3 // This source code is licensed under the BSD-style license found in the
96     this->iterations_ = iterations;  in iterations()
101     return this->iterations_;  in iterations()
114     std::array<size_t, XNN_MAX_TENSOR_DIMS> input_dims;  in TestX8()  local
118     std::fill(input_dims.begin(), input_dims.end(), 1);  in TestX8()
123       input_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = input_dim(i);  in TestX8()
124       input_pre_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = pre_padding(i);  in TestX8()
125       input_post_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = post_padding(i);  in TestX8()
126       output_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = output_dim(i);  in TestX8()
133     for (size_t i = XNN_MAX_TENSOR_DIMS; i != 0; i--) {  in TestX8()
134       input_strides[i - 1] = input_stride;  in TestX8()
135       output_strides[i - 1] = output_stride;  in TestX8()
136       input_stride *= input_dims[i - 1];  in TestX8()
137       output_stride *= output_dims[i - 1];  in TestX8()
150       for (size_t i = 0; i < input_dims[0]; i++) {  in TestX8()
151         for (size_t j = 0; j < input_dims[1]; j++) {  in TestX8()
152           for (size_t k = 0; k < input_dims[2]; k++) {  in TestX8()
153             for (size_t l = 0; l < input_dims[3]; l++) {  in TestX8()
154               for (size_t m = 0; m < input_dims[4]; m++) {  in TestX8()
155                 for (size_t n = 0; n < input_dims[5]; n++) {  in TestX8()
229     std::array<size_t, XNN_MAX_TENSOR_DIMS> input_dims;  in TestX16()  local
233     std::fill(input_dims.begin(), input_dims.end(), 1);  in TestX16()
238       input_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = input_dim(i);  in TestX16()
239       input_pre_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = pre_padding(i);  in TestX16()
240       input_post_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = post_padding(i);  in TestX16()
241       output_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = output_dim(i);  in TestX16()
248     for (size_t i = XNN_MAX_TENSOR_DIMS; i != 0; i--) {  in TestX16()
249       input_strides[i - 1] = input_stride;  in TestX16()
250       output_strides[i - 1] = output_stride;  in TestX16()
251       input_stride *= input_dims[i - 1];  in TestX16()
252       output_stride *= output_dims[i - 1];  in TestX16()
265       for (size_t i = 0; i < input_dims[0]; i++) {  in TestX16()
266         for (size_t j = 0; j < input_dims[1]; j++) {  in TestX16()
267           for (size_t k = 0; k < input_dims[2]; k++) {  in TestX16()
268             for (size_t l = 0; l < input_dims[3]; l++) {  in TestX16()
269               for (size_t m = 0; m < input_dims[4]; m++) {  in TestX16()
270                 for (size_t n = 0; n < input_dims[5]; n++) {  in TestX16()
344     std::array<size_t, XNN_MAX_TENSOR_DIMS> input_dims;  in TestX32()  local
348     std::fill(input_dims.begin(), input_dims.end(), 1);  in TestX32()
353       input_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = input_dim(i);  in TestX32()
354       input_pre_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = pre_padding(i);  in TestX32()
355       input_post_paddings[XNN_MAX_TENSOR_DIMS - num_dims() + i] = post_padding(i);  in TestX32()
356       output_dims[XNN_MAX_TENSOR_DIMS - num_dims() + i] = output_dim(i);  in TestX32()
363     for (size_t i = XNN_MAX_TENSOR_DIMS; i != 0; i--) {  in TestX32()
364       input_strides[i - 1] = input_stride;  in TestX32()
365       output_strides[i - 1] = output_stride;  in TestX32()
366       input_stride *= input_dims[i - 1];  in TestX32()
367       output_stride *= output_dims[i - 1];  in TestX32()
380       for (size_t i = 0; i < input_dims[0]; i++) {  in TestX32()
381         for (size_t j = 0; j < input_dims[1]; j++) {  in TestX32()
382           for (size_t k = 0; k < input_dims[2]; k++) {  in TestX32()
383             for (size_t l = 0; l < input_dims[3]; l++) {  in TestX32()
384               for (size_t m = 0; m < input_dims[4]; m++) {  in TestX32()
385                 for (size_t n = 0; n < input_dims[5]; n++) {  in TestX32()