blob: a255f94b2ea9da704494eb2edd7ccd0568ce7984 [file] [log] [blame]
/*
* Copyright (c) Meta Platforms, Inc. and affiliates.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include <executorch/kernels/test/FunctionHeaderWrapper.h> // Declares the operator
#include <executorch/kernels/test/TestUtil.h>
#include <executorch/kernels/test/supported_features.h>
#include <executorch/runtime/core/exec_aten/exec_aten.h>
#include <executorch/runtime/core/exec_aten/testing_util/tensor_factory.h>
#include <executorch/runtime/core/exec_aten/testing_util/tensor_util.h>
#include <gtest/gtest.h>
using namespace ::testing;
using exec_aten::Scalar;
using exec_aten::ScalarType;
using exec_aten::Tensor;
using torch::executor::testing::SupportedFeatures;
using torch::executor::testing::TensorFactory;
class OpPixelShuffleOutTest : public OperatorTest {
protected:
Tensor& op_pixel_shuffle_out(
const Tensor& self,
int64_t upscale_factor,
Tensor& out) {
return torch::executor::aten::pixel_shuffle_outf(
context_, self, upscale_factor, out);
}
template <ScalarType DTYPE_IN>
void test_pixel_shuffle() {
TensorFactory<DTYPE_IN> tf_in;
const std::vector<int32_t> sizes = {1, 4, 2, 2};
const std::vector<int32_t> out_sizes = {1, 1, 4, 4};
// Destination for the pixel_shuffle.
Tensor out = tf_in.zeros(out_sizes);
op_pixel_shuffle_out(
tf_in.make(
sizes, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}),
2,
out);
EXPECT_TENSOR_EQ(
out,
// Pixel shuffle distributes channels amongst the spatial dimensions.
tf_in.make(
out_sizes, {0, 4, 1, 5, 8, 12, 9, 13, 2, 6, 3, 7, 10, 14, 11, 15}));
}
};
//
// Correctness Tests
//
/**
* Uses the function templates above to test all input dtypes.
*/
TEST_F(OpPixelShuffleOutTest, AllRealDtypesSupported) {
#define ENUMERATE_TEST_ENTRY(ctype, dtype) \
test_pixel_shuffle<ScalarType::dtype>();
ET_FORALL_REAL_TYPES(ENUMERATE_TEST_ENTRY)
#undef ENUMERATE_TEST_ENTRY
}
TEST_F(OpPixelShuffleOutTest, LargerInputRank) {
TensorFactory<ScalarType::Int> tf;
// Pixel shuffle allows a 3D (or higher) input tensor, make sure the extra
// dimensions don't cause issues.
Tensor a = tf.ones(/*sizes=*/{1, 4, 1, 4, 2, 2});
const std::vector<int32_t> out_sizes = {1, 4, 1, 1, 4, 4};
Tensor out = tf.zeros(out_sizes);
op_pixel_shuffle_out(a, 2, out);
EXPECT_TENSOR_EQ(out, tf.ones(out_sizes));
}
// Mismatched shape tests.
TEST_F(OpPixelShuffleOutTest, InvalidInputChannelsDies) {
TensorFactory<ScalarType::Int> tf;
// Input tensors with invalid shapes. 7 is not divisible by upsample_factor
// ** 2.
Tensor a = tf.ones(/*sizes=*/{1, 7, 4, 4});
Tensor out = tf.zeros(/*sizes=*/{1, 1, 8, 8});
// Using the wrong input shape should exit with an error code.
ET_EXPECT_KERNEL_FAILURE(context_, op_pixel_shuffle_out(a, 2, out));
}
TEST_F(OpPixelShuffleOutTest, WrongInputRankDies) {
TensorFactory<ScalarType::Int> tf;
// Pixel shuffle requires a 3D or higher input tensor.
Tensor a = tf.ones(/*sizes=*/{1, 2});
Tensor out = tf.zeros(/*sizes=*/{1, 2});
// Using the wrong input shape should exit with an error code.
ET_EXPECT_KERNEL_FAILURE(context_, op_pixel_shuffle_out(a, 2, out));
}
TEST_F(OpPixelShuffleOutTest, DifferentDtypeDies) {
TensorFactory<ScalarType::Int> tf;
TensorFactory<ScalarType::Float> tf_float;
Tensor a = tf.ones(/*sizes=*/{1, 18, 4, 4});
// Pixel shuffle requires two tensors with the same dtype.
Tensor out = tf_float.zeros(/*sizes=*/{1, 2, 12, 12});
// Using the wrong output shape should exit with an error code.
ET_EXPECT_KERNEL_FAILURE(context_, op_pixel_shuffle_out(a, 3, out));
}
TEST_F(OpPixelShuffleOutTest, NegativeUpscaleFactorDies) {
TensorFactory<ScalarType::Int> tf;
Tensor a = tf.ones(/*sizes=*/{1, 18, 4, 4});
Tensor out = tf.zeros(/*sizes=*/{1, 2, 12, 12});
// Using a negative upscale factor should exit with an error code.
ET_EXPECT_KERNEL_FAILURE(context_, op_pixel_shuffle_out(a, -3, out));
}