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authorGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-10-08 19:12:44 +0000
committerGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-10-08 19:12:44 +0000
commit5266ff8966c072defd5bfcfa74c1892fc500943b (patch)
tree5764fac42ae0e5957aac9f74ec3b0a51f04400e4 /unsupported/test/cxx11_tensor_argmax_cuda.cu
parent4860727ac2f404bddd23ba60896bc1288f0de06c (diff)
Cleaned up a regression test
Diffstat (limited to 'unsupported/test/cxx11_tensor_argmax_cuda.cu')
-rw-r--r--unsupported/test/cxx11_tensor_argmax_cuda.cu14
1 files changed, 7 insertions, 7 deletions
diff --git a/unsupported/test/cxx11_tensor_argmax_cuda.cu b/unsupported/test/cxx11_tensor_argmax_cuda.cu
index 6fe8982f2..653443dc5 100644
--- a/unsupported/test/cxx11_tensor_argmax_cuda.cu
+++ b/unsupported/test/cxx11_tensor_argmax_cuda.cu
@@ -116,10 +116,10 @@ void test_cuda_argmax_dim()
assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
- VERIFY_IS_EQUAL(tensor_arg.dimensions().TotalSize(),
+ VERIFY_IS_EQUAL(tensor_arg.size(),
size_t(2*3*5*7 / tensor.dimension(dim)));
- for (size_t n = 0; n < tensor_arg.dimensions().TotalSize(); ++n) {
+ for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
// Expect max to be in the first index of the reduced dimension
VERIFY_IS_EQUAL(tensor_arg.data()[n], 0);
}
@@ -144,7 +144,7 @@ void test_cuda_argmax_dim()
assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
- for (size_t n = 0; n < tensor_arg.dimensions().TotalSize(); ++n) {
+ for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
// Expect max to be in the last index of the reduced dimension
VERIFY_IS_EQUAL(tensor_arg.data()[n], tensor.dimension(dim) - 1);
}
@@ -205,10 +205,10 @@ void test_cuda_argmin_dim()
assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
- VERIFY_IS_EQUAL(tensor_arg.dimensions().TotalSize(),
- size_t(2*3*5*7 / tensor.dimension(dim)));
+ VERIFY_IS_EQUAL(tensor_arg.size(),
+ 2*3*5*7 / tensor.dimension(dim));
- for (size_t n = 0; n < tensor_arg.dimensions().TotalSize(); ++n) {
+ for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
// Expect min to be in the first index of the reduced dimension
VERIFY_IS_EQUAL(tensor_arg.data()[n], 0);
}
@@ -233,7 +233,7 @@ void test_cuda_argmin_dim()
assert(cudaMemcpyAsync(tensor_arg.data(), d_out, out_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
- for (size_t n = 0; n < tensor_arg.dimensions().TotalSize(); ++n) {
+ for (DenseIndex n = 0; n < tensor_arg.size(); ++n) {
// Expect max to be in the last index of the reduced dimension
VERIFY_IS_EQUAL(tensor_arg.data()[n], tensor.dimension(dim) - 1);
}