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[IE CLDNN] Add padding directly to input tensor in conv unit tests (#3014)

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Jedrzej Hajduczenia 2020-11-19 08:17:32 +01:00 committed by GitHub
parent fd0e03286a
commit 281c01725c
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 4 additions and 4 deletions
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8
inference-engine/thirdparty/clDNN/tests/test_cases/convolution_gpu_test.cpp vendored
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@ -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)