From fe58aba03030daa7175bbe98d10f866869c74e0a Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Thu, 23 Jan 2025 17:14:34 +0100
Subject: [PATCH 1/7] Conv fwd_dims both for nhwc and nchw in input and output
---
include/aidge/operator/Conv.hpp | 4 ++
src/operator/Conv.cpp | 77 ++++++++++++++++++++-------------
2 files changed, 50 insertions(+), 31 deletions(-)
diff --git a/include/aidge/operator/Conv.hpp b/include/aidge/operator/Conv.hpp
index 135ff8860..e2faeb6ac 100644
--- a/include/aidge/operator/Conv.hpp
+++ b/include/aidge/operator/Conv.hpp
@@ -172,6 +172,8 @@ public:
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of input channel imposed.");
}
+ if(getInput(1)->dataFormat()==Aidge::DataFormat::NHWC)
+ return getInput(1)->template dims<DIM+2>()[DIM+1];
return getInput(1)->template dims<DIM+2>()[1];
}
@@ -184,6 +186,8 @@ public:
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of output channel imposed.");
}
+ if(getInput(1)->dataFormat()==Aidge::DataFormat::NHWC)
+ return getInput(1)->template dims<DIM+2>()[DIM+1];
return getInput(1)->template dims<DIM+2>()[0];
}
diff --git a/src/operator/Conv.cpp b/src/operator/Conv.cpp
index 836c47645..746c32dd4 100644
--- a/src/operator/Conv.cpp
+++ b/src/operator/Conv.cpp
@@ -40,42 +40,57 @@ Aidge::Conv_Op<DIM>::Conv_Op(const Aidge::Conv_Op<DIM>& op)
template <Aidge::DimIdx_t DIM>
bool Aidge::Conv_Op<DIM>::forwardDims(bool /*allowDataDependency*/) {
- if (inputsAssociated()) {
- // first check weight since it defines inChannels and outChannels
- AIDGE_ASSERT((getInput(1)->nbDims() == (DIM+2)),
- "Wrong weight Tensor dimension: {} for Conv{}D operator. Expected number of dimensions is {}.", getInput(1)->nbDims(), DIM, DIM+2);
- // check data
+ if (!inputsAssociated())
+ return false;
+ // first check weight since it defines inChannels and outChannels
+ if(getInput(0)->dataFormat() == Aidge::DataFormat::NHWC){
AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
- (getInput(0)->template dims<DIM+2>()[1] == inChannels()),
- "Wrong input size ({}) for Conv operator. Expected dims are [x, {}, {}].", getInput(0)->dims(), inChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
- // check optional bias
- if(getInput(2))
- AIDGE_ASSERT((getInput(2)->nbDims() == (1)) &&
- (getInput(2)->template dims<1>()[0] == outChannels()),
- "Wrong bias size ({}) for Conv operator. Expected dims are [{}].", getInput(2)->dims(), outChannels());
-
- std::array<DimSize_t, DIM + 2> outputDims{};
- const std::array<DimSize_t, DIM + 2> inputDims(getInput(0)->template dims<DIM+2>());
-
- for (std::size_t dim = 0; dim < mAttributes->template getAttr<ConvAttr::KernelDims>().size() ; ++dim) {
- const DimSize_t kernelExtent = mAttributes->template getAttr<ConvAttr::DilationDims>()[dim] *
- (mAttributes->template getAttr<ConvAttr::KernelDims>()[dim] - 1) +
- 1;
-
- outputDims[dim+2] = 1 + static_cast<DimSize_t>(
- floor(static_cast<float>(inputDims[dim+2] - kernelExtent) /
- static_cast<float>(mAttributes->template getAttr<ConvAttr::StrideDims>()[dim])));
- }
+ (getInput(0)->template dims<DIM+2>()[DIM+1] == inChannels()),
+ "Wrong input size ({}) for Conv operator. Expected dims are [{}, {}, x].", getInput(0)->dims(), inChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
+ }
+ else{ //For dataFormat in NCHW or Default Format
+ AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
+ (getInput(0)->template dims<DIM+2>()[1] == inChannels()),
+ "Wrong input size ({}) for Conv operator. Expected dims are [x, {}, {}].", getInput(0)->dims(), inChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
+ }
- outputDims[1] = outChannels();
- outputDims[0] = inputDims[0];
- mOutputs[0]->resize(outputDims);
- return true;
+ AIDGE_ASSERT((getInput(1)->nbDims() == (DIM+2)),
+ "Wrong weight Tensor dimension: {} for Conv{}D operator. Expected number of dimensions is {}.", getInput(1)->nbDims(), DIM, DIM+2);
+
+ if(getInput(2))
+ AIDGE_ASSERT((getInput(2)->nbDims() == (1)) &&
+ (getInput(2)->template dims<1>()[0] == outChannels()),
+ "Wrong bias size ({}) for Conv operator. Expected dims are [{}].", getInput(2)->dims(), outChannels());
+
+ const std::array<DimSize_t, DIM + 2> inputDims(getInput(0)->template dims<DIM+2>());
+ std::array<DimSize_t, DIM + 2> outputDims;
+
+
+ unsigned int in_dims_index = (getInput(0)->dataFormat() == Aidge::DataFormat::NHWC) ? 1 : 2;
+ unsigned int out_dims_index = (getOutput(0)->dataFormat() == Aidge::DataFormat::NHWC) ? 1 : 2;
+
+ for (std::size_t dim = 0; dim < mAttributes->template getAttr<ConvAttr::KernelDims>().size(); ++dim) {
+ const DimSize_t kernelExtent = mAttributes->template getAttr<ConvAttr::DilationDims>()[dim] *
+ (mAttributes->template getAttr<ConvAttr::KernelDims>()[dim] - 1) +
+ 1;
+
+ outputDims[dim + out_dims_index] = 1 + static_cast<DimSize_t>(
+ floor(static_cast<float>(inputDims[dim + in_dims_index] - kernelExtent) /
+ static_cast<float>(mAttributes->template getAttr<ConvAttr::StrideDims>()[dim]))
+ );
}
- return false;
-}
+ if(getOutput(0)->dataFormat() == Aidge::DataFormat::NHWC)
+ outputDims[DIM+1] = outChannels();
+ else
+ outputDims[1] = outChannels();
+ outputDims[0] = inputDims[0];
+ mOutputs[0]->resize(outputDims);
+ return true;
+
+
+}
template <Aidge::DimIdx_t DIM>
std::vector<std::pair<std::vector<Aidge::DimSize_t>, std::vector<Aidge::DimSize_t>>>
--
GitLab
From 6c301e2f6ca3390b345cbe6abc4df8e308884bb6 Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Tue, 28 Jan 2025 15:33:16 +0100
Subject: [PATCH 2/7] New unit_test for forward_conv and some fix about nhwc
format
---
include/aidge/operator/Conv.hpp | 3 +-
src/operator/Conv.cpp | 2 +-
unit_tests/operator/Test_Conv_Op.cpp | 84 ++++++++++++++++++++++++++++
3 files changed, 86 insertions(+), 3 deletions(-)
diff --git a/include/aidge/operator/Conv.hpp b/include/aidge/operator/Conv.hpp
index e2faeb6ac..c6bbd0e40 100644
--- a/include/aidge/operator/Conv.hpp
+++ b/include/aidge/operator/Conv.hpp
@@ -172,6 +172,7 @@ public:
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of input channel imposed.");
}
+
if(getInput(1)->dataFormat()==Aidge::DataFormat::NHWC)
return getInput(1)->template dims<DIM+2>()[DIM+1];
return getInput(1)->template dims<DIM+2>()[1];
@@ -186,8 +187,6 @@ public:
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of output channel imposed.");
}
- if(getInput(1)->dataFormat()==Aidge::DataFormat::NHWC)
- return getInput(1)->template dims<DIM+2>()[DIM+1];
return getInput(1)->template dims<DIM+2>()[0];
}
diff --git a/src/operator/Conv.cpp b/src/operator/Conv.cpp
index 746c32dd4..91aaad8ee 100644
--- a/src/operator/Conv.cpp
+++ b/src/operator/Conv.cpp
@@ -63,7 +63,7 @@ bool Aidge::Conv_Op<DIM>::forwardDims(bool /*allowDataDependency*/) {
"Wrong bias size ({}) for Conv operator. Expected dims are [{}].", getInput(2)->dims(), outChannels());
const std::array<DimSize_t, DIM + 2> inputDims(getInput(0)->template dims<DIM+2>());
- std::array<DimSize_t, DIM + 2> outputDims;
+ std::array<DimSize_t, DIM + 2> outputDims{};
unsigned int in_dims_index = (getInput(0)->dataFormat() == Aidge::DataFormat::NHWC) ? 1 : 2;
diff --git a/unit_tests/operator/Test_Conv_Op.cpp b/unit_tests/operator/Test_Conv_Op.cpp
index bc24fc808..103b8c624 100644
--- a/unit_tests/operator/Test_Conv_Op.cpp
+++ b/unit_tests/operator/Test_Conv_Op.cpp
@@ -22,6 +22,90 @@
#include "aidge/utils/Types.h"
namespace Aidge {
+TEST_CASE("[core/operator] Conv_Op(ForwardDims) ", "[Operator][ForwardDims][Conv]") {
+ SECTION("I:NCHW O:NCHW W:NCHW"){
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,3,224,450}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4})); // Out_ch, In_ch_h,W,H
+
+ const std::vector<std::size_t> expectedOutputDims({16,4,222,447});
+ auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ //Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
+ input->setDataFormat(Aidge::DataFormat::NCHW);
+ weight->setDataFormat(Aidge::DataFormat::NCHW);
+
+ //Set inputs
+ conv1.setInput(1,weight);
+ conv1.setInput(0,input);
+
+ REQUIRE(conv1.forwardDims());
+ REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ }
+
+ SECTION("I:NCHW O:NHWC W:NCHW") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,3,224,450}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4}));
+
+ const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+ auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
+ input->setDataFormat(Aidge::DataFormat::NCHW);
+ weight->setDataFormat(Aidge::DataFormat::NCHW);
+
+ // Set inputs
+ conv1.setInput(1, weight);
+ conv1.setInput(0, input);
+
+ REQUIRE(conv1.forwardDims());
+ REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ }
+
+ SECTION("I:NHWC O:NCHW W:NHWC") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,4,3,3})); // H, W, In_ch, Out_ch
+
+ const std::vector<std::size_t> expectedOutputDims({16,4,222,447});
+ auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
+ input->setDataFormat(Aidge::DataFormat::NHWC);
+ weight->setDataFormat(Aidge::DataFormat::NHWC);
+
+ // Set inputs
+ conv1.setInput(1, weight);
+ conv1.setInput(0, input);
+
+ REQUIRE(conv1.forwardDims());
+ REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ }
+
+ SECTION("I:NHWC O:NHWC W:NCHW") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4})); // Out_ch, In_ch, H, W
+
+ const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+ auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
+ input->setDataFormat(Aidge::DataFormat::NHWC);
+ weight->setDataFormat(Aidge::DataFormat::NCHW);
+
+ // Set inputs
+ conv1.setInput(1, weight);
+ conv1.setInput(0, input);
+
+ REQUIRE(conv1.forwardDims());
+ REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ }
+
+}
+
+
TEST_CASE("[core/operator] Conv_Op(computeReceptiveField)", "[Operator][computeReceptiveField][Conv]") {
auto dataProvider = Producer({16, 3, 224, 224}, "dataProvider");
auto conv1 = Conv(3, 32, {5, 5}, "conv1"); // output dims: {16, 32, 220, 220}
--
GitLab
From a9acb2f86f949d74f7a660d1eddcbc6c4045a2a7 Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Wed, 19 Feb 2025 16:06:52 +0100
Subject: [PATCH 3/7] new comments for Conv.hpp and Conv.cpp
---
include/aidge/operator/Conv.hpp | 3 +++
src/operator/Conv.cpp | 2 +-
2 files changed, 4 insertions(+), 1 deletion(-)
diff --git a/include/aidge/operator/Conv.hpp b/include/aidge/operator/Conv.hpp
index c6bbd0e40..f9c910928 100644
--- a/include/aidge/operator/Conv.hpp
+++ b/include/aidge/operator/Conv.hpp
@@ -173,8 +173,10 @@ public:
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of input channel imposed.");
}
+ // check format
if(getInput(1)->dataFormat()==Aidge::DataFormat::NHWC)
return getInput(1)->template dims<DIM+2>()[DIM+1];
+ // default format is NCHW
return getInput(1)->template dims<DIM+2>()[1];
}
@@ -187,6 +189,7 @@ public:
if (!getInput(1)) {
AIDGE_THROW_OR_ABORT(std::runtime_error, "Convolution operator has no weight Tensor associated so no specific number of output channel imposed.");
}
+ // first weight dimension for both NCHW (Cout,Cin,H,W) and NHWC (Cout,H,W,Cin) data format
return getInput(1)->template dims<DIM+2>()[0];
}
diff --git a/src/operator/Conv.cpp b/src/operator/Conv.cpp
index 91aaad8ee..2077cab52 100644
--- a/src/operator/Conv.cpp
+++ b/src/operator/Conv.cpp
@@ -46,7 +46,7 @@ bool Aidge::Conv_Op<DIM>::forwardDims(bool /*allowDataDependency*/) {
if(getInput(0)->dataFormat() == Aidge::DataFormat::NHWC){
AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
(getInput(0)->template dims<DIM+2>()[DIM+1] == inChannels()),
- "Wrong input size ({}) for Conv operator. Expected dims are [{}, {}, x].", getInput(0)->dims(), inChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
+ "Wrong input size ({}) for Conv operator. Expected dims are [x, {}, {}].", getInput(0)->dims(), fmt::join(std::vector<std::string>(DIM, "x"), ", "), inChannels());
}
else{ //For dataFormat in NCHW or Default Format
AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
--
GitLab
From d2689b32cd2c188b953c5c9be26f3ce0d6966569 Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Thu, 20 Feb 2025 10:44:00 +0100
Subject: [PATCH 4/7] Refactor setDataFormat method to improve data type
handling and transformation logic
---
include/aidge/data/Tensor.hpp | 45 +++++++++++++++++++++++++++--------
1 file changed, 35 insertions(+), 10 deletions(-)
diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 7aa2ed52b..5e4a817bb 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -452,19 +452,44 @@ public:
}
/**
- * @brief Set the DataFormat of the Tensor and transpose data, only
- * if the Tensor has already been initialized and copyTrans is true.
- * In this case, a transposition occurs only if both previous format and
- * new format are different from DataFormat::Default.
- * @param df New DataFormat
- * @param copyTrans If true (default), when both previous format and new
- * format are different from DataFormat::Default, previous
- * data is copy-transposed.
+ * @brief Set the DataType of the Tensor and converts data
+ * if the Tensor has already been initialized and copyCast is true.
+ * @param dt DataType
+ * @param copyCast If true (default), previous data is copy-casted. Otherwise
+ * previous data is lost.
*/
void setDataFormat(const DataFormat df, bool copyTrans = true) {
- if (mImpl && copyTrans && (dataFormat() != df) && df != DataFormat::Default && dataFormat() != DataFormat::Default) {
- copyTranspose(*this, getDataFormatTranspose(dataFormat(), df));
+ if (!copyTrans || df == dataFormat()) {
+ mDataFormat = df;
+ return;
+ }
+ // Skip transformation if both formats are Default or NNCH
+ if ((df == DataFormat::Default && dataFormat() == DataFormat::Default) || df == DataFormat::NCHW && dataFormat() == DataFormat::NCHW) {
+ mDataFormat = df;
+ return;
+ }
+
+ const auto transpose = getDataFormatTranspose(dataFormat(), df);
+
+ if (mImpl) {
+ copyTranspose(*this, transpose);
+ } else {
+ std::vector<DimSize_t> newDims;
+ newDims.reserve(nbDims());
+ for (std::size_t i = 0; i < nbDims(); ++i) {
+ newDims.push_back(dims()[transpose[i]]);
+ }
+ mDims = std::move(newDims);
+
+ std::vector<std::size_t> newStrides(nbDims(), 1);
+ for (size_t i = 0; i < nbDims(); ++i) {
+ for (size_t j = i + 1; j < nbDims(); ++j) {
+ newStrides[i] *= newDims[j];
+ }
+ }
+ mStrides = std::move(newStrides);
}
+
mDataFormat = df;
}
--
GitLab
From a9fbc969e6af0796e844c8ecd4525b751791334b Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Thu, 20 Feb 2025 11:56:56 +0100
Subject: [PATCH 5/7] setDataFormat fix, working without impl
---
include/aidge/data/Tensor.hpp | 32 +++++++++++++++++---------------
1 file changed, 17 insertions(+), 15 deletions(-)
diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 5e4a817bb..5c184e961 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -452,19 +452,23 @@ public:
}
/**
- * @brief Set the DataType of the Tensor and converts data
- * if the Tensor has already been initialized and copyCast is true.
- * @param dt DataType
- * @param copyCast If true (default), previous data is copy-casted. Otherwise
- * previous data is lost.
+ * @brief Set the DataFormat of the Tensor and transpose data, only
+ * if the Tensor has already been initialized and copyTrans is true.
+ * In this case, a transposition occurs only if both previous format and
+ * new format are different from DataFormat::Default.
+ * @param df New DataFormat
+ * @param copyTrans If true (default), when both previous format and new
+ * format are different from DataFormat::Default, previous
+ * data is copy-transposed.
*/
void setDataFormat(const DataFormat df, bool copyTrans = true) {
if (!copyTrans || df == dataFormat()) {
mDataFormat = df;
return;
}
- // Skip transformation if both formats are Default or NNCH
- if ((df == DataFormat::Default && dataFormat() == DataFormat::Default) || df == DataFormat::NCHW && dataFormat() == DataFormat::NCHW) {
+
+ if ((df == DataFormat::Default && dataFormat() == DataFormat::Default) ||
+ (df == DataFormat::NCHW && dataFormat() == DataFormat::NCHW)) {
mDataFormat = df;
return;
}
@@ -475,24 +479,22 @@ public:
copyTranspose(*this, transpose);
} else {
std::vector<DimSize_t> newDims;
- newDims.reserve(nbDims());
- for (std::size_t i = 0; i < nbDims(); ++i) {
+ for (std::size_t i = 0; i < dims().size(); ++i) {
newDims.push_back(dims()[transpose[i]]);
}
- mDims = std::move(newDims);
-
- std::vector<std::size_t> newStrides(nbDims(), 1);
- for (size_t i = 0; i < nbDims(); ++i) {
- for (size_t j = i + 1; j < nbDims(); ++j) {
+
+ std::vector<std::size_t> newStrides(dims().size(), 1);
+ for (size_t i = 0; i < dims().size(); ++i) {
+ for (size_t j = i + 1; j < dims().size(); ++j) {
newStrides[i] *= newDims[j];
}
}
+ mDims = std::move(newDims);
mStrides = std::move(newStrides);
}
mDataFormat = df;
}
-
/**
* @brief Get the Impl object
* @return constexpr const std::shared_ptr<TensorImpl>&
--
GitLab
From a442b39c0cc45b83a4880c5be66742695aa3ffc1 Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Thu, 20 Feb 2025 15:37:16 +0100
Subject: [PATCH 6/7] New tests
---
unit_tests/operator/Test_Conv_Op.cpp | 130 +++++++++++++++++++--------
1 file changed, 95 insertions(+), 35 deletions(-)
diff --git a/unit_tests/operator/Test_Conv_Op.cpp b/unit_tests/operator/Test_Conv_Op.cpp
index 103b8c624..002e52522 100644
--- a/unit_tests/operator/Test_Conv_Op.cpp
+++ b/unit_tests/operator/Test_Conv_Op.cpp
@@ -42,66 +42,126 @@ TEST_CASE("[core/operator] Conv_Op(ForwardDims) ", "[Operator][ForwardDims][Conv
REQUIRE(conv1.forwardDims());
REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
}
-
- SECTION("I:NCHW O:NHWC W:NCHW") {
- std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,3,224,450}));
- std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4}));
-
- const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+ SECTION("I:NCHW O:NCHW W:NHWC") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16, 3, 224, 450}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4, 3, 3, 4})); // Out_ch, H, W, In_ch
+
+ const std::vector<std::size_t> expectedOutputDims({16, 4, 222, 447});
auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // Set DataFormat
- conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
+
+ // Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
input->setDataFormat(Aidge::DataFormat::NCHW);
- weight->setDataFormat(Aidge::DataFormat::NCHW);
-
+ weight->setDataFormat(Aidge::DataFormat::NHWC); // NHWC weight format
+
// Set inputs
conv1.setInput(1, weight);
conv1.setInput(0, input);
-
+
REQUIRE(conv1.forwardDims());
REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
}
-
- SECTION("I:NHWC O:NCHW W:NHWC") {
- std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
- std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,4,3,3})); // H, W, In_ch, Out_ch
-
- const std::vector<std::size_t> expectedOutputDims({16,4,222,447});
+
+ SECTION("I:NHWC O:NHWC W:NCHW") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16, 3, 224, 450}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4, 3, 3, 4})); // Out_ch, In_ch, H, W
+
+ const std::vector<std::size_t> expectedOutputDims({16, 222, 447, 4});
auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // Set DataFormat
- conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
+
+ // Set DataFormat
+ conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
input->setDataFormat(Aidge::DataFormat::NHWC);
- weight->setDataFormat(Aidge::DataFormat::NHWC);
-
+ weight->setDataFormat(Aidge::DataFormat::NCHW); // NCHW weight format
+
// Set inputs
conv1.setInput(1, weight);
conv1.setInput(0, input);
-
+
REQUIRE(conv1.forwardDims());
REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
}
-
- SECTION("I:NHWC O:NHWC W:NCHW") {
- std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
- std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4})); // Out_ch, In_ch, H, W
-
- const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+
+ SECTION("I:NHWC O:NHWC W:NHWC") {
+ std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16, 3,224, 450}));
+ std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4, 3, 3, 4})); // (Out_ch, H, W, In_ch)
+
+ const std::vector<std::size_t> expectedOutputDims({16, 222, 447, 4});
auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // Set DataFormat
+
+ // Set DataFormat
conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
input->setDataFormat(Aidge::DataFormat::NHWC);
- weight->setDataFormat(Aidge::DataFormat::NCHW);
-
+ weight->setDataFormat(Aidge::DataFormat::NHWC);
+
// Set inputs
conv1.setInput(1, weight);
conv1.setInput(0, input);
-
+
REQUIRE(conv1.forwardDims());
REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
}
+
+
+ // SECTION("I:NCHW O:NHWC W:NCHW") {
+ // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,3,224,450}));
+ // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4}));
+
+ // const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+ // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // // Set DataFormat
+ // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
+ // input->setDataFormat(Aidge::DataFormat::NCHW);
+ // weight->setDataFormat(Aidge::DataFormat::NCHW);
+
+ // // Set inputs
+ // conv1.setInput(1, weight);
+ // conv1.setInput(0, input);
+
+ // REQUIRE(conv1.forwardDims());
+ // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ // }
+
+ // SECTION("I:NHWC O:NCHW W:NHWC") {
+ // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
+ // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,4,3,3})); // H, W, In_ch, Out_ch
+
+ // const std::vector<std::size_t> expectedOutputDims({16,4,222,447});
+ // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // // Set DataFormat
+ // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
+ // input->setDataFormat(Aidge::DataFormat::NHWC);
+ // weight->setDataFormat(Aidge::DataFormat::NHWC);
+
+ // // Set inputs
+ // conv1.setInput(1, weight);
+ // conv1.setInput(0, input);
+
+ // REQUIRE(conv1.forwardDims());
+ // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ // }
+
+ // SECTION("I:NHWC O:NHWC W:NCHW") {
+ // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
+ // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4})); // Out_ch, In_ch, H, W
+
+ // const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
+ // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
+
+ // // Set DataFormat
+ // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
+ // input->setDataFormat(Aidge::DataFormat::NHWC);
+ // weight->setDataFormat(Aidge::DataFormat::NCHW);
+
+ // // Set inputs
+ // conv1.setInput(1, weight);
+ // conv1.setInput(0, input);
+
+ // REQUIRE(conv1.forwardDims());
+ // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
+ // }
}
--
GitLab
From 7c87a79d712a4b15c8253c2b5e71fef377f95789 Mon Sep 17 00:00:00 2001
From: Wissam Boussella <wissam.boussella@cea.fr>
Date: Thu, 20 Feb 2025 16:18:10 +0100
Subject: [PATCH 7/7] remove redendency in setDataFormat deleting old tests
---
include/aidge/data/Tensor.hpp | 6 ---
unit_tests/operator/Test_Conv_Op.cpp | 61 ----------------------------
2 files changed, 67 deletions(-)
diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 5c184e961..785caaa0e 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -467,12 +467,6 @@ public:
return;
}
- if ((df == DataFormat::Default && dataFormat() == DataFormat::Default) ||
- (df == DataFormat::NCHW && dataFormat() == DataFormat::NCHW)) {
- mDataFormat = df;
- return;
- }
-
const auto transpose = getDataFormatTranspose(dataFormat(), df);
if (mImpl) {
diff --git a/unit_tests/operator/Test_Conv_Op.cpp b/unit_tests/operator/Test_Conv_Op.cpp
index 002e52522..de33ddd5a 100644
--- a/unit_tests/operator/Test_Conv_Op.cpp
+++ b/unit_tests/operator/Test_Conv_Op.cpp
@@ -101,67 +101,6 @@ TEST_CASE("[core/operator] Conv_Op(ForwardDims) ", "[Operator][ForwardDims][Conv
REQUIRE(conv1.forwardDims());
REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
}
-
-
- // SECTION("I:NCHW O:NHWC W:NCHW") {
- // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,3,224,450}));
- // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4}));
-
- // const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
- // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // // Set DataFormat
- // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
- // input->setDataFormat(Aidge::DataFormat::NCHW);
- // weight->setDataFormat(Aidge::DataFormat::NCHW);
-
- // // Set inputs
- // conv1.setInput(1, weight);
- // conv1.setInput(0, input);
-
- // REQUIRE(conv1.forwardDims());
- // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
- // }
-
- // SECTION("I:NHWC O:NCHW W:NHWC") {
- // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
- // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,4,3,3})); // H, W, In_ch, Out_ch
-
- // const std::vector<std::size_t> expectedOutputDims({16,4,222,447});
- // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // // Set DataFormat
- // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NCHW);
- // input->setDataFormat(Aidge::DataFormat::NHWC);
- // weight->setDataFormat(Aidge::DataFormat::NHWC);
-
- // // Set inputs
- // conv1.setInput(1, weight);
- // conv1.setInput(0, input);
-
- // REQUIRE(conv1.forwardDims());
- // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
- // }
-
- // SECTION("I:NHWC O:NHWC W:NCHW") {
- // std::shared_ptr<Tensor> input = std::make_shared<Tensor>(std::vector<std::size_t>({16,224,450,3}));
- // std::shared_ptr<Tensor> weight = std::make_shared<Tensor>(std::vector<std::size_t>({4,3,3,4})); // Out_ch, In_ch, H, W
-
- // const std::vector<std::size_t> expectedOutputDims({16,222,447,4});
- // auto conv1 = Conv_Op<2>(std::array<size_t, 2>{3, 4});
-
- // // Set DataFormat
- // conv1.getOutput(0)->setDataFormat(Aidge::DataFormat::NHWC);
- // input->setDataFormat(Aidge::DataFormat::NHWC);
- // weight->setDataFormat(Aidge::DataFormat::NCHW);
-
- // // Set inputs
- // conv1.setInput(1, weight);
- // conv1.setInput(0, input);
-
- // REQUIRE(conv1.forwardDims());
- // REQUIRE(conv1.getOutput(0)->dims() == expectedOutputDims);
- // }
}
--
GitLab