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Updated the regressions tests that cover full reductions

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This commit is contained in:
Benoit Steiner
2015-11-05 14:22:30 -08:00
parent c75a19f815
commit 0d15ad8019
6 changed files with 102 additions and 58 deletions
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16
unsupported/test/cxx11_tensor_argmax.cpp
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@@ -61,14 +61,14 @@ static void test_argmax_tuple_reducer()
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
index_tuples = tensor.index_tuples();
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced(1);
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce(
dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float>>());
Tensor<float, 1, DataLayout> maxi = tensor.maximum();
Tensor<float, 0, DataLayout> maxi = tensor.maximum();
VERIFY_IS_EQUAL(maxi(0), reduced(0).second);
VERIFY_IS_EQUAL(maxi(), reduced(0).second);
array<DenseIndex, 3> reduce_dims;
for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
@@ -93,14 +93,14 @@ static void test_argmin_tuple_reducer()
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
index_tuples = tensor.index_tuples();
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced(1);
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce(
dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float>>());
Tensor<float, 1, DataLayout> mini = tensor.minimum();
Tensor<float, 0, DataLayout> mini = tensor.minimum();
VERIFY_IS_EQUAL(mini(0), reduced(0).second);
VERIFY_IS_EQUAL(mini(), reduced(0).second);
array<DenseIndex, 3> reduce_dims;
for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
@@ -123,7 +123,7 @@ static void test_simple_argmax()
tensor = (tensor + tensor.constant(0.5)).log();
tensor(0,0,0,0) = 10.0;
Tensor<DenseIndex, 1, DataLayout> tensor_argmax(1);
Tensor<DenseIndex, 0, DataLayout> tensor_argmax;
tensor_argmax = tensor.argmax();
@@ -144,7 +144,7 @@ static void test_simple_argmin()
tensor = (tensor + tensor.constant(0.5)).log();
tensor(0,0,0,0) = -10.0;
Tensor<DenseIndex, 1, DataLayout> tensor_argmin(1);
Tensor<DenseIndex, 0, DataLayout> tensor_argmin;
tensor_argmin = tensor.argmin();