--- /dev/null
- if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD)
+ // This file is part of OpenCV project.
+ // It is subject to the license terms in the LICENSE file found in the top-level directory
+ // of this distribution and at http://opencv.org/license.html.
+
+
+ #include "test_precomp.hpp"
+ #include <set>
+ #include <string>
+ #include "npy_blob.hpp"
+ #include <opencv2/dnn/shape_utils.hpp>
+
+ #if defined(_MSC_VER) // workaround for 32-bit MSVC compiler
+ #pragma optimize("", off)
+ #endif
+
+
+ #define CV_TEST_TAG_DNN_ERROR_PARSER "dnn_error_parser"
+ #define CV_TEST_TAG_DNN_ERROR_NET_SETUP "dnn_error_net_setup"
+ #define CV_TEST_TAG_DNN_ERROR_FORWARD "dnn_error_forward"
+ #define CV_TEST_TAG_DNN_LAYER_FALLBACK "dnn_layer_fallback"
+ #define CV_TEST_TAG_DNN_NO_ACCURACY_CHECK "dnn_no_accuracy_check"
+
+
+ namespace opencv_test {
+
+ struct TestCase
+ {
+ const char* name;
+ uint32_t inputs;
+ uint32_t outputs;
+ };
+
+ static const TestCase testConformanceConfig[] = {
+ {"test_abs", 1, 1},
+ {"test_acos", 1, 1},
+ {"test_acos_example", 1, 1},
+ {"test_acosh", 1, 1},
+ {"test_acosh_example", 1, 1},
+ {"test_adagrad", 5, 2},
+ {"test_adagrad_multiple", 8, 4},
+ {"test_adam", 6, 3},
+ {"test_adam_multiple", 10, 6},
+ {"test_add", 2, 1},
+ {"test_add_bcast", 2, 1},
+ {"test_add_uint8", 2, 1},
+ {"test_and2d", 2, 1},
+ {"test_and3d", 2, 1},
+ {"test_and4d", 2, 1},
+ {"test_and_bcast3v1d", 2, 1},
+ {"test_and_bcast3v2d", 2, 1},
+ {"test_and_bcast4v2d", 2, 1},
+ {"test_and_bcast4v3d", 2, 1},
+ {"test_and_bcast4v4d", 2, 1},
+ {"test_argmax_default_axis_example", 1, 1},
+ {"test_argmax_default_axis_example_select_last_index", 1, 1},
+ {"test_argmax_default_axis_random", 1, 1},
+ {"test_argmax_default_axis_random_select_last_index", 1, 1},
+ {"test_argmax_keepdims_example", 1, 1},
+ {"test_argmax_keepdims_example_select_last_index", 1, 1},
+ {"test_argmax_keepdims_random", 1, 1},
+ {"test_argmax_keepdims_random_select_last_index", 1, 1},
+ {"test_argmax_negative_axis_keepdims_example", 1, 1},
+ {"test_argmax_negative_axis_keepdims_example_select_last_index", 1, 1},
+ {"test_argmax_negative_axis_keepdims_random", 1, 1},
+ {"test_argmax_negative_axis_keepdims_random_select_last_index", 1, 1},
+ {"test_argmax_no_keepdims_example", 1, 1},
+ {"test_argmax_no_keepdims_example_select_last_index", 1, 1},
+ {"test_argmax_no_keepdims_random", 1, 1},
+ {"test_argmax_no_keepdims_random_select_last_index", 1, 1},
+ {"test_argmin_default_axis_example", 1, 1},
+ {"test_argmin_default_axis_example_select_last_index", 1, 1},
+ {"test_argmin_default_axis_random", 1, 1},
+ {"test_argmin_default_axis_random_select_last_index", 1, 1},
+ {"test_argmin_keepdims_example", 1, 1},
+ {"test_argmin_keepdims_example_select_last_index", 1, 1},
+ {"test_argmin_keepdims_random", 1, 1},
+ {"test_argmin_keepdims_random_select_last_index", 1, 1},
+ {"test_argmin_negative_axis_keepdims_example", 1, 1},
+ {"test_argmin_negative_axis_keepdims_example_select_last_index", 1, 1},
+ {"test_argmin_negative_axis_keepdims_random", 1, 1},
+ {"test_argmin_negative_axis_keepdims_random_select_last_index", 1, 1},
+ {"test_argmin_no_keepdims_example", 1, 1},
+ {"test_argmin_no_keepdims_example_select_last_index", 1, 1},
+ {"test_argmin_no_keepdims_random", 1, 1},
+ {"test_argmin_no_keepdims_random_select_last_index", 1, 1},
+ {"test_asin", 1, 1},
+ {"test_asin_example", 1, 1},
+ {"test_asinh", 1, 1},
+ {"test_asinh_example", 1, 1},
+ {"test_atan", 1, 1},
+ {"test_atan_example", 1, 1},
+ {"test_atanh", 1, 1},
+ {"test_atanh_example", 1, 1},
+ {"test_averagepool_1d_default", 1, 1},
+ {"test_averagepool_2d_ceil", 1, 1},
+ {"test_averagepool_2d_default", 1, 1},
+ {"test_averagepool_2d_pads", 1, 1},
+ {"test_averagepool_2d_pads_count_include_pad", 1, 1},
+ {"test_averagepool_2d_precomputed_pads", 1, 1},
+ {"test_averagepool_2d_precomputed_pads_count_include_pad", 1, 1},
+ {"test_averagepool_2d_precomputed_same_upper", 1, 1},
+ {"test_averagepool_2d_precomputed_strides", 1, 1},
+ {"test_averagepool_2d_same_lower", 1, 1},
+ {"test_averagepool_2d_same_upper", 1, 1},
+ {"test_averagepool_2d_strides", 1, 1},
+ {"test_averagepool_3d_default", 1, 1},
+ {"test_basic_conv_with_padding", 2, 1},
+ {"test_basic_conv_without_padding", 2, 1},
+ {"test_basic_convinteger", 3, 1},
+ {"test_batchnorm_epsilon", 5, 1},
+ {"test_batchnorm_epsilon_training_mode", 5, 3},
+ {"test_batchnorm_example", 5, 1},
+ {"test_batchnorm_example_training_mode", 5, 3},
+ {"test_bernoulli", 1, 1},
+ {"test_bernoulli_double", 1, 1},
+ {"test_bernoulli_double_expanded", 1, 1},
+ {"test_bernoulli_expanded", 1, 1},
+ {"test_bernoulli_seed", 1, 1},
+ {"test_bernoulli_seed_expanded", 1, 1},
+ {"test_bitshift_left_uint16", 2, 1},
+ {"test_bitshift_left_uint32", 2, 1},
+ {"test_bitshift_left_uint64", 2, 1},
+ {"test_bitshift_left_uint8", 2, 1},
+ {"test_bitshift_right_uint16", 2, 1},
+ {"test_bitshift_right_uint32", 2, 1},
+ {"test_bitshift_right_uint64", 2, 1},
+ {"test_bitshift_right_uint8", 2, 1},
+ {"test_cast_BFLOAT16_to_FLOAT", 1, 1},
+ {"test_cast_DOUBLE_to_FLOAT", 1, 1},
+ {"test_cast_DOUBLE_to_FLOAT16", 1, 1},
+ {"test_cast_FLOAT16_to_DOUBLE", 1, 1},
+ {"test_cast_FLOAT16_to_FLOAT", 1, 1},
+ {"test_cast_FLOAT_to_BFLOAT16", 1, 1},
+ {"test_cast_FLOAT_to_DOUBLE", 1, 1},
+ {"test_cast_FLOAT_to_FLOAT16", 1, 1},
+ {"test_cast_FLOAT_to_STRING", 1, 1},
+ {"test_cast_STRING_to_FLOAT", 1, 1},
+ {"test_castlike_BFLOAT16_to_FLOAT", 2, 1},
+ {"test_castlike_BFLOAT16_to_FLOAT_expanded", 2, 1},
+ {"test_castlike_DOUBLE_to_FLOAT", 2, 1},
+ {"test_castlike_DOUBLE_to_FLOAT16", 2, 1},
+ {"test_castlike_DOUBLE_to_FLOAT16_expanded", 2, 1},
+ {"test_castlike_DOUBLE_to_FLOAT_expanded", 2, 1},
+ {"test_castlike_FLOAT16_to_DOUBLE", 2, 1},
+ {"test_castlike_FLOAT16_to_DOUBLE_expanded", 2, 1},
+ {"test_castlike_FLOAT16_to_FLOAT", 2, 1},
+ {"test_castlike_FLOAT16_to_FLOAT_expanded", 2, 1},
+ {"test_castlike_FLOAT_to_BFLOAT16", 2, 1},
+ {"test_castlike_FLOAT_to_BFLOAT16_expanded", 2, 1},
+ {"test_castlike_FLOAT_to_DOUBLE", 2, 1},
+ {"test_castlike_FLOAT_to_DOUBLE_expanded", 2, 1},
+ {"test_castlike_FLOAT_to_FLOAT16", 2, 1},
+ {"test_castlike_FLOAT_to_FLOAT16_expanded", 2, 1},
+ {"test_castlike_FLOAT_to_STRING", 2, 1},
+ {"test_castlike_FLOAT_to_STRING_expanded", 2, 1},
+ {"test_castlike_STRING_to_FLOAT", 2, 1},
+ {"test_castlike_STRING_to_FLOAT_expanded", 2, 1},
+ {"test_ceil", 1, 1},
+ {"test_ceil_example", 1, 1},
+ {"test_celu", 1, 1},
+ {"test_celu_expanded", 1, 1},
+ {"test_clip", 3, 1},
+ {"test_clip_default_inbounds", 1, 1},
+ {"test_clip_default_int8_inbounds", 1, 1},
+ {"test_clip_default_int8_max", 2, 1},
+ {"test_clip_default_int8_min", 2, 1},
+ {"test_clip_default_max", 2, 1},
+ {"test_clip_default_min", 2, 1},
+ {"test_clip_example", 3, 1},
+ {"test_clip_inbounds", 3, 1},
+ {"test_clip_outbounds", 3, 1},
+ {"test_clip_splitbounds", 3, 1},
+ {"test_compress_0", 2, 1},
+ {"test_compress_1", 2, 1},
+ {"test_compress_default_axis", 2, 1},
+ {"test_compress_negative_axis", 2, 1},
+ {"test_concat_1d_axis_0", 2, 1},
+ {"test_concat_1d_axis_negative_1", 2, 1},
+ {"test_concat_2d_axis_0", 2, 1},
+ {"test_concat_2d_axis_1", 2, 1},
+ {"test_concat_2d_axis_negative_1", 2, 1},
+ {"test_concat_2d_axis_negative_2", 2, 1},
+ {"test_concat_3d_axis_0", 2, 1},
+ {"test_concat_3d_axis_1", 2, 1},
+ {"test_concat_3d_axis_2", 2, 1},
+ {"test_concat_3d_axis_negative_1", 2, 1},
+ {"test_concat_3d_axis_negative_2", 2, 1},
+ {"test_concat_3d_axis_negative_3", 2, 1},
+ {"test_constant", 0, 1},
+ {"test_constant_pad", 3, 1},
+ {"test_constantofshape_float_ones", 1, 1},
+ {"test_constantofshape_int_shape_zero", 1, 1},
+ {"test_constantofshape_int_zeros", 1, 1},
+ {"test_conv_with_autopad_same", 2, 1},
+ {"test_conv_with_strides_and_asymmetric_padding", 2, 1},
+ {"test_conv_with_strides_no_padding", 2, 1},
+ {"test_conv_with_strides_padding", 2, 1},
+ {"test_convinteger_with_padding", 3, 1},
+ {"test_convinteger_without_padding", 3, 1},
+ {"test_convtranspose", 2, 1},
+ {"test_convtranspose_1d", 2, 1},
+ {"test_convtranspose_3d", 2, 1},
+ {"test_convtranspose_autopad_same", 2, 1},
+ {"test_convtranspose_dilations", 2, 1},
+ {"test_convtranspose_kernel_shape", 2, 1},
+ {"test_convtranspose_output_shape", 2, 1},
+ {"test_convtranspose_pad", 2, 1},
+ {"test_convtranspose_pads", 2, 1},
+ {"test_convtranspose_with_kernel", 2, 1},
+ {"test_cos", 1, 1},
+ {"test_cos_example", 1, 1},
+ {"test_cosh", 1, 1},
+ {"test_cosh_example", 1, 1},
+ {"test_cumsum_1d", 2, 1},
+ {"test_cumsum_1d_exclusive", 2, 1},
+ {"test_cumsum_1d_reverse", 2, 1},
+ {"test_cumsum_1d_reverse_exclusive", 2, 1},
+ {"test_cumsum_2d_axis_0", 2, 1},
+ {"test_cumsum_2d_axis_1", 2, 1},
+ {"test_cumsum_2d_negative_axis", 2, 1},
+ {"test_depthtospace_crd_mode", 1, 1},
+ {"test_depthtospace_crd_mode_example", 1, 1},
+ {"test_depthtospace_dcr_mode", 1, 1},
+ {"test_depthtospace_example", 1, 1},
+ {"test_dequantizelinear", 3, 1},
+ {"test_dequantizelinear_axis", 3, 1},
+ {"test_det_2d", 1, 1},
+ {"test_det_nd", 1, 1},
+ {"test_div", 2, 1},
+ {"test_div_bcast", 2, 1},
+ {"test_div_example", 2, 1},
+ {"test_div_uint8", 2, 1},
+ {"test_dropout_default", 1, 1},
+ {"test_dropout_default_mask", 1, 2},
+ {"test_dropout_default_mask_ratio", 2, 2},
+ {"test_dropout_default_old", 1, 1},
+ {"test_dropout_default_ratio", 2, 1},
+ {"test_dropout_random_old", 1, 1},
+ {"test_dynamicquantizelinear", 1, 3},
+ {"test_dynamicquantizelinear_expanded", 1, 3},
+ {"test_dynamicquantizelinear_max_adjusted", 1, 3},
+ {"test_dynamicquantizelinear_max_adjusted_expanded", 1, 3},
+ {"test_dynamicquantizelinear_min_adjusted", 1, 3},
+ {"test_dynamicquantizelinear_min_adjusted_expanded", 1, 3},
+ {"test_edge_pad", 2, 1},
+ {"test_einsum_batch_diagonal", 1, 1},
+ {"test_einsum_batch_matmul", 2, 1},
+ {"test_einsum_inner_prod", 2, 1},
+ {"test_einsum_sum", 1, 1},
+ {"test_einsum_transpose", 1, 1},
+ {"test_elu", 1, 1},
+ {"test_elu_default", 1, 1},
+ {"test_elu_example", 1, 1},
+ {"test_equal", 2, 1},
+ {"test_equal_bcast", 2, 1},
+ {"test_erf", 1, 1},
+ {"test_exp", 1, 1},
+ {"test_exp_example", 1, 1},
+ {"test_expand_dim_changed", 2, 1},
+ {"test_expand_dim_unchanged", 2, 1},
+ {"test_eyelike_populate_off_main_diagonal", 1, 1},
+ {"test_eyelike_with_dtype", 1, 1},
+ {"test_eyelike_without_dtype", 1, 1},
+ {"test_flatten_axis0", 1, 1},
+ {"test_flatten_axis1", 1, 1},
+ {"test_flatten_axis2", 1, 1},
+ {"test_flatten_axis3", 1, 1},
+ {"test_flatten_default_axis", 1, 1},
+ {"test_flatten_negative_axis1", 1, 1},
+ {"test_flatten_negative_axis2", 1, 1},
+ {"test_flatten_negative_axis3", 1, 1},
+ {"test_flatten_negative_axis4", 1, 1},
+ {"test_floor", 1, 1},
+ {"test_floor_example", 1, 1},
+ {"test_gather_0", 2, 1},
+ {"test_gather_1", 2, 1},
+ {"test_gather_2d_indices", 2, 1},
+ {"test_gather_elements_0", 2, 1},
+ {"test_gather_elements_1", 2, 1},
+ {"test_gather_elements_negative_indices", 2, 1},
+ {"test_gather_negative_indices", 2, 1},
+ {"test_gathernd_example_float32", 2, 1},
+ {"test_gathernd_example_int32", 2, 1},
+ {"test_gathernd_example_int32_batch_dim1", 2, 1},
+ {"test_gemm_all_attributes", 3, 1},
+ {"test_gemm_alpha", 3, 1},
+ {"test_gemm_beta", 3, 1},
+ {"test_gemm_default_matrix_bias", 3, 1},
+ {"test_gemm_default_no_bias", 2, 1},
+ {"test_gemm_default_scalar_bias", 3, 1},
+ {"test_gemm_default_single_elem_vector_bias", 3, 1},
+ {"test_gemm_default_vector_bias", 3, 1},
+ {"test_gemm_default_zero_bias", 3, 1},
+ {"test_gemm_transposeA", 3, 1},
+ {"test_gemm_transposeB", 3, 1},
+ {"test_globalaveragepool", 1, 1},
+ {"test_globalaveragepool_precomputed", 1, 1},
+ {"test_globalmaxpool", 1, 1},
+ {"test_globalmaxpool_precomputed", 1, 1},
+ {"test_greater", 2, 1},
+ {"test_greater_bcast", 2, 1},
+ {"test_greater_equal", 2, 1},
+ {"test_greater_equal_bcast", 2, 1},
+ {"test_greater_equal_bcast_expanded", 2, 1},
+ {"test_greater_equal_expanded", 2, 1},
+ {"test_gridsample", 2, 1},
+ {"test_gridsample_aligncorners_true", 2, 1},
+ {"test_gridsample_bicubic", 2, 1},
+ {"test_gridsample_bilinear", 2, 1},
+ {"test_gridsample_border_padding", 2, 1},
+ {"test_gridsample_nearest", 2, 1},
+ {"test_gridsample_reflection_padding", 2, 1},
+ {"test_gridsample_zeros_padding", 2, 1},
+ {"test_gru_batchwise", 3, 2},
+ {"test_gru_defaults", 3, 1},
+ {"test_gru_seq_length", 4, 1},
+ {"test_gru_with_initial_bias", 4, 1},
+ {"test_hardmax_axis_0", 1, 1},
+ {"test_hardmax_axis_1", 1, 1},
+ {"test_hardmax_axis_2", 1, 1},
+ {"test_hardmax_default_axis", 1, 1},
+ {"test_hardmax_example", 1, 1},
+ {"test_hardmax_negative_axis", 1, 1},
+ {"test_hardmax_one_hot", 1, 1},
+ {"test_hardsigmoid", 1, 1},
+ {"test_hardsigmoid_default", 1, 1},
+ {"test_hardsigmoid_example", 1, 1},
+ {"test_hardswish", 1, 1},
+ {"test_hardswish_expanded", 1, 1},
+ {"test_identity", 1, 1},
+ {"test_identity_opt", 1, 1},
+ {"test_identity_sequence", 1, 1},
+ {"test_if", 1, 1},
+ {"test_if_opt", 1, 1},
+ {"test_if_seq", 1, 1},
+ {"test_instancenorm_epsilon", 3, 1},
+ {"test_instancenorm_example", 3, 1},
+ {"test_isinf", 1, 1},
+ {"test_isinf_negative", 1, 1},
+ {"test_isinf_positive", 1, 1},
+ {"test_isnan", 1, 1},
+ {"test_leakyrelu", 1, 1},
+ {"test_leakyrelu_default", 1, 1},
+ {"test_leakyrelu_example", 1, 1},
+ {"test_less", 2, 1},
+ {"test_less_bcast", 2, 1},
+ {"test_less_equal", 2, 1},
+ {"test_less_equal_bcast", 2, 1},
+ {"test_less_equal_bcast_expanded", 2, 1},
+ {"test_less_equal_expanded", 2, 1},
+ {"test_log", 1, 1},
+ {"test_log_example", 1, 1},
+ {"test_logsoftmax_axis_0", 1, 1},
+ {"test_logsoftmax_axis_0_expanded", 1, 1},
+ {"test_logsoftmax_axis_1", 1, 1},
+ {"test_logsoftmax_axis_1_expanded", 1, 1},
+ {"test_logsoftmax_axis_2", 1, 1},
+ {"test_logsoftmax_axis_2_expanded", 1, 1},
+ {"test_logsoftmax_default_axis", 1, 1},
+ {"test_logsoftmax_default_axis_expanded", 1, 1},
+ {"test_logsoftmax_example_1", 1, 1},
+ {"test_logsoftmax_example_1_expanded", 1, 1},
+ {"test_logsoftmax_large_number", 1, 1},
+ {"test_logsoftmax_large_number_expanded", 1, 1},
+ {"test_logsoftmax_negative_axis", 1, 1},
+ {"test_logsoftmax_negative_axis_expanded", 1, 1},
+ {"test_loop11", 3, 2},
+ {"test_loop13_seq", 3, 1},
+ {"test_loop16_seq_none", 3, 1},
+ {"test_lrn", 1, 1},
+ {"test_lrn_default", 1, 1},
+ {"test_lstm_batchwise", 3, 2},
+ {"test_lstm_defaults", 3, 1},
+ {"test_lstm_with_initial_bias", 4, 1},
+ {"test_lstm_with_peepholes", 8, 1},
+ {"test_matmul_2d", 2, 1},
+ {"test_matmul_3d", 2, 1},
+ {"test_matmul_4d", 2, 1},
+ {"test_matmulinteger", 4, 1},
+ {"test_max_example", 3, 1},
+ {"test_max_float16", 2, 1},
+ {"test_max_float32", 2, 1},
+ {"test_max_float64", 2, 1},
+ {"test_max_int16", 2, 1},
+ {"test_max_int32", 2, 1},
+ {"test_max_int64", 2, 1},
+ {"test_max_int8", 2, 1},
+ {"test_max_one_input", 1, 1},
+ {"test_max_two_inputs", 2, 1},
+ {"test_max_uint16", 2, 1},
+ {"test_max_uint32", 2, 1},
+ {"test_max_uint64", 2, 1},
+ {"test_max_uint8", 2, 1},
+ {"test_maxpool_1d_default", 1, 1},
+ {"test_maxpool_2d_ceil", 1, 1},
+ {"test_maxpool_2d_default", 1, 1},
+ {"test_maxpool_2d_dilations", 1, 1},
+ {"test_maxpool_2d_pads", 1, 1},
+ {"test_maxpool_2d_precomputed_pads", 1, 1},
+ {"test_maxpool_2d_precomputed_same_upper", 1, 1},
+ {"test_maxpool_2d_precomputed_strides", 1, 1},
+ {"test_maxpool_2d_same_lower", 1, 1},
+ {"test_maxpool_2d_same_upper", 1, 1},
+ {"test_maxpool_2d_strides", 1, 1},
+ {"test_maxpool_2d_uint8", 1, 1},
+ {"test_maxpool_3d_default", 1, 1},
+ {"test_maxpool_with_argmax_2d_precomputed_pads", 1, 2},
+ {"test_maxpool_with_argmax_2d_precomputed_strides", 1, 2},
+ {"test_maxunpool_export_with_output_shape", 3, 1},
+ {"test_maxunpool_export_without_output_shape", 2, 1},
+ {"test_mean_example", 3, 1},
+ {"test_mean_one_input", 1, 1},
+ {"test_mean_two_inputs", 2, 1},
+ {"test_min_example", 3, 1},
+ {"test_min_float16", 2, 1},
+ {"test_min_float32", 2, 1},
+ {"test_min_float64", 2, 1},
+ {"test_min_int16", 2, 1},
+ {"test_min_int32", 2, 1},
+ {"test_min_int64", 2, 1},
+ {"test_min_int8", 2, 1},
+ {"test_min_one_input", 1, 1},
+ {"test_min_two_inputs", 2, 1},
+ {"test_min_uint16", 2, 1},
+ {"test_min_uint32", 2, 1},
+ {"test_min_uint64", 2, 1},
+ {"test_min_uint8", 2, 1},
+ {"test_mod_broadcast", 2, 1},
+ {"test_mod_int64_fmod", 2, 1},
+ {"test_mod_mixed_sign_float16", 2, 1},
+ {"test_mod_mixed_sign_float32", 2, 1},
+ {"test_mod_mixed_sign_float64", 2, 1},
+ {"test_mod_mixed_sign_int16", 2, 1},
+ {"test_mod_mixed_sign_int32", 2, 1},
+ {"test_mod_mixed_sign_int64", 2, 1},
+ {"test_mod_mixed_sign_int8", 2, 1},
+ {"test_mod_uint16", 2, 1},
+ {"test_mod_uint32", 2, 1},
+ {"test_mod_uint64", 2, 1},
+ {"test_mod_uint8", 2, 1},
+ {"test_momentum", 5, 2},
+ {"test_momentum_multiple", 8, 4},
+ {"test_mul", 2, 1},
+ {"test_mul_bcast", 2, 1},
+ {"test_mul_example", 2, 1},
+ {"test_mul_uint8", 2, 1},
+ {"test_mvn", 1, 1},
+ {"test_mvn_expanded", 1, 1},
+ {"test_neg", 1, 1},
+ {"test_neg_example", 1, 1},
+ {"test_nesterov_momentum", 5, 2},
+ {"test_nllloss_NC", 2, 1},
+ {"test_nllloss_NC_expanded", 2, 1},
+ {"test_nllloss_NCd1", 2, 1},
+ {"test_nllloss_NCd1_expanded", 2, 1},
+ {"test_nllloss_NCd1_ii", 2, 1},
+ {"test_nllloss_NCd1_ii_expanded", 2, 1},
+ {"test_nllloss_NCd1_mean_weight_negative_ii", 3, 1},
+ {"test_nllloss_NCd1_mean_weight_negative_ii_expanded", 3, 1},
+ {"test_nllloss_NCd1_weight", 3, 1},
+ {"test_nllloss_NCd1_weight_expanded", 3, 1},
+ {"test_nllloss_NCd1_weight_ii", 3, 1},
+ {"test_nllloss_NCd1_weight_ii_expanded", 3, 1},
+ {"test_nllloss_NCd1d2", 2, 1},
+ {"test_nllloss_NCd1d2_expanded", 2, 1},
+ {"test_nllloss_NCd1d2_no_weight_reduction_mean_ii", 2, 1},
+ {"test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded", 2, 1},
+ {"test_nllloss_NCd1d2_reduction_mean", 2, 1},
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+ {"test_nllloss_NCd1d2_reduction_sum", 2, 1},
+ {"test_nllloss_NCd1d2_reduction_sum_expanded", 2, 1},
+ {"test_nllloss_NCd1d2_with_weight", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_expanded", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_mean", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_mean_expanded", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_sum", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_sum_expanded", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_sum_ii", 3, 1},
+ {"test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded", 3, 1},
+ {"test_nllloss_NCd1d2d3_none_no_weight_negative_ii", 2, 1},
+ {"test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded", 2, 1},
+ {"test_nllloss_NCd1d2d3_sum_weight_high_ii", 3, 1},
+ {"test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded", 3, 1},
+ {"test_nllloss_NCd1d2d3d4d5_mean_weight", 3, 1},
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+ {"test_nonmaxsuppression_two_batches", 5, 1},
+ {"test_nonmaxsuppression_two_classes", 5, 1},
+ {"test_nonzero_example", 1, 1},
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+ {"test_optional_has_element_empty", 1, 1},
+ {"test_or2d", 2, 1},
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+ {"test_or4d", 2, 1},
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+ {"test_or_bcast4v2d", 2, 1},
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+ {"test_pow", 2, 1},
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+ {"test_pow_bcast_scalar", 2, 1},
+ {"test_pow_example", 2, 1},
+ {"test_pow_types_float", 2, 1},
+ {"test_pow_types_float32_int32", 2, 1},
+ {"test_pow_types_float32_int64", 2, 1},
+ {"test_pow_types_float32_uint32", 2, 1},
+ {"test_pow_types_float32_uint64", 2, 1},
+ {"test_pow_types_int", 2, 1},
+ {"test_pow_types_int32_float32", 2, 1},
+ {"test_pow_types_int32_int32", 2, 1},
+ {"test_pow_types_int64_float32", 2, 1},
+ {"test_pow_types_int64_int64", 2, 1},
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+ {"test_prelu_example", 2, 1},
+ {"test_qlinearconv", 8, 1},
+ {"test_qlinearmatmul_2D", 8, 1},
+ {"test_qlinearmatmul_3D", 8, 1},
+ {"test_quantizelinear", 3, 1},
+ {"test_quantizelinear_axis", 3, 1},
+ {"test_range_float_type_positive_delta", 3, 1},
+ {"test_range_float_type_positive_delta_expanded", 3, 1},
+ {"test_range_int32_type_negative_delta", 3, 1},
+ {"test_range_int32_type_negative_delta_expanded", 3, 1},
+ {"test_reciprocal", 1, 1},
+ {"test_reciprocal_example", 1, 1},
+ {"test_reduce_l1_default_axes_keepdims_example", 1, 1},
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+ {"test_reduce_l1_do_not_keepdims_random", 1, 1},
+ {"test_reduce_l1_keep_dims_example", 1, 1},
+ {"test_reduce_l1_keep_dims_random", 1, 1},
+ {"test_reduce_l1_negative_axes_keep_dims_example", 1, 1},
+ {"test_reduce_l1_negative_axes_keep_dims_random", 1, 1},
+ {"test_reduce_l2_default_axes_keepdims_example", 1, 1},
+ {"test_reduce_l2_default_axes_keepdims_random", 1, 1},
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+ {"test_reduce_l2_keep_dims_random", 1, 1},
+ {"test_reduce_l2_negative_axes_keep_dims_example", 1, 1},
+ {"test_reduce_l2_negative_axes_keep_dims_random", 1, 1},
+ {"test_reduce_log_sum", 1, 1},
+ {"test_reduce_log_sum_asc_axes", 1, 1},
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+ {"test_reduce_log_sum_exp_default_axes_keepdims_random", 1, 1},
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+ {"test_reduce_log_sum_exp_keepdims_random", 1, 1},
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+ {"test_reduce_max_negative_axes_keepdims_example", 1, 1},
+ {"test_reduce_max_negative_axes_keepdims_random", 1, 1},
+ {"test_reduce_mean_default_axes_keepdims_example", 1, 1},
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+ {"test_reduce_min_keepdims_example", 1, 1},
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+ {"test_reduce_min_negative_axes_keepdims_example", 1, 1},
+ {"test_reduce_min_negative_axes_keepdims_random", 1, 1},
+ {"test_reduce_prod_default_axes_keepdims_example", 1, 1},
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+ {"test_reduce_prod_keepdims_example", 1, 1},
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+ {"test_reduce_prod_negative_axes_keepdims_example", 1, 1},
+ {"test_reduce_prod_negative_axes_keepdims_random", 1, 1},
+ {"test_reduce_sum_default_axes_keepdims_example", 2, 1},
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+ {"test_reduce_sum_keepdims_example", 2, 1},
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+ {"test_reduce_sum_negative_axes_keepdims_example", 2, 1},
+ {"test_reduce_sum_negative_axes_keepdims_random", 2, 1},
+ {"test_reduce_sum_square_default_axes_keepdims_example", 1, 1},
+ {"test_reduce_sum_square_default_axes_keepdims_random", 1, 1},
+ {"test_reduce_sum_square_do_not_keepdims_example", 1, 1},
+ {"test_reduce_sum_square_do_not_keepdims_random", 1, 1},
+ {"test_reduce_sum_square_keepdims_example", 1, 1},
+ {"test_reduce_sum_square_keepdims_random", 1, 1},
+ {"test_reduce_sum_square_negative_axes_keepdims_example", 1, 1},
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+ {"test_relu", 1, 1},
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+ {"test_reshape_extended_dims", 2, 1},
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+ {"test_reshape_negative_extended_dims", 2, 1},
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+ {"test_reshape_reduced_dims", 2, 1},
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+ {"test_reshape_reordered_last_dims", 2, 1},
+ {"test_reshape_zero_and_negative_dim", 2, 1},
+ {"test_reshape_zero_dim", 2, 1},
+ {"test_resize_downsample_scales_cubic", 2, 1},
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+ {"test_resize_downsample_scales_linear_align_corners", 2, 1},
+ {"test_resize_downsample_scales_nearest", 2, 1},
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+ {"test_resize_downsample_sizes_linear_pytorch_half_pixel", 2, 1},
+ {"test_resize_downsample_sizes_nearest", 2, 1},
+ {"test_resize_downsample_sizes_nearest_tf_half_pixel_for_nn", 2, 1},
+ {"test_resize_tf_crop_and_resize", 3, 1},
+ {"test_resize_upsample_scales_cubic", 2, 1},
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+ {"test_resize_upsample_scales_cubic_align_corners", 2, 1},
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+ {"test_resize_upsample_scales_nearest", 2, 1},
+ {"test_resize_upsample_sizes_cubic", 2, 1},
+ {"test_resize_upsample_sizes_nearest", 2, 1},
+ {"test_resize_upsample_sizes_nearest_ceil_half_pixel", 2, 1},
+ {"test_resize_upsample_sizes_nearest_floor_align_corners", 2, 1},
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+ {"test_round", 1, 1},
+ {"test_scan9_sum", 2, 2},
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+ {"test_scatter_elements_with_axis", 3, 1},
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+ {"test_scatter_elements_with_negative_indices", 3, 1},
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+ {"test_scatternd", 3, 1},
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+ {"test_scatternd_multiply", 3, 1},
+ {"test_sce_NCd1_mean_weight_negative_ii", 3, 1},
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+ {"test_sce_NCd1d2d3_none_no_weight_negative_ii", 2, 1},
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+ {"test_sce_NCd1d2d3_sum_weight_high_ii", 3, 1},
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+ {"test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", 3, 2},
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+ {"test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", 2, 2},
+ {"test_sce_mean", 2, 1},
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+ {"test_sce_mean_3d_expanded", 2, 1},
+ {"test_sce_mean_3d_log_prob", 2, 2},
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+ {"test_sce_mean_expanded", 2, 1},
+ {"test_sce_mean_log_prob", 2, 2},
+ {"test_sce_mean_log_prob_expanded", 2, 2},
+ {"test_sce_mean_no_weight_ii", 2, 1},
+ {"test_sce_mean_no_weight_ii_3d", 2, 1},
+ {"test_sce_mean_no_weight_ii_3d_expanded", 2, 1},
+ {"test_sce_mean_no_weight_ii_3d_log_prob", 2, 2},
+ {"test_sce_mean_no_weight_ii_3d_log_prob_expanded", 2, 2},
+ {"test_sce_mean_no_weight_ii_4d", 2, 1},
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+ {"test_sce_mean_no_weight_ii_4d_log_prob", 2, 2},
+ {"test_sce_mean_no_weight_ii_4d_log_prob_expanded", 2, 2},
+ {"test_sce_mean_no_weight_ii_expanded", 2, 1},
+ {"test_sce_mean_no_weight_ii_log_prob", 2, 2},
+ {"test_sce_mean_no_weight_ii_log_prob_expanded", 2, 2},
+ {"test_sce_mean_weight", 3, 1},
+ {"test_sce_mean_weight_expanded", 3, 1},
+ {"test_sce_mean_weight_ii", 3, 1},
+ {"test_sce_mean_weight_ii_3d", 3, 1},
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+ {"test_sce_mean_weight_ii_3d_log_prob", 3, 2},
+ {"test_sce_mean_weight_ii_3d_log_prob_expanded", 3, 2},
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+ {"test_sce_mean_weight_ii_4d_log_prob", 3, 2},
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+ {"test_sce_mean_weight_ii_expanded", 3, 1},
+ {"test_sce_mean_weight_ii_log_prob", 3, 2},
+ {"test_sce_mean_weight_ii_log_prob_expanded", 3, 2},
+ {"test_sce_mean_weight_log_prob", 3, 2},
+ {"test_sce_mean_weight_log_prob_expanded", 3, 2},
+ {"test_sce_none", 2, 1},
+ {"test_sce_none_expanded", 2, 1},
+ {"test_sce_none_log_prob", 2, 2},
+ {"test_sce_none_log_prob_expanded", 2, 2},
+ {"test_sce_none_weights", 3, 1},
+ {"test_sce_none_weights_expanded", 3, 1},
+ {"test_sce_none_weights_log_prob", 3, 2},
+ {"test_sce_none_weights_log_prob_expanded", 3, 2},
+ {"test_sce_sum", 2, 1},
+ {"test_sce_sum_expanded", 2, 1},
+ {"test_sce_sum_log_prob", 2, 2},
+ {"test_sce_sum_log_prob_expanded", 2, 2},
+ {"test_selu", 1, 1},
+ {"test_selu_default", 1, 1},
+ {"test_selu_example", 1, 1},
+ {"test_sequence_insert_at_back", 2, 1},
+ {"test_sequence_insert_at_front", 3, 1},
+ {"test_shape", 1, 1},
+ {"test_shape_clip_end", 1, 1},
+ {"test_shape_clip_start", 1, 1},
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+ {"test_shape_end_negative_1", 1, 1},
+ {"test_shape_example", 1, 1},
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+ {"test_shape_start_1_end_2", 1, 1},
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+ {"test_shape_start_negative_1", 1, 1},
+ {"test_shrink_hard", 1, 1},
+ {"test_shrink_soft", 1, 1},
+ {"test_sigmoid", 1, 1},
+ {"test_sigmoid_example", 1, 1},
+ {"test_sign", 1, 1},
+ {"test_simple_rnn_batchwise", 3, 2},
+ {"test_simple_rnn_defaults", 3, 1},
+ {"test_simple_rnn_with_initial_bias", 4, 1},
+ {"test_sin", 1, 1},
+ {"test_sin_example", 1, 1},
+ {"test_sinh", 1, 1},
+ {"test_sinh_example", 1, 1},
+ {"test_size", 1, 1},
+ {"test_size_example", 1, 1},
+ {"test_slice", 5, 1},
+ {"test_slice_default_axes", 3, 1},
+ {"test_slice_default_steps", 4, 1},
+ {"test_slice_end_out_of_bounds", 5, 1},
+ {"test_slice_neg", 5, 1},
+ {"test_slice_neg_steps", 5, 1},
+ {"test_slice_negative_axes", 4, 1},
+ {"test_slice_start_out_of_bounds", 5, 1},
+ {"test_softmax_axis_0", 1, 1},
+ {"test_softmax_axis_0_expanded", 1, 1},
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+ {"test_softmax_example_expanded", 1, 1},
+ {"test_softmax_large_number", 1, 1},
+ {"test_softmax_large_number_expanded", 1, 1},
+ {"test_softmax_negative_axis", 1, 1},
+ {"test_softmax_negative_axis_expanded", 1, 1},
+ {"test_softplus", 1, 1},
+ {"test_softplus_example", 1, 1},
+ {"test_softsign", 1, 1},
+ {"test_softsign_example", 1, 1},
+ {"test_spacetodepth", 1, 1},
+ {"test_spacetodepth_example", 1, 1},
+ {"test_split_equal_parts_1d", 1, 3},
+ {"test_split_equal_parts_2d", 1, 2},
+ {"test_split_equal_parts_default_axis", 1, 3},
+ {"test_split_variable_parts_1d", 2, 2},
+ {"test_split_variable_parts_2d", 2, 2},
+ {"test_split_variable_parts_default_axis", 2, 2},
+ {"test_split_zero_size_splits", 2, 3},
+ {"test_sqrt", 1, 1},
+ {"test_sqrt_example", 1, 1},
+ {"test_squeeze", 2, 1},
+ {"test_squeeze_negative_axes", 2, 1},
+ {"test_strnormalizer_export_monday_casesensintive_lower", 1, 1},
+ {"test_strnormalizer_export_monday_casesensintive_nochangecase", 1, 1},
+ {"test_strnormalizer_export_monday_casesensintive_upper", 1, 1},
+ {"test_strnormalizer_export_monday_empty_output", 1, 1},
+ {"test_strnormalizer_export_monday_insensintive_upper_twodim", 1, 1},
+ {"test_strnormalizer_nostopwords_nochangecase", 1, 1},
+ {"test_sub", 2, 1},
+ {"test_sub_bcast", 2, 1},
+ {"test_sub_example", 2, 1},
+ {"test_sub_uint8", 2, 1},
+ {"test_sum_example", 3, 1},
+ {"test_sum_one_input", 1, 1},
+ {"test_sum_two_inputs", 2, 1},
+ {"test_tan", 1, 1},
+ {"test_tan_example", 1, 1},
+ {"test_tanh", 1, 1},
+ {"test_tanh_example", 1, 1},
+ {"test_tfidfvectorizer_tf_batch_onlybigrams_skip0", 1, 1},
+ {"test_tfidfvectorizer_tf_batch_onlybigrams_skip5", 1, 1},
+ {"test_tfidfvectorizer_tf_batch_uniandbigrams_skip5", 1, 1},
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+ {"test_tfidfvectorizer_tf_onlybigrams_levelempty", 1, 1},
+ {"test_tfidfvectorizer_tf_onlybigrams_skip5", 1, 1},
+ {"test_tfidfvectorizer_tf_uniandbigrams_skip5", 1, 1},
+ {"test_thresholdedrelu", 1, 1},
+ {"test_thresholdedrelu_default", 1, 1},
+ {"test_thresholdedrelu_example", 1, 1},
+ {"test_tile", 2, 1},
+ {"test_tile_precomputed", 2, 1},
+ {"test_top_k", 2, 2},
+ {"test_top_k_negative_axis", 2, 2},
+ {"test_top_k_smallest", 2, 2},
+ {"test_training_dropout", 3, 1},
+ {"test_training_dropout_default", 3, 1},
+ {"test_training_dropout_default_mask", 3, 2},
+ {"test_training_dropout_mask", 3, 2},
+ {"test_training_dropout_zero_ratio", 3, 1},
+ {"test_training_dropout_zero_ratio_mask", 3, 2},
+ {"test_transpose_all_permutations_0", 1, 1},
+ {"test_transpose_all_permutations_1", 1, 1},
+ {"test_transpose_all_permutations_2", 1, 1},
+ {"test_transpose_all_permutations_3", 1, 1},
+ {"test_transpose_all_permutations_4", 1, 1},
+ {"test_transpose_all_permutations_5", 1, 1},
+ {"test_transpose_default", 1, 1},
+ {"test_tril", 1, 1},
+ {"test_tril_neg", 2, 1},
+ {"test_tril_one_row_neg", 1, 1},
+ {"test_tril_out_neg", 2, 1},
+ {"test_tril_out_pos", 2, 1},
+ {"test_tril_pos", 2, 1},
+ {"test_tril_square", 1, 1},
+ {"test_tril_square_neg", 2, 1},
+ {"test_tril_zero", 2, 1},
+ {"test_triu", 1, 1},
+ {"test_triu_neg", 2, 1},
+ {"test_triu_one_row", 2, 1},
+ {"test_triu_out_neg_out", 2, 1},
+ {"test_triu_out_pos", 2, 1},
+ {"test_triu_pos", 2, 1},
+ {"test_triu_square", 1, 1},
+ {"test_triu_square_neg", 2, 1},
+ {"test_triu_zero", 2, 1},
+ {"test_unique_not_sorted_without_axis", 1, 4},
+ {"test_unique_sorted_with_axis", 1, 4},
+ {"test_unique_sorted_with_axis_3d", 1, 4},
+ {"test_unique_sorted_with_negative_axis", 1, 4},
+ {"test_unique_sorted_without_axis", 1, 4},
+ {"test_unsqueeze_axis_0", 2, 1},
+ {"test_unsqueeze_axis_1", 2, 1},
+ {"test_unsqueeze_axis_2", 2, 1},
+ {"test_unsqueeze_axis_3", 1, 1},
+ {"test_unsqueeze_negative_axes", 2, 1},
+ {"test_unsqueeze_three_axes", 2, 1},
+ {"test_unsqueeze_two_axes", 2, 1},
+ {"test_unsqueeze_unsorted_axes", 2, 1},
+ {"test_upsample_nearest", 2, 1},
+ {"test_where_example", 3, 1},
+ {"test_where_long_example", 3, 1},
+ {"test_xor2d", 2, 1},
+ {"test_xor3d", 2, 1},
+ {"test_xor4d", 2, 1},
+ {"test_xor_bcast3v1d", 2, 1},
+ {"test_xor_bcast3v2d", 2, 1},
+ {"test_xor_bcast4v2d", 2, 1},
+ {"test_xor_bcast4v3d", 2, 1},
+ {"test_xor_bcast4v4d", 2, 1},
+ };
+
+
+ std::ostream& operator<<(std::ostream& os, const TestCase& test_case)
+ {
+ return os << test_case.name;
+ }
+
+ typedef tuple<TestCase, tuple<Backend, Target> > ONNXConfParams;
+
+ std::string printOnnxConfParams(const testing::TestParamInfo<ONNXConfParams>& params)
+ {
+ TestCase test_case = get<0>(params.param);
+ Backend backend = get<0>(get<1>(params.param));
+ Target target = get<1>(get<1>(params.param));
+
+ std::stringstream ss;
+ ss << test_case.name << "_";
+ PrintTo(backend, &ss);
+ ss << "_";
+ PrintTo(target, &ss);
+
+ return ss.str();
+ }
+
+ class Test_ONNX_conformance : public TestWithParam<ONNXConfParams>
+ {
+ public:
+
+ TestCase test_case;
+ Backend backend;
+ Target target;
+
+ double default_l1;
+ double default_lInf;
+
+ static std::set<std::string> parser_deny_list;
+ static std::set<std::string> global_deny_list;
+ static std::set<std::string> opencl_fp16_deny_list;
+ static std::set<std::string> opencl_deny_list;
+ static std::set<std::string> cpu_deny_list;
+ #ifdef HAVE_HALIDE
+ static std::set<std::string> halide_deny_list;
+ #endif
+
+ Test_ONNX_conformance()
+ {
+ test_case = get<0>(GetParam());
+ backend = get<0>(get<1>(GetParam()));
+ target = get<1>(get<1>(GetParam()));
+
- std::vector<String> names = net.getLayerNames();
++ if (target == DNN_TARGET_CUDA_FP16 || target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD)
+ {
+ default_l1 = 4e-3;
+ default_lInf = 2e-2;
+ }
+ else
+ {
+ default_l1 = 1e-5;
+ default_lInf = 1e-4;
+ }
+ }
+
+ bool checkFallbacks(Net& net) const
+ {
+ // Check if all the layers are supported with current backend and target.
+ // Some layers might be fused so their timings equal to zero.
+ std::vector<double> timings;
+ net.getPerfProfile(timings);
- static void initDenyList(std::set<std::string>& deny_set, const char* const deny_list[], const size_t n)
- {
- for (size_t i = 0; i < n; ++i)
- {
- deny_set.insert(deny_list[i]);
- }
- }
-
++ std::vector<std::string> names = net.getLayerNames();
+ CV_CheckEQ(names.size(), timings.size(), "DNN critical error");
+
+ bool hasFallbacks = false;
+ for (int i = 0; i < names.size(); ++i)
+ {
+ Ptr<dnn::Layer> l = net.getLayer(net.getLayerId(names[i]));
+ bool fused = timings[i] == 0.;
+ if ((!l->supportBackend(backend) || l->preferableTarget != target) && !fused)
+ {
+ hasFallbacks = true;
+ std::cout << "FALLBACK: Layer [" << l->type << "]:[" << l->name << "] is expected to has backend implementation" << endl;
+ }
+ }
+ return hasFallbacks;
+ }
+
- const char* const parser[] = {
+ static void SetUpTestCase()
+ {
- "" // dummy element of non empty list
++ parser_deny_list = {
+ #include "test_onnx_conformance_layer_parser_denylist.inl.hpp"
- initDenyList(parser_deny_list, parser, sizeof(parser)/sizeof(parser[0]));
+ };
- const char* const global[] = {
+
- "" // dummy element of non empty list
++ global_deny_list = {
+ #include "test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp"
- initDenyList(global_deny_list, global, sizeof(global)/sizeof(global[0]));
+ };
- const char* const opencl_fp16[] = {
+
- "" // dummy element of non empty list
++ opencl_fp16_deny_list = {
+ #include "test_onnx_conformance_layer_filter_opencv_ocl_fp16_denylist.inl.hpp"
- initDenyList(opencl_fp16_deny_list, opencl_fp16, sizeof(opencl_fp16)/sizeof(opencl_fp16[0]));
+ };
- const char* const opencl[] = {
+
- "" // dummy element of non empty list
++ opencl_deny_list = {
+ #include "test_onnx_conformance_layer_filter_opencv_ocl_fp32_denylist.inl.hpp"
- initDenyList(opencl_deny_list, opencl, sizeof(opencl)/sizeof(opencl[0]));
+ };
- const char* const cpu[] = {
+
- "" // dummy element of non empty list
++ cpu_deny_list = {
+ #include "test_onnx_conformance_layer_filter_opencv_cpu_denylist.inl.hpp"
- initDenyList(cpu_deny_list, cpu, sizeof(cpu)/sizeof(cpu[0]));
+ };
- const char* const halide_deny_list_[] = {
+
+ #ifdef HAVE_HALIDE
- "" // dummy element of non empty list
++ halide_deny_list = {
+ #include "test_onnx_conformance_layer_filter__halide_denylist.inl.hpp"
- initDenyList(halide_deny_list, halide_deny_list_, sizeof(halide_deny_list_)/sizeof(halide_deny_list_[0]));
+ };
- std::vector<String> inputNames;
+ #endif
+ }
+
+ };
+
+ std::set<std::string> Test_ONNX_conformance::parser_deny_list;
+ std::set<std::string> Test_ONNX_conformance::global_deny_list;
+ std::set<std::string> Test_ONNX_conformance::opencl_fp16_deny_list;
+ std::set<std::string> Test_ONNX_conformance::opencl_deny_list;
+ std::set<std::string> Test_ONNX_conformance::cpu_deny_list;
+ #ifdef HAVE_HALIDE
+ std::set<std::string> Test_ONNX_conformance::halide_deny_list;
+ #endif
+
+ TEST_P(Test_ONNX_conformance, Layer_Test)
+ {
+ const std::string& name = test_case.name;
+ ASSERT_FALSE(name.empty());
+
+ bool checkLayersFallbacks = true;
+ bool checkAccuracy = true;
+
+ if (parser_deny_list.find(name) != parser_deny_list.end())
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+
+ if (backend == DNN_BACKEND_OPENCV)
+ {
+ if (global_deny_list.find(name) != global_deny_list.end())
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCV_BACKEND, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+ if ((target == DNN_TARGET_OPENCL_FP16) && (opencl_fp16_deny_list.find(name) != opencl_fp16_deny_list.end()))
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_OPENCV_BACKEND, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+ if ((target == DNN_TARGET_OPENCL) && (opencl_deny_list.find(name) != opencl_deny_list.end()))
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL, CV_TEST_TAG_DNN_SKIP_OPENCV_BACKEND, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+ if ((target == DNN_TARGET_CPU) && (cpu_deny_list.find(name) != cpu_deny_list.end()))
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_CPU, CV_TEST_TAG_DNN_SKIP_OPENCV_BACKEND, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+ }
+ #ifdef HAVE_HALIDE
+ else if (backend == DNN_BACKEND_HALIDE)
+ {
+ if (halide_deny_list.find(name) != halide_deny_list.end())
+ {
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE, CV_TEST_TAG_DNN_SKIP_ONNX_CONFORMANCE);
+ }
+ }
+ #endif
+ #ifdef HAVE_INF_ENGINE
+ else if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
+ {
+ #include "test_onnx_conformance_layer_filter__openvino.inl.hpp"
+ }
+ #endif
+ #if 0 //def HAVE_VULKAN
+ else if (backend == DNN_BACKEND_VKCOM)
+ {
+ #include "test_onnx_conformance_layer_filter__vulkan.inl.hpp"
+ }
+ #endif
+ #if 0 //def HAVE_CUDA
+ else if (backend == DNN_BACKEND_CUDA)
+ {
+ #include "test_onnx_conformance_layer_filter__cuda.inl.hpp"
+ }
+ #endif
+ else
+ {
+ std::ostringstream ss;
+ ss << "No test filter available for backend ";
+ PrintTo(backend, &ss);
+ ss << ". Run test by default";
+ std::cout << ss.str() << std::endl;
+ }
+
+ std::vector<Mat> inputs;
+ std::vector<Mat> ref_outputs;
+
+ std::string prefix = cv::format("dnn/onnx/conformance/node/%s", test_case.name);
+
+ Net net;
+ try
+ {
+ std::string model_path = findDataFile(prefix + "/model.onnx");
+
+ //cout << "Read ONNX inputs..." << endl;
+ for (int i = 0; i < test_case.inputs; ++i)
+ {
+ Mat input = readTensorFromONNX(findDataFile(prefix + cv::format("/test_data_set_0/input_%d.pb", i)));
+ inputs.push_back(input);
+ }
+
+ //cout << "Read ONNX reference outputs..." << endl;
+ for (int i = 0; i < test_case.outputs; ++i)
+ {
+ Mat output = readTensorFromONNX(findDataFile(prefix + cv::format("/test_data_set_0/output_%d.pb", i)));
+ ref_outputs.push_back(output);
+ }
+
+ //cout << "Parse model..." << endl;
+ net = readNetFromONNX(model_path);
+ if (net.empty())
+ {
+ applyTestTag(CV_TEST_TAG_DNN_ERROR_PARSER);
+ }
+ }
+ catch (...)
+ {
+ cout << "Exception during ONNX model parse / loading input / loading reference data!" << endl;
+ applyTestTag(CV_TEST_TAG_DNN_ERROR_PARSER);
+ throw;
+ }
+ ASSERT_FALSE(net.empty());
+
- std::vector<String> layerNames = net.getUnconnectedOutLayersNames();
++ std::vector<std::string> inputNames;
+ for (int i = 0; i < inputs.size(); ++i)
+ inputNames.push_back(cv::format("%d", i));
+ net.setInputsNames(inputNames);
+
+ try
+ {
+ net.setPreferableBackend(backend);
+ net.setPreferableTarget(target);
+
+ for (int i = 0; i < inputs.size(); ++i)
+ {
+ net.setInput(inputs[i], inputNames[i]);
+ }
+ }
+ catch (...)
+ {
+ cout << "Exception during network configuration!" << endl;
+ applyTestTag(CV_TEST_TAG_DNN_ERROR_NET_SETUP);
+ throw;
+ }
+
++ std::vector<std::string> layerNames = net.getUnconnectedOutLayersNames();
+ std::vector< std::vector<Mat> > outputs_;
+ try
+ {
+ net.forward(outputs_, layerNames);
+ }
+ catch (...)
+ {
+ cout << "Exception during net.forward() call!" << endl;
+ applyTestTag(CV_TEST_TAG_DNN_ERROR_FORWARD);
+ throw;
+ }
+ ASSERT_GE(outputs_.size(), 1);
+ const std::vector<Mat>& outputs = outputs_[0];
+
+ if (checkLayersFallbacks && checkFallbacks(net))
+ {
+ applyTestTag(CV_TEST_TAG_DNN_LAYER_FALLBACK);
+ }
+
+ if (checkAccuracy)
+ {
+ try
+ {
+ if (ref_outputs.size() == 1)
+ {
+ // probably we found random unconnected layers.
+ normAssert(ref_outputs[0], outputs[0], "", default_l1, default_lInf);
+ }
+ else
+ {
+ ASSERT_EQ(outputs.size(), ref_outputs.size());
+ for (size_t i = 0; i < ref_outputs.size(); ++i)
+ {
+ normAssert(ref_outputs[i], outputs[i], "", default_l1, default_lInf);
+ }
+ }
+ }
+ catch (...)
+ {
+ cout << "Exception during accuracy check!" << endl;
+ throw;
+ }
+ }
+ else
+ {
+ applyTestTag(CV_TEST_TAG_DNN_NO_ACCURACY_CHECK);
+ }
+
+ if (!HasFailure())
+ cout << "Test passed!" << endl;
+ }
+
+ INSTANTIATE_TEST_CASE_P(/**/, Test_ONNX_conformance,
+ testing::Combine(
+ testing::ValuesIn(testConformanceConfig),
+ dnnBackendsAndTargets(/*withInferenceEngine=*/true, /*withHalide=*/true)
+ ),
+ printOnnxConfParams
+ );
+
+ };
projects / platform / upstream / opencv.git / commitdiff