diff options
30 files changed, 496 insertions, 96 deletions
diff --git a/arm_compute/core/CL/kernels/CLActivationLayerKernel.h b/arm_compute/core/CL/kernels/CLActivationLayerKernel.h index dab133f05a..30bf6fb0d6 100644 --- a/arm_compute/core/CL/kernels/CLActivationLayerKernel.h +++ b/arm_compute/core/CL/kernels/CLActivationLayerKernel.h @@ -56,6 +56,16 @@ public: * @param[in] act_info Activation layer information. */ void configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info); + /** Static function to check if given info will lead to a valid configuration of @ref CLActivationLayerKernel + * + * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result + * of the activation function. Data types supported: QS8/QS16/F16/F32. + * @param[in] output Destination tensor info. Data type supported: same as @p input + * @param[in] act_info Activation layer information. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h index 0895fe3f79..aa4b9d6c5f 100644 --- a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h +++ b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h @@ -59,6 +59,16 @@ public: * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticAdditionKernel + * + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] policy Policy to use to handle overflow. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h b/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h index d7755d5e31..13136d93e0 100644 --- a/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h +++ b/arm_compute/core/CL/kernels/CLArithmeticSubtractionKernel.h @@ -61,6 +61,16 @@ public: * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticSubtractionKernel + * + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] policy Policy to use to handle overflow. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h index 26825efba9..a24432145a 100644 --- a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h +++ b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h @@ -63,6 +63,24 @@ public: * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input */ void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon); + /** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayerKernel + * + * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result. + * 3 lower dimensions represent a single input with dimensions [width, height, FM]. + * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input + * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. + * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] epsilon Small value to avoid division with zero. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h b/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h index 309a202df3..ed876df06f 100644 --- a/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h +++ b/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h @@ -59,6 +59,20 @@ public: */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLPixelWiseMultiplicationKernel + * + * @param[in] input1 An input tensor info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 An input tensor info. Data types supported: same as @p input1. + * @param[in] output The output tensor info, Data types supported: same as @p input1. Note: U8 (QS8, QS16) requires both inputs to be U8 (QS8, QS16). + * @param[in] scale Scale to apply after multiplication. + * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. For QS8 and QS16 scale must be 1. + * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate + * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h b/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h index 29190e2dd1..a9159a4bb8 100644 --- a/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h +++ b/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h @@ -60,11 +60,11 @@ public: void configure(const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info); /** Static function to check if given info will lead to a valid configuration of @ref CLPoolingLayerKernel * - * @param[in] input Input's tensor info - * @param[in] output Output's tensor info + * @param[in] input Source tensor info. Data types supported: QS8/QS16/F16/F32. + * @param[in] output Destination tensor info. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref PoolingLayerInfo. * - * @return an error + * @return an error status */ static Error validate(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info); diff --git a/arm_compute/core/Error.h b/arm_compute/core/Error.h index 6e4aa6a4f8..fa3f9c0615 100644 --- a/arm_compute/core/Error.h +++ b/arm_compute/core/Error.h @@ -240,7 +240,7 @@ Error create_error(ErrorCode error_code, const char *function, const char *file, * * @param[in] error Error value to check. */ -#define ARM_COMPUTE_ERROR_THROW(error) \ +#define ARM_COMPUTE_ERROR_THROW_ON(error) \ error.throw_if_error(); /** If the condition is true, the given message is printed and an exception is thrown @@ -282,7 +282,7 @@ Error create_error(ErrorCode error_code, const char *function, const char *file, */ #define ARM_COMPUTE_CONST_ON_ERROR(cond, val, msg) (cond) ? throw std::logic_error(msg) : val; #else /* ARM_COMPUTE_ASSERTS_ENABLED */ -#define ARM_COMPUTE_ERROR_THROW(error) +#define ARM_COMPUTE_ERROR_THROW_ON(error) #define ARM_COMPUTE_ERROR_ON_MSG(cond, ...) #define ARM_COMPUTE_ERROR_ON_LOC_MSG(cond, func, file, line, ...) #define ARM_COMPUTE_CONST_ON_ERROR(cond, val, msg) val diff --git a/arm_compute/core/Validate.h b/arm_compute/core/Validate.h index 1e2d262683..2ca9f6b64e 100644 --- a/arm_compute/core/Validate.h +++ b/arm_compute/core/Validate.h @@ -142,7 +142,7 @@ inline arm_compute::Error error_on_nullptr(const char *function, const char *fil return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_NULLPTR(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_nullptr(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_nullptr(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_nullptr(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -164,7 +164,7 @@ inline arm_compute::Error error_on_nullptr(const char *function, const char *fil arm_compute::Error error_on_mismatching_windows(const char *function, const char *file, const int line, const Window &full, const Window &win); #define ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(f, w) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_windows(__func__, __FILE__, __LINE__, f, w)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_windows(__func__, __FILE__, __LINE__, f, w)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_WINDOWS(f, w) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_windows(__func__, __FILE__, __LINE__, f, w)) @@ -186,7 +186,7 @@ arm_compute::Error error_on_mismatching_windows(const char *function, const char arm_compute::Error error_on_invalid_subwindow(const char *function, const char *file, const int line, const Window &full, const Window &sub); #define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_invalid_subwindow(__func__, __FILE__, __LINE__, f, s)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_invalid_subwindow(__func__, __FILE__, __LINE__, f, s)) #define ARM_COMPUTE_RETURN_ERROR_ON_INVALID_SUBWINDOW(f, s) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_invalid_subwindow(__func__, __FILE__, __LINE__, f, s)) @@ -206,7 +206,7 @@ arm_compute::Error error_on_invalid_subwindow(const char *function, const char * arm_compute::Error error_on_window_not_collapsable_at_dimension(const char *function, const char *file, const int line, const Window &full, const Window &window, const int dim); #define ARM_COMPUTE_ERROR_ON_WINDOW_NOT_COLLAPSABLE_AT_DIMENSION(f, w, d) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_window_not_collapsable_at_dimension(__func__, __FILE__, __LINE__, f, w, d)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_window_not_collapsable_at_dimension(__func__, __FILE__, __LINE__, f, w, d)) #define ARM_COMPUTE_RETURN_ERROR_ON_WINDOW_NOT_COLLAPSABLE_AT_DIMENSION(f, w, d) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_window_not_collapsable_at_dimension(__func__, __FILE__, __LINE__, f, w, d)) @@ -225,7 +225,7 @@ arm_compute::Error error_on_window_not_collapsable_at_dimension(const char *func arm_compute::Error error_on_coordinates_dimensions_gte(const char *function, const char *file, const int line, const Coordinates &pos, unsigned int max_dim); #define ARM_COMPUTE_ERROR_ON_COORDINATES_DIMENSIONS_GTE(p, md) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_coordinates_dimensions_gte(__func__, __FILE__, __LINE__, p, md)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_coordinates_dimensions_gte(__func__, __FILE__, __LINE__, p, md)) #define ARM_COMPUTE_RETURN_ERROR_ON_COORDINATES_DIMENSIONS_GTE(p, md) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_coordinates_dimensions_gte(__func__, __FILE__, __LINE__, p, md)) @@ -244,7 +244,7 @@ arm_compute::Error error_on_coordinates_dimensions_gte(const char *function, con arm_compute::Error error_on_window_dimensions_gte(const char *function, const char *file, const int line, const Window &win, unsigned int max_dim); #define ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE(w, md) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_window_dimensions_gte(__func__, __FILE__, __LINE__, w, md)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_window_dimensions_gte(__func__, __FILE__, __LINE__, w, md)) #define ARM_COMPUTE_RETURN_ERROR_ON_WINDOW_DIMENSIONS_GTE(w, md) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_window_dimensions_gte(__func__, __FILE__, __LINE__, w, md)) @@ -267,7 +267,7 @@ arm_compute::Error error_on_mismatching_dimensions(const char *function, const c return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_dimensions(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_dimensions(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_dimensions(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -357,7 +357,7 @@ inline arm_compute::Error error_on_mismatching_shapes(const char *function, cons return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_shapes(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_shapes(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_shapes(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -408,7 +408,7 @@ inline arm_compute::Error error_on_mismatching_data_types(const char *function, return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_data_types(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_data_types(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_data_types(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -432,7 +432,7 @@ inline arm_compute::Error error_on_mismatching_fixed_point(const char *function, DataType &&first_data_type = tensor_info_1->data_type(); const int first_fixed_point_position = tensor_info_1->fixed_point_position(); - if((first_data_type != DataType::QS8) && (first_data_type != DataType::QS16)) + if(!is_data_type_fixed_point(first_data_type)) { return arm_compute::Error{}; } @@ -473,7 +473,7 @@ inline arm_compute::Error error_on_mismatching_fixed_point(const char *function, return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -556,7 +556,7 @@ inline arm_compute::Error error_on_data_type_not_in(const char *function, const return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(t, ...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_data_type_not_in(__func__, __FILE__, __LINE__, t, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_data_type_not_in(__func__, __FILE__, __LINE__, t, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(t, ...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_data_type_not_in(__func__, __FILE__, __LINE__, t, __VA_ARGS__)) @@ -602,7 +602,7 @@ inline arm_compute::Error error_on_data_type_channel_not_in(const char *function return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c, ...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_data_type_channel_not_in(__func__, __FILE__, __LINE__, t, c, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_data_type_channel_not_in(__func__, __FILE__, __LINE__, t, c, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c, ...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_data_type_channel_not_in(__func__, __FILE__, __LINE__, t, c, __VA_ARGS__)) @@ -618,7 +618,7 @@ inline arm_compute::Error error_on_data_type_channel_not_in(const char *function arm_compute::Error error_on_tensor_not_2d(const char *function, const char *file, const int line, const ITensor *tensor); #define ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(t) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_tensor_not_2d(__func__, __FILE__, __LINE__, t)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_tensor_not_2d(__func__, __FILE__, __LINE__, t)) #define ARM_COMPUTE_RETURN_ERROR_ON_TENSOR_NOT_2D(t) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_tensor_not_2d(__func__, __FILE__, __LINE__, t)) @@ -648,7 +648,7 @@ inline arm_compute::Error error_on_channel_not_in(const char *function, const ch return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_CHANNEL_NOT_IN(c, ...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_channel_not_in(__func__, __FILE__, __LINE__, c, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_channel_not_in(__func__, __FILE__, __LINE__, c, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_CHANNEL_NOT_IN(c, ...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_channel_not_in(__func__, __FILE__, __LINE__, c, __VA_ARGS__)) @@ -665,7 +665,7 @@ inline arm_compute::Error error_on_channel_not_in(const char *function, const ch arm_compute::Error error_on_channel_not_in_known_format(const char *function, const char *file, const int line, Format fmt, Channel cn); #define ARM_COMPUTE_ERROR_ON_CHANNEL_NOT_IN_KNOWN_FORMAT(f, c) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_channel_not_in_known_format(__func__, __FILE__, __LINE__, f, c)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_channel_not_in_known_format(__func__, __FILE__, __LINE__, f, c)) #define ARM_COMPUTE_RETURN_ERROR_ON_CHANNEL_NOT_IN_KNOWN_FORMAT(f, c) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_channel_not_in_known_format(__func__, __FILE__, __LINE__, f, c)) @@ -687,7 +687,7 @@ arm_compute::Error error_on_channel_not_in_known_format(const char *function, co arm_compute::Error error_on_invalid_multi_hog(const char *function, const char *file, const int line, const IMultiHOG *multi_hog); #define ARM_COMPUTE_ERROR_ON_INVALID_MULTI_HOG(m) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_invalid_multi_hog(__func__, __FILE__, __LINE__, m)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_invalid_multi_hog(__func__, __FILE__, __LINE__, m)) #define ARM_COMPUTE_RETURN_ERROR_ON_INVALID_MULTI_HOG(m) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_invalid_multi_hog(__func__, __FILE__, __LINE__, m)) @@ -701,7 +701,7 @@ arm_compute::Error error_on_invalid_multi_hog(const char *function, const char * arm_compute::Error error_on_unconfigured_kernel(const char *function, const char *file, const int line, const IKernel *kernel); #define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_unconfigured_kernel(__func__, __FILE__, __LINE__, k)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_unconfigured_kernel(__func__, __FILE__, __LINE__, k)) #define ARM_COMPUTE_RETURN_ERROR_ON_UNCONFIGURED_KERNEL(k) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_unconfigured_kernel(__func__, __FILE__, __LINE__, k)) @@ -719,7 +719,7 @@ arm_compute::Error error_on_unconfigured_kernel(const char *function, const char arm_compute::Error error_on_invalid_subtensor(const char *function, const char *file, const int line, const TensorShape &parent_shape, const Coordinates &coords, const TensorShape &shape); #define ARM_COMPUTE_ERROR_ON_INVALID_SUBTENSOR(p, c, s) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_invalid_subtensor(__func__, __FILE__, __LINE__, p, c, s)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_invalid_subtensor(__func__, __FILE__, __LINE__, p, c, s)) #define ARM_COMPUTE_RETURN_ERROR_ON_INVALID_SUBTENSOR(p, c, s) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_invalid_subtensor(__func__, __FILE__, __LINE__, p, c, s)) @@ -736,7 +736,7 @@ arm_compute::Error error_on_invalid_subtensor(const char *function, const char * arm_compute::Error error_on_invalid_subtensor_valid_region(const char *function, const char *file, const int line, const ValidRegion &parent_valid_region, const ValidRegion &valid_region); #define ARM_COMPUTE_ERROR_ON_INVALID_SUBTENSOR_VALID_REGION(pv, sv) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_invalid_subtensor_valid_region(__func__, __FILE__, __LINE__, pv, sv)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_invalid_subtensor_valid_region(__func__, __FILE__, __LINE__, pv, sv)) #define ARM_COMPUTE_RETURN_ERROR_ON_INVALID_SUBTENSOR_VALID_REGION(pv, sv) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_invalid_subtensor_valid_region(__func__, __FILE__, __LINE__, pv, sv)) @@ -783,7 +783,7 @@ inline arm_compute::Error error_on_mismatching_fixed_point_position(const char * return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_mismatching_fixed_point_position(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_mismatching_fixed_point_position(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_mismatching_fixed_point_position(__func__, __FILE__, __LINE__, __VA_ARGS__)) @@ -827,7 +827,7 @@ inline arm_compute::Error error_on_value_not_representable_in_fixed_point(const return arm_compute::Error{}; } #define ARM_COMPUTE_ERROR_ON_VALUE_NOT_REPRESENTABLE_IN_FIXED_POINT(...) \ - ARM_COMPUTE_ERROR_THROW(::arm_compute::error_on_value_not_representable_in_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) + ARM_COMPUTE_ERROR_THROW_ON(::arm_compute::error_on_value_not_representable_in_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) #define ARM_COMPUTE_RETURN_ERROR_ON_VALUE_NOT_REPRESENTABLE_IN_FIXED_POINT(...) \ ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_value_not_representable_in_fixed_point(__func__, __FILE__, __LINE__, __VA_ARGS__)) } diff --git a/arm_compute/runtime/CL/functions/CLActivationLayer.h b/arm_compute/runtime/CL/functions/CLActivationLayer.h index a1aeb193d1..037ae71e7f 100644 --- a/arm_compute/runtime/CL/functions/CLActivationLayer.h +++ b/arm_compute/runtime/CL/functions/CLActivationLayer.h @@ -49,6 +49,16 @@ public: * @param[in] act_info Activation layer parameters. */ void configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info); + /** Static function to check if given info will lead to a valid configuration of @ref CLActivationLayer + * + * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result + * of the activation function. Data types supported: QS8/QS16/F16/F32. + * @param[in] output Destination tensor info. Data type supported: same as @p input + * @param[in] act_info Activation layer information. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info); }; } #endif /* __ARM_COMPUTE_CLACTIVATIONLAYER_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLArithmeticAddition.h b/arm_compute/runtime/CL/functions/CLArithmeticAddition.h index f888256b33..0c54147e6c 100644 --- a/arm_compute/runtime/CL/functions/CLArithmeticAddition.h +++ b/arm_compute/runtime/CL/functions/CLArithmeticAddition.h @@ -47,6 +47,16 @@ public: * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticAddition + * + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] policy Policy to use to handle overflow. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy); }; } #endif /* __ARM_COMPUTE_CLARITHMETICADDITION_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h b/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h index eedeaa8d0e..749f1b26b3 100644 --- a/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h +++ b/arm_compute/runtime/CL/functions/CLArithmeticSubtraction.h @@ -48,6 +48,16 @@ public: * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticSubtraction + * + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] policy Policy to use to handle overflow. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy); }; } #endif /* __ARM_COMPUTE_CLARITHMETICSUBTRACTION_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h index ffb66bee60..70a201a1f8 100644 --- a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h +++ b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h @@ -51,14 +51,32 @@ public: * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result. * 3 lower dimensions represent a single input with dimensions [width, height, FM]. * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. + * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] epsilon Small value to avoid division with zero. - * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input */ void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon); + /** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayer + * + * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result. + * 3 lower dimensions represent a single input with dimensions [width, height, FM]. + * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input + * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. + * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] epsilon Small value to avoid division with zero. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon); // Inherited methods overridden: void run() override; diff --git a/arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h b/arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h index 71754fc3f4..4fdcd750bd 100644 --- a/arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h +++ b/arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h @@ -37,15 +37,30 @@ class CLPixelWiseMultiplication : public ICLSimpleFunction public: /** Initialise the kernel's inputs, output and convertion policy. * - * @param[in] input1 First tensor input. Data types supported: U8, S16, F16 or F32. - * @param[in] input2 Second tensor input. Data types supported: U8, S16, F16 or F32. - * @param[out] output Output tensor. Data types supported: U8(Only if both inputs are U8), S16, F16 or F32. - * @param[in] scale Scale to apply after multiplication. Must be positive. + * @param[in] input1 An input tensor. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 An input tensor. Data types supported: same as @p input1. + * @param[out] output The output tensor, Data types supported: same as @p input1. Note: U8 (QS8, QS16) requires both inputs to be U8 (QS8, QS16). + * @param[in] scale Scale to apply after multiplication. + * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. For QS8 and QS16 scale must be 1. * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); + /** Static function to check if given info will lead to a valid configuration of @ref CLPixelWiseMultiplication + * + * @param[in] input1 An input tensor info. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in] input2 An input tensor info. Data types supported: same as @p input1. + * @param[in] output The output tensor info, Data types supported: same as @p input1. Note: U8 (QS8, QS16) requires both inputs to be U8 (QS8, QS16). + * @param[in] scale Scale to apply after multiplication. + * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. For QS8 and QS16 scale must be 1. + * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate + * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. + * + * @return an error status + */ + static Error validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); }; } #endif /*__ARM_COMPUTE_CLPIXELWISEMULTIPLICATION_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLPoolingLayer.h b/arm_compute/runtime/CL/functions/CLPoolingLayer.h index f7fd114be1..9c51534f78 100644 --- a/arm_compute/runtime/CL/functions/CLPoolingLayer.h +++ b/arm_compute/runtime/CL/functions/CLPoolingLayer.h @@ -50,11 +50,11 @@ public: void configure(ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info); /** Static function to check if given info will lead to a valid configuration of @ref CLPoolingLayer * - * @param[in] input Input's tensor info - * @param[in] output Output's tensor info + * @param[in] input Source tensor info. Data types supported: QS8/QS16/F16/F32. + * @param[in] output Destination tensor info. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref PoolingLayerInfo. * - * @return an expected value + * @return an error status */ static Error validate(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info); }; diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp index ca6760d8c2..5bfc832518 100644 --- a/src/core/CL/kernels/CLActivationLayerKernel.cpp +++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp @@ -50,12 +50,11 @@ CLActivationLayerKernel::CLActivationLayerKernel() void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32, DataType::QASYMM8); - ARM_COMPUTE_ERROR_ON_MSG((input->info()->data_type() == DataType::QASYMM8) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), - "For QASYMM8 only lower/upper bounded relu is supported"); + ARM_COMPUTE_ERROR_ON_NULLPTR(input); if(output != nullptr) { + ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), output->info()); // Output auto inizialitation if not yet initialized auto_init_if_empty(*output->info(), input->info()->tensor_shape(), @@ -63,12 +62,10 @@ void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, Act input->info()->data_type(), input->info()->fixed_point_position(), input->info()->quantization_info()); - - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); } + ARM_COMPUTE_ERROR_THROW_ON(CLActivationLayerKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, act_info)); + const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); const DataType dt = input->info()->data_type(); const int fixed_point_position = input->info()->fixed_point_position(); @@ -156,6 +153,23 @@ void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, Act ICLKernel::configure(win); } +Error CLActivationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((input->data_type() == DataType::QASYMM8) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), + "For QASYMM8 only lower/upper bounded relu is supported"); + + // Checks performed when output is configured + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + } + + return Error{}; +} + void CLActivationLayerKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); diff --git a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp index 65422c2bbf..a7625f4303 100644 --- a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp +++ b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp @@ -68,17 +68,7 @@ void CLArithmeticAdditionKernel::configure(const ICLTensor *input1, const ICLTen } } - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input1, input2, output); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_MSG(output->info()->data_type() == DataType::U8 && (input1->info()->data_type() != DataType::U8 || input2->info()->data_type() != DataType::U8), - "Output can only be U8 if both inputs are U8"); - if(is_data_type_fixed_point(input1->info()->data_type()) || is_data_type_fixed_point(input2->info()->data_type()) || is_data_type_fixed_point(output->info()->data_type())) - { - // Check that all data types are the same and all fixed-point positions are the same - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input1, input2, output); - } + ARM_COMPUTE_ERROR_THROW_ON(CLArithmeticAdditionKernel::validate(input1->info(), input2->info(), output->info(), policy)); _input1 = input1; _input2 = input2; @@ -119,6 +109,27 @@ void CLArithmeticAdditionKernel::configure(const ICLTensor *input1, const ICLTen ICLKernel::configure(win); } +Error CLArithmeticAdditionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +{ + ARM_COMPUTE_UNUSED(policy); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, input2); + + // Validate in case of configured output + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), + "Output can only be U8 if both inputs are U8"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, output); + } + + return Error{}; +} + void CLArithmeticAdditionKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); diff --git a/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp b/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp index c5183af7d7..47d77ad8a9 100644 --- a/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp +++ b/src/core/CL/kernels/CLArithmeticSubtractionKernel.cpp @@ -61,17 +61,7 @@ void CLArithmeticSubtractionKernel::configure(const ICLTensor *input1, const ICL } } - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input1, input2, output); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_MSG(output->info()->data_type() == DataType::U8 && (input1->info()->data_type() != DataType::U8 || input2->info()->data_type() != DataType::U8), - "Output can only be U8 if both inputs are U8"); - if(is_data_type_fixed_point(input1->info()->data_type()) || is_data_type_fixed_point(input2->info()->data_type()) || is_data_type_fixed_point(output->info()->data_type())) - { - // Check that all data types are the same and all fixed-point positions are the same - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input1, input2, output); - } + ARM_COMPUTE_ERROR_THROW_ON(CLArithmeticSubtractionKernel::validate(input1->info(), input2->info(), output->info(), policy)); _input1 = input1; _input2 = input2; @@ -111,6 +101,27 @@ void CLArithmeticSubtractionKernel::configure(const ICLTensor *input1, const ICL ICLKernel::configure(win); } +Error CLArithmeticSubtractionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +{ + ARM_COMPUTE_UNUSED(policy); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, input2); + + // Validate in case of configured output + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), + "Output can only be U8 if both inputs are U8"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, output); + } + + return Error{}; +} + void CLArithmeticSubtractionKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp index 43f39f423f..f17091166c 100644 --- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp +++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp @@ -45,7 +45,7 @@ CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var, beta, gamma); _input = input; _output = output; @@ -57,21 +57,13 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out if(output != nullptr) { + ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), output->info()); // Output tensor auto initialization if not yet initialized auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); - - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, mean, var, beta, gamma); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, mean, var, beta, gamma); - } - else - { - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var, beta, gamma); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var, beta, gamma); } - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); - ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != mean->info()->dimension(0)); + ARM_COMPUTE_ERROR_THROW_ON(CLBatchNormalizationLayerKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, + mean->info(), var->info(), beta->info(), gamma->info(), epsilon)); const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); @@ -108,6 +100,28 @@ void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *out ICLKernel::configure(win); } +Error CLBatchNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon) +{ + ARM_COMPUTE_UNUSED(epsilon); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var, beta, gamma); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var, beta, gamma); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != mean->dimension(0)); + + if(output != nullptr && output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + } + + return Error{}; +} + void CLBatchNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp index 33c8b81c1d..5e35c8c1ff 100644 --- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp +++ b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp @@ -64,20 +64,8 @@ void CLPixelWiseMultiplicationKernel::configure(const ICLTensor *input1, const I } } - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input1, input2, output); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_MSG(output->info()->data_type() == DataType::U8 && (input1->info()->data_type() != DataType::U8 || input2->info()->data_type() != DataType::U8), - "Output can only be U8 if both inputs are U8"); - ARM_COMPUTE_ERROR_ON_MSG(scale < 0, "Scale cannot be negative. "); - if(is_data_type_fixed_point(input1->info()->data_type())) - { - // All data types must be all QS8 or all QS16 - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input1, input2, output); - ARM_COMPUTE_ERROR_ON_MSG(scale != 1, "Unsupported scaling factor for QS8/QS16. Scale must be 1."); - } + ARM_COMPUTE_ERROR_THROW_ON(CLPixelWiseMultiplicationKernel::validate(input1->info(), input2->info(), output->info(), + scale, overflow_policy, rounding_policy)); _input1 = input1; _input2 = input2; @@ -178,6 +166,42 @@ void CLPixelWiseMultiplicationKernel::configure(const ICLTensor *input1, const I ICLKernel::configure(win); } +Error CLPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy) +{ + ARM_COMPUTE_UNUSED(overflow_policy); + ARM_COMPUTE_UNUSED(rounding_policy); + + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(scale < 0, "Scale cannot be negative."); + + if(is_data_type_fixed_point(input1->data_type())) + { + // All data types must be all QS8 or all QS16 + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(scale != 1, "Unsupported scaling factor for QS8/QS16. Scale must be 1."); + } + + // Validate in case of configured output + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), + "Output can only be U8 if both inputs are U8"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input1, output); + if(is_data_type_fixed_point(input1->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, output); + } + } + + return Error{}; +} + void CLPixelWiseMultiplicationKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp index 19d36a6ac6..2854cd8265 100644 --- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp +++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp @@ -65,9 +65,7 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad(); std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_ERROR_ON(pool_pad_x >= pool_size || pool_pad_y >= pool_size); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); // Check output dimensions std::tie(pooled_w, pooled_h) = scaled_dimensions(input->info()->dimension(0), @@ -85,9 +83,7 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); } - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); - ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pooled_w) || (output->info()->dimension(1) != pooled_h)); + ARM_COMPUTE_ERROR_THROW_ON(CLPoolingLayerKernel::validate(input->info(), output->info(), pool_info)); const int input_width = input->info()->dimension(0); const int input_height = input->info()->dimension(1); diff --git a/src/runtime/CL/functions/CLActivationLayer.cpp b/src/runtime/CL/functions/CLActivationLayer.cpp index fbb90d9a8b..5369a59211 100644 --- a/src/runtime/CL/functions/CLActivationLayer.cpp +++ b/src/runtime/CL/functions/CLActivationLayer.cpp @@ -35,3 +35,8 @@ void CLActivationLayer::configure(ICLTensor *input, ICLTensor *output, Activatio k->configure(input, output, act_info); _kernel = std::move(k); } + +Error CLActivationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info) +{ + return CLActivationLayerKernel::validate(input, output, act_info); +} diff --git a/src/runtime/CL/functions/CLArithmeticAddition.cpp b/src/runtime/CL/functions/CLArithmeticAddition.cpp index 5ca384d6a4..5fa0b8c33a 100644 --- a/src/runtime/CL/functions/CLArithmeticAddition.cpp +++ b/src/runtime/CL/functions/CLArithmeticAddition.cpp @@ -36,3 +36,8 @@ void CLArithmeticAddition::configure(const ICLTensor *input1, const ICLTensor *i k->configure(input1, input2, output, policy); _kernel = std::move(k); } + +Error CLArithmeticAddition::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +{ + return CLArithmeticAdditionKernel::validate(input1, input2, output, policy); +} diff --git a/src/runtime/CL/functions/CLArithmeticSubtraction.cpp b/src/runtime/CL/functions/CLArithmeticSubtraction.cpp index 651f51a24a..12a6b80691 100644 --- a/src/runtime/CL/functions/CLArithmeticSubtraction.cpp +++ b/src/runtime/CL/functions/CLArithmeticSubtraction.cpp @@ -36,3 +36,8 @@ void CLArithmeticSubtraction::configure(const ICLTensor *input1, const ICLTensor k->configure(input1, input2, output, policy); _kernel = std::move(k); } + +Error CLArithmeticSubtraction::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy) +{ + return CLArithmeticSubtractionKernel::validate(input1, input2, output, policy); +} diff --git a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp index 68cdaac812..c4e307e541 100644 --- a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp @@ -42,6 +42,14 @@ void CLBatchNormalizationLayer::configure(ICLTensor *input, ICLTensor *output, c _norm_kernel.configure(input, output, mean, var, beta, gamma, epsilon); } +Error CLBatchNormalizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *var, + const ITensorInfo *beta, const ITensorInfo *gamma, + float epsilon) +{ + return CLBatchNormalizationLayerKernel::validate(input, output, mean, var, beta, gamma, epsilon); +} + void CLBatchNormalizationLayer::run() { CLScheduler::get().enqueue(_norm_kernel, true); diff --git a/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp b/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp index 139d466b39..164ff153ed 100644 --- a/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp +++ b/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp @@ -37,3 +37,9 @@ void CLPixelWiseMultiplication::configure(const ICLTensor *input1, const ICLTens k->configure(input1, input2, output, scale, overflow_policy, rounding_policy); _kernel = std::move(k); } + +Error CLPixelWiseMultiplication::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy) +{ + return CLPixelWiseMultiplicationKernel::validate(input1, input2, output, scale, overflow_policy, rounding_policy); +}
\ No newline at end of file diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp index 83bd2d0a3a..becfb847e6 100644 --- a/tests/validation/CL/ActivationLayer.cpp +++ b/tests/validation/CL/ActivationLayer.cpp @@ -156,6 +156,41 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } } +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data types + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Unsupported activation + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + }), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + })), + framework::dataset::make("Expected", { true, false, false, true, true, true, false })), + input_info, output_info, act_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLActivationLayer::validate(&input_info, &output_info, act_info)) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + template <typename T> using CLActivationLayerFixture = ActivationValidationFixture<CLTensor, CLAccessor, CLActivationLayer, T>; diff --git a/tests/validation/CL/ArithmeticAddition.cpp b/tests/validation/CL/ArithmeticAddition.cpp index 51257b4b88..19ccdaf111 100644 --- a/tests/validation/CL/ArithmeticAddition.cpp +++ b/tests/validation/CL/ArithmeticAddition.cpp @@ -61,6 +61,38 @@ const auto ArithmeticAdditionFP32Dataset = combine(combine(framework::dataset::m TEST_SUITE(CL) TEST_SUITE(ArithmeticAddition) +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Invalid data type combination + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("Expected", { false, false, true, true, true, false })), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLArithmeticAddition::validate(&input1_info, &input2_info, &output_info, ConvertPolicy::WRAP)) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + template <typename T> using CLArithmeticAdditionFixture = ArithmeticAdditionValidationFixture<CLTensor, CLAccessor, CLArithmeticAddition, T>; diff --git a/tests/validation/CL/ArithmeticSubtraction.cpp b/tests/validation/CL/ArithmeticSubtraction.cpp index 5e7d741009..a068c8a357 100644 --- a/tests/validation/CL/ArithmeticSubtraction.cpp +++ b/tests/validation/CL/ArithmeticSubtraction.cpp @@ -68,6 +68,38 @@ const auto ArithmeticSubtractionFP32Dataset = combine(combine(framework::dataset TEST_SUITE(CL) TEST_SUITE(ArithmeticSubtraction) +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Invalid data type combination + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("Expected", { false, false, true, true, true, false })), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLArithmeticSubtraction::validate(&input1_info, &input2_info, &output_info, ConvertPolicy::WRAP)) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + template <typename T1, typename T2 = T1, typename T3 = T1> using CLArithmeticSubtractionFixture = ArithmeticSubtractionValidationFixture<CLTensor, CLAccessor, CLArithmeticSubtraction, T1, T2, T3>; diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp index 69f8d7b635..c29a400402 100644 --- a/tests/validation/CL/BatchNormalizationLayer.cpp +++ b/tests/validation/CL/BatchNormalizationLayer.cpp @@ -78,6 +78,43 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran validate(dst.info()->valid_region(), valid_region); } +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data types + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data types + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + }), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32), + TensorInfo(TensorShape(2U), 1, DataType::F16), + TensorInfo(TensorShape(2U), 1, DataType::F32), + TensorInfo(TensorShape(5U), 1, DataType::F32), + TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), + TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("Expected", { false, true, true, true, true, false})), + input_info, output_info, mvbg_info, expected) +{ + auto mean_info = mvbg_info; + auto var_info = mvbg_info; + auto beta_info = mvbg_info; + auto gamma_info = mvbg_info; + bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info, &output_info, &mean_info, &var_info, &beta_info, &gamma_info, 1.f)); + ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + TEST_SUITE(Float) TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), diff --git a/tests/validation/CL/PixelWiseMultiplication.cpp b/tests/validation/CL/PixelWiseMultiplication.cpp index 66f3ff6375..d49462a7f7 100644 --- a/tests/validation/CL/PixelWiseMultiplication.cpp +++ b/tests/validation/CL/PixelWiseMultiplication.cpp @@ -90,6 +90,46 @@ using CLFixedPointPixelWiseMultiplicationFixture = FixedPointPixelWiseMultiplica TEST_SUITE(CL) TEST_SUITE(PixelWiseMultiplication) +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Invalid scale + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Invalid data type combination + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching data type + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Invalid scale + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS16, 2), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), + })), + framework::dataset::make("Scale",{ 2.f, 2.f, -1.f, 1.f, 1.f, 1.f, 1.f, 3.f})), + framework::dataset::make("Expected", { false, false, true, true, true, true, true, true })), + input1_info, input2_info, output_info, scale, expected) +{ + bool has_error = bool(CLPixelWiseMultiplication::validate(&input1_info, &input2_info, &output_info, scale, ConvertPolicy::WRAP, RoundingPolicy::TO_ZERO)); + ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + TEST_SUITE(F16toF16) TEST_SUITE(Scale255) |