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[IE CLDNN] Fix handling of fsv4 input padding in mmad bfyx to fsv32 convolution kernel (#3253)

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This commit is contained in:
Jedrzej Hajduczenia
2020-11-27 11:41:13 +01:00
committed by GitHub
parent 86f96a8f3a
commit a09de25dd2
2 changed files with 10 additions and 6 deletions
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8
inference-engine/thirdparty/clDNN/kernel_selector/core/cl_kernels/convolution_gpu_mmad_bfyx_to_b_fs_yx_fsv32.cl vendored
View File

@@ -185,7 +185,9 @@ KERNEL(convolution_mmad_bfyx_to_b_fs_yx_fsv32)(
}
slm_block[c + lid] = AS_PACKED_IN_TYPE(src);
#elif INPUT0_LAYOUT_B_FS_YX_FSV4
const __global uint* ptr = input + input_offset + kh * DILATION_SIZE_Y * input_y_pitch + (x_chunk + lid) * input_x_pitch;
const __global uint* ptr = input + input_offset
+ (kh * DILATION_SIZE_Y + INPUT0_PAD_BEFORE_SIZE_Y) * input_y_pitch
+ (x_chunk + lid + INPUT0_PAD_BEFORE_SIZE_X) * input_x_pitch;
PACKED_IN_TYPE src = AS_PACKED_IN_TYPE(ptr[0]);
slm_block[c + lid] = src;
#endif
@@ -214,7 +216,9 @@ KERNEL(convolution_mmad_bfyx_to_b_fs_yx_fsv32)(
}
slm_block_tail[lid] = AS_PACKED_IN_TYPE(src);
#elif INPUT0_LAYOUT_B_FS_YX_FSV4
const __global uint* ptr = input + input_offset + kh * DILATION_SIZE_Y * input_y_pitch + (x_chunk + lid) * input_x_pitch;
const __global uint* ptr = input + input_offset
+ (kh * DILATION_SIZE_Y + INPUT0_PAD_BEFORE_SIZE_Y) * input_y_pitch
+ (x_chunk + lid + INPUT0_PAD_BEFORE_SIZE_X) * input_x_pitch;
PACKED_IN_TYPE src = AS_PACKED_IN_TYPE(ptr[0]);
slm_block_tail[lid] = src;
#endif

8
inference-engine/thirdparty/clDNN/tests/test_cases/convolution_gpu_test.cpp vendored
View File

@@ -7661,7 +7661,7 @@ template <typename InputT, typename WeightsT, typename OutputT>
class convolution_test_base {
public:
virtual topology build_topology(const cldnn::engine& engine) {
auto input_lay = layout(input_type(), format::bfyx, input_size());
auto input_lay = layout(input_type(), format::bfyx, input_size(), padding_size());
auto wei_lay = layout(weights_type(), format::bfyx, weights_size());
auto wei_mem = memory::allocate(engine, wei_lay);
@@ -7739,7 +7739,7 @@ public:
auto net = network(prog, 0);
auto input_lay = layout(input_type(), format::bfyx, input_size());
auto input_lay = layout(input_type(), format::bfyx, input_size(), padding_size());
auto input_mem = memory::allocate(engine, input_lay);
std::vector<InputT> input_flat(input_lay.get_linear_size(), static_cast<InputT>(0));
for (size_t bi = 0; bi < batch_num(); ++bi)
@@ -8026,7 +8026,7 @@ class convolution_random_test_fsv4_input : public convolution_random_test_base<I
public:
using parent = convolution_random_test_base<InputT, WeightsT, OutputT>;
topology build_topology(const cldnn::engine& engine) override {
auto input_lay = layout(this->input_type(), format::b_fs_yx_fsv4, this->input_size());
auto input_lay = layout(this->input_type(), format::b_fs_yx_fsv4, this->input_size(), this->padding_size());
auto wei_lay = layout(this->weights_type(), format::bfyx, this->weights_size());
auto wei_mem = memory::allocate(engine, wei_lay);
@@ -8099,7 +8099,7 @@ public:
auto net = network(prog, 0);
auto input_lay = layout(this->input_type(), format::b_fs_yx_fsv4, this->input_size());
auto input_lay = layout(this->input_type(), format::b_fs_yx_fsv4, this->input_size(), this->padding_size());
auto input_mem = memory::allocate(engine, input_lay);
std::vector<InputT> input_flat(input_lay.get_linear_size(), static_cast<InputT>(0));
for (size_t bi = 0; bi < this->batch_num(); ++bi)