_pad_below(0, 0, pad_above.at(1), pad_above.at(0));
input_offset_x = 0;
input_offset_y = 0;
op_input_name += "_bordered";
const cldnn::border cldnn_border(op_input_name,
get_input_name(op, 0),
border_pad_above,
border_pad_below,
cldnn::border_type::zero);
topology.add(cldnn_border);
}
const cldnn::tensor input_offset(0, 0, input_offset_x, input_offset_y);
const cldnn::tensor strides(1, 1, win_stride.at(1), win_stride.at(0));
const cldnn::tensor dilation(1, 1, win_dilation.at(1), win_dilation.at(0));
const cldnn::convolution cldnn_conv(get_output_name(op),
get_input_name(op, 0),
op_input_name,
{get_input_name(op, 1)},
strides,
input_offset,
......@@ -1435,26 +1458,71 @@ bool runtime::intelgpu::IntelGPUBackend::compile(shared_ptr<Function> func)
const shared_ptr<op::ConvolutionBackpropData> conv_op =
static_pointer_cast<op::ConvolutionBackpropData>(op);
const Strides& win_stride = conv_op->get_window_movement_strides_backward();
const CoordinateDiff& pad_below = conv_op->get_padding_below_backward();
const CoordinateDiff& pad_above = conv_op->get_padding_above_backward();
const Strides& win_dilation = conv_op->get_window_dilation_strides_backward();
const Strides& data_dilation = conv_op->get_data_dilation_strides_backward();
if ((win_stride.size() > 2) || (win_stride.at(0) != 1) || (win_stride.at(1) != 1) ||
(pad_below.size() > 2) || (pad_above.size() > 2) || (data_dilation.size() > 2) ||
(data_dilation.at(0) != 1) || (data_dilation.at(1) != 1) ||
(win_dilation.size() > 2) || (win_dilation.at(0) != 1) || (win_dilation.at(1) != 1))
{
do_convolution_operation(topology,
get_input_name(op, 1),
get_input_shape(op, 1),
get_input_name(op, 0),
get_input_shape(op, 0),
get_output_name(op),
get_output_shape(op),
get_output_type(op),
conv_op->get_padding_below_backward(),
conv_op->get_window_movement_strides_backward(),
conv_op->get_window_dilation_strides_backward(),
conv_op->get_data_dilation_strides_backward(),
0,
1,
1,
"input[batch][input_channel]",
"filter[input_channel][output_channel]",
"output[batch][output_channel]",
true);
}
else
{
cldnn::tensor::value_type input_offset_xy = -1;
std::string op_input_name = get_input_name(op, 1);
do_convolution_operation(topology,
get_input_name(op, 1),
get_input_shape(op, 1),
get_input_name(op, 0),
get_input_shape(op, 0),
get_output_name(op),
get_output_shape(op),
get_output_type(op),
conv_op->get_padding_below_backward(),
conv_op->get_window_movement_strides_backward(),
conv_op->get_window_dilation_strides_backward(),
conv_op->get_data_dilation_strides_backward(),
0,
1,
1,
"input[batch][input_channel]",
"filter[input_channel][output_channel]",
"output[batch][output_channel]",
true);
if ((pad_below.at(0) == pad_above.at(0)) && (pad_below.at(1) == pad_above.at(1)))
{
input_offset_xy = pad_below.at(0) - 1;
}
else
{
// Different input padding for operation workarounded by adding aux layer
const cldnn::tensor crop_pad_above(0, 0, -pad_below.at(1), -pad_below.at(0));
const cldnn::tensor crop_pad_below(0, 0, -pad_above.at(1), -pad_above.at(0));
op_input_name += "_cropped";
const cldnn::crop cldnn_crop(op_input_name,
get_input_name(op, 1),
crop_pad_above,
crop_pad_below,
cldnn::crop_borders_t());
topology.add(cldnn_crop);
}
const cldnn::tensor input_offset(0, 0, input_offset_xy, input_offset_xy);
const cldnn::tensor strides(1, 1, win_stride.at(1), win_stride.at(0));
const cldnn::convolution_grad_input cldnn_conv_back_data(get_output_name(op),
op_input_name,
{get_input_name(op, 0)},
strides,
input_offset);
topology.add(cldnn_conv_back_data);
}
break;
}
case OP_TYPEID::Min:
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment