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narendasannarendasan
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Merge pull request #195 from peri044/conv3d_layer_support
Add 3d convolution support with testcases
2 parents 5e1b842 + b9a53da commit 7ba20f8

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2 files changed

+165
-1
lines changed

‎core/lowering/passes/conv3d_to_convolution.cpp‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -15,7 +15,7 @@ void Conv3DToConvolution(std::shared_ptr<torch::jit::Graph>& graph) {
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std::string convolution_pattern = R"IR(
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graph(%x, %w, %b, %s, %p, %d, %g):
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%1 : bool = prim::Constant[value=0]()
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%2 : int[] = prim::Constant[value=[0, 0]]()
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%2 : int[] = prim::Constant[value=[0, 0, 0]]()
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%4 : Tensor = aten::_convolution(%x, %w, %b, %s, %p, %d, %1, %2, %g, %1, %1, %1)
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return (%4))IR";;
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‎tests/core/converters/test_conv_deconv.cpp‎

Lines changed: 164 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -203,6 +203,170 @@ TEST(Converters, ATenConvolutionWithPaddingConvertsCorrectly) {
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ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt, 2e-6));
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}
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TEST(Converters, ATenConvolution3dConvertsCorrectly) {
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const auto graph = R"IR(
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graph(%0 : Tensor,
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%1 : Float(32:81, 3:27, 3:9, 3:3, 3:1),
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%2 : Float(32:1)):
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%sv : int = prim::Constant[value=1]()
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%s : int[] = prim::ListConstruct(%sv, %sv, %sv)
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%pv : int = prim::Constant[value=0]()
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%p : int[] = prim::ListConstruct(%pv, %pv, %pv)
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%transposed : bool = prim::Constant[value=0]()
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%opv : int = prim::Constant[value=0]()
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%op : int[] = prim::ListConstruct(%opv, %opv, %opv)
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%g : int = prim::Constant[value=1]()
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%fb : bool = prim::Constant[value=0]()
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%out : Tensor = aten::_convolution(%0, %1, %2, %s, %p, %s, %transposed, %op, %g, %fb, %fb, %fb)
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return (%out))IR";
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auto g = std::make_shared<torch::jit::Graph>();
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torch::jit::parseIR(graph, &*g);
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auto in = at::randint(1, 10, {1, 3, 5, 5, 5}, {at::kCUDA});
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auto w = at::randint(1, 10, {32, 3, 3, 3, 3}, {at::kCUDA});
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auto b = at::randint(1, 10, {32}, {at::kCUDA});
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auto jit_in = at::clone(in);
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auto jit_w = at::clone(w);
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auto jit_b = at::clone(b);
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auto params = trtorch::core::conversion::get_named_params(g->inputs(), {jit_w, jit_b});
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auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_in});
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auto trt_in = at::clone(in);
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auto trt_w = at::clone(w);
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auto trt_b = at::clone(b);
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params = trtorch::core::conversion::get_named_params(g->inputs(), {trt_w, trt_b});
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auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_in});
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auto trt = trt_results[0].reshape(jit_results[0].sizes());
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ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt, 2e-6));
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}
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TEST(Converters, ATenConvolution3dNoBiasConvertsCorrectly) {
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const auto graph = R"IR(
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graph(%0 : Tensor,
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%1 : Float(32:81, 3:27, 3:9, 3:3, 3:1)):
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%bias : None = prim::Constant()
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%sv : int = prim::Constant[value=1]()
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%s : int[] = prim::ListConstruct(%sv, %sv, %sv)
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%pv : int = prim::Constant[value=0]()
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%p : int[] = prim::ListConstruct(%pv, %pv, %pv)
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%transposed : bool = prim::Constant[value=0]()
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%opv : int = prim::Constant[value=0]()
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%op : int[] = prim::ListConstruct(%opv, %opv, %opv)
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%g : int = prim::Constant[value=1]()
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%fb : bool = prim::Constant[value=0]()
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%out : Tensor = aten::_convolution(%0, %1, %bias, %s, %p, %s, %transposed, %op, %g, %fb, %fb, %fb)
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return (%out))IR";
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auto g = std::make_shared<torch::jit::Graph>();
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torch::jit::parseIR(graph, &*g);
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auto in = at::randint(1, 2, {1, 3, 5, 5, 5}, {at::kCUDA});
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auto w = at::randint(1, 2, {32, 3, 3, 3, 3}, {at::kCUDA});
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auto jit_in = at::clone(in);
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auto jit_w = at::clone(w);
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auto params = trtorch::core::conversion::get_named_params(g->inputs(), {jit_w});
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auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_in});
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auto trt_in = at::clone(in);
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auto trt_w = at::clone(w);
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params = trtorch::core::conversion::get_named_params(g->inputs(), {trt_w});
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auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_in});
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auto trt = trt_results[0].reshape(jit_results[0].sizes());
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ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt, 2e-6));
284+
}
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TEST(Converters, ATenConvolution3dWithPaddingConvertsCorrectly) {
287+
const auto graph = R"IR(
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graph(%0 : Tensor,
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%1 : Float(32:81, 3:27, 3:9, 3:3, 3:1),
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%2 : Float(32:1)):
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%sv : int = prim::Constant[value=1]()
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%s : int[] = prim::ListConstruct(%sv, %sv, %sv)
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%pv : int = prim::Constant[value=1]()
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%p : int[] = prim::ListConstruct(%pv, %pv, %pv)
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%transposed : bool = prim::Constant[value=0]()
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%opv : int = prim::Constant[value=0]()
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%op : int[] = prim::ListConstruct(%opv, %opv, %opv)
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%g : int = prim::Constant[value=1]()
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%fb : bool = prim::Constant[value=0]()
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%out : Tensor = aten::_convolution(%0, %1, %2, %s, %p, %s, %transposed, %op, %g, %fb, %fb, %fb)
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return (%out))IR";
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auto g = std::make_shared<torch::jit::Graph>();
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torch::jit::parseIR(graph, &*g);
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auto in = at::randint(1, 10, {1, 3, 5, 5, 5}, {at::kCUDA});
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auto w = at::randint(1, 10, {32, 3, 3, 3, 3}, {at::kCUDA});
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auto b = at::randint(1, 10, {32}, {at::kCUDA});
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auto jit_in = at::clone(in);
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auto jit_w = at::clone(w);
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auto jit_b = at::clone(b);
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auto params = trtorch::core::conversion::get_named_params(g->inputs(), {jit_w, jit_b});
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auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_in});
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auto trt_in = at::clone(in);
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auto trt_w = at::clone(w);
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auto trt_b = at::clone(b);
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params = trtorch::core::conversion::get_named_params(g->inputs(), {trt_w, trt_b});
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auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_in});
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auto trt = trt_results[0].reshape(jit_results[0].sizes());
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ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt, 2e-6));
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}
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TEST(Converters, ATenConvolution3dWithStrideDilationConvertsCorrectly) {
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const auto graph = R"IR(
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graph(%0 : Tensor,
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%1 : Float(32:81, 3:27, 3:9, 3:3, 3:1),
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%2 : Float(32:1)):
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%sv : int = prim::Constant[value=2]()
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%s : int[] = prim::ListConstruct(%sv, %sv, %sv)
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%pv : int = prim::Constant[value=1]()
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%p : int[] = prim::ListConstruct(%pv, %pv, %pv)
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%transposed : bool = prim::Constant[value=0]()
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%opv : int = prim::Constant[value=0]()
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%op : int[] = prim::ListConstruct(%opv, %opv, %opv)
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%g : int = prim::Constant[value=1]()
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%fb : bool = prim::Constant[value=0]()
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%out : Tensor = aten::_convolution(%0, %1, %2, %s, %p, %s, %transposed, %op, %g, %fb, %fb, %fb)
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return (%out))IR";
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auto g = std::make_shared<torch::jit::Graph>();
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torch::jit::parseIR(graph, &*g);
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auto in = at::randint(1, 10, {1, 3, 5, 5, 5}, {at::kCUDA});
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auto w = at::randint(1, 10, {32, 3, 3, 3, 3}, {at::kCUDA});
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auto b = at::randint(1, 10, {32}, {at::kCUDA});
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auto jit_in = at::clone(in);
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auto jit_w = at::clone(w);
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auto jit_b = at::clone(b);
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auto params = trtorch::core::conversion::get_named_params(g->inputs(), {jit_w, jit_b});
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auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_in});
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auto trt_in = at::clone(in);
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auto trt_w = at::clone(w);
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auto trt_b = at::clone(b);
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params = trtorch::core::conversion::get_named_params(g->inputs(), {trt_w, trt_b});
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auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_in});
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auto trt = trt_results[0].reshape(jit_results[0].sizes());
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ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt, 2e-6));
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}
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TEST(Converters, ATenConvTransposeConvertsCorrectly) {
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const auto graph = R"IR(
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graph(%0 : Tensor,

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