diff options
Diffstat (limited to 'tests/validation/fixtures/RNNLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/RNNLayerFixture.h | 32 |
1 files changed, 17 insertions, 15 deletions
diff --git a/tests/validation/fixtures/RNNLayerFixture.h b/tests/validation/fixtures/RNNLayerFixture.h index 1668e94cf0..e9a05e7838 100644 --- a/tests/validation/fixtures/RNNLayerFixture.h +++ b/tests/validation/fixtures/RNNLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 Arm Limited. + * Copyright (c) 2018-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -42,7 +42,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class RNNLayerValidationFixture : public framework::Fixture { public: - template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape recurrent_weights_shape, TensorShape bias_shape, TensorShape output_shape, ActivationLayerInfo info, DataType data_type) { @@ -54,7 +53,10 @@ protected: template <typename U> void fill(U &&tensor, int i) { - std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + static_assert(std::is_floating_point<T>::value || std::is_same<T, half>::value, "Only floating point data types supported."); + using DistributionType = typename std::conditional<std::is_same<T, half>::value, arm_compute::utils::uniform_real_distribution_16bit<T>, std::uniform_real_distribution<T>>::type; + + DistributionType distribution{ T(-1.0f), T(1.0f) }; library->fill(tensor, distribution, i); } @@ -73,12 +75,12 @@ protected: FunctionType rnn; rnn.configure(&input, &weights, &recurrent_weights, &bias, &hidden_state, &output, info); - ARM_COMPUTE_EXPECT(input.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(recurrent_weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(hidden_state.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(output.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(input.info()->is_resizable()); + ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); + ARM_COMPUTE_ASSERT(recurrent_weights.info()->is_resizable()); + ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); + ARM_COMPUTE_ASSERT(hidden_state.info()->is_resizable()); + ARM_COMPUTE_ASSERT(output.info()->is_resizable()); // Allocate tensors input.allocator()->allocate(); @@ -88,12 +90,12 @@ protected: hidden_state.allocator()->allocate(); output.allocator()->allocate(); - ARM_COMPUTE_EXPECT(!input.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!recurrent_weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!hidden_state.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!output.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(!input.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!weights.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!recurrent_weights.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!bias.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!hidden_state.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!output.info()->is_resizable()); // Fill tensors fill(AccessorType(input), 0); |