| /external/XNNPACK/test/ |
| D | resize-bilinear-nhwc.cc | 26 for (size_t output_width = input_width + 1; output_width < 15; output_width *= 3) { in TEST() local
29 .output_size(1, output_width) in TEST()
39 for (size_t output_width = 3; output_width <= 5; output_width += 2) { in TEST() local
42 .output_size(output_height, output_width) in TEST()
64 for (size_t output_width = 1; output_width <= 3; output_width++) { in TEST() local
65 for (size_t input_width = output_width + 1; input_width < 15; input_width *= 3) { in TEST()
68 .output_size(1, output_width) in TEST()
180 for (size_t output_width = input_width + 1; output_width < 15; output_width *= 3) { in TEST() local
184 .output_size(1, output_width) in TEST()
194 for (size_t output_width = 3; output_width <= 5; output_width += 2) { in TEST() local
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| D | resize-bilinear-operator-tester.h | 52 inline ResizeBilinearOperatorTester& output_size(size_t output_height, size_t output_width) { in output_size() argument
54 assert(output_width >= 1); in output_size()
56 this->output_width_ = output_width; in output_size()
70 inline ResizeBilinearOperatorTester& output_width(size_t output_width) { in output_width() argument
71 assert(output_width >= 1); in output_width()
72 this->output_width_ = output_width; in output_width()
76 inline size_t output_width() const { in output_width() function
89 if (align_corners() && output_width() > 1) { in width_scale()
90 return float(input_width() - 1) / float(output_width() - 1); in width_scale()
92 return float(input_width()) / float(output_width()); in width_scale()
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| D | average-pooling-operator-tester.h | 218 inline size_t output_width() const { in output_width() function
398 …std::vector<uint8_t> output((batch_size() * output_height() * output_width() - 1) * output_pixel_s… in TestQ8()
399 std::vector<float> output_ref(batch_size() * output_height() * output_width() * channels()); in TestQ8()
408 for (size_t ox = 0; ox < output_width(); ox++) { in TestQ8()
420 …output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = float(acc * scal… in TestQ8()
421 output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = in TestQ8()
422 …std::min<float>(output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c], f… in TestQ8()
423 output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = in TestQ8()
424 …std::max<float>(output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c], f… in TestQ8()
462 for (size_t x = 0; x < output_width(); x++) { in TestQ8()
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| D | argmax-pooling-operator-tester.h | 168 inline size_t output_width() const { in output_width() function
296 …std::vector<float> output((batch_size() * output_height() * output_width() - 1) * output_pixel_str… in TestF32()
297 std::vector<float> output_ref(batch_size() * output_height() * output_width() * channels()); in TestF32()
298 std::vector<uint32_t> index(batch_size() * output_height() * output_width() * channels()); in TestF32()
299 std::vector<uint32_t> index_ref(batch_size() * output_height() * output_width() * channels()); in TestF32()
307 for (size_t ox = 0; ox < output_width(); ox++) { in TestF32()
327 … output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_value; in TestF32()
328 … index_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_index; in TestF32()
379 for (size_t x = 0; x < output_width(); x++) { in TestF32()
381 …ASSERT_LE(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c], ou… in TestF32()
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| D | convolution-operator-tester.h | 99 (output_width() - 1) * subsampling_width() + dilated_kernel_width() - input_width(); in padding_left()
131 (output_width() - 1) * subsampling_width() + dilated_kernel_width() - input_width(); in padding_right()
364 return groups() * group_output_channels() * output_height() * output_width(); in output_batch_stride()
366 …is->output_batch_stride_ >= groups() * group_output_channels() * output_height() * output_width()); in output_batch_stride()
392 inline size_t output_width() const { in output_width() function
546 …std::vector<uint8_t> output(batch_size() * ((output_height() * output_width() - 1) * output_pixel_… in TestNHWCxQ8()
547 …std::vector<int32_t> accumulators(batch_size() * output_height() * output_width() * groups() * gro… in TestNHWCxQ8()
548 …std::vector<double> output_ref(batch_size() * output_height() * output_width() * groups() * group_… in TestNHWCxQ8()
563 for (size_t ox = 0; ox < output_width(); ox++) { in TestNHWCxQ8()
566 …accumulators[(((i * output_height() + oy) * output_width() + ox) * groups() + g) * group_output_ch… in TestNHWCxQ8()
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| D | max-pooling-operator-tester.h | 261 inline size_t output_width() const { in output_width() function
401 …std::vector<uint8_t> output((batch_size() * output_height() * output_width() - 1) * output_pixel_s… in TestU8()
402 std::vector<uint8_t> output_ref(batch_size() * output_height() * output_width() * channels()); in TestU8()
410 for (size_t ox = 0; ox < output_width(); ox++) { in TestU8()
425 … output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_value; in TestU8()
462 for (size_t x = 0; x < output_width(); x++) { in TestU8()
464 …ASSERT_LE(uint32_t(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride()… in TestU8()
465 …ASSERT_GE(uint32_t(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride()… in TestU8()
466 … ASSERT_EQ(uint32_t(output_ref[((i * output_height() + y) * output_width() + x) * channels() + c]), in TestU8()
467 … uint32_t(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c])) << in TestU8()
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| D | deconvolution-operator-tester.h | 332 inline size_t output_width() const { in output_width() function
440 …std::vector<uint8_t> output((batch_size() * output_height() * output_width() - 1) * output_pixel_s… in TestQ8()
441 …std::vector<int32_t> accumulators(batch_size() * output_height() * output_width() * groups() * gro… in TestQ8()
442 …std::vector<double> output_ref(batch_size() * output_height() * output_width() * groups() * group_… in TestQ8()
457 for (size_t ox = 0; ox < output_width(); ox++) { in TestQ8()
460 …accumulators[(((i * output_height() + oy) * output_width() + ox) * groups() + g) * group_output_ch… in TestQ8()
472 for (size_t ox = 0; ox < output_width(); ox++) { in TestQ8()
484 …accumulators[(((i * output_height() + oy) * output_width() + ox) * groups() + g) * group_output_ch… in TestQ8()
548 for (size_t x = 0; x < output_width(); x++) { in TestQ8()
551 …ASSERT_LE(int32_t(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() … in TestQ8()
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| D | conv-hwc2spchw-microkernel-tester.h | 254 inline size_t output_width() const { in output_width() function
294 ASSERT_GE(output_width(), 1);
306 std::vector<float> output(batch_size() * output_channels() * output_height() * output_width());
307 …std::vector<float> output_ref(batch_size() * output_channels() * output_height() * output_width());
327 for (size_t ox = 0; ox < output_width(); ox++) {
345 … output_ref[((i * output_channels() + oc) * output_height() + oy) * output_width() + ox] = acc;
380 output_width() * sizeof(float),
381 output_height() * output_width() * sizeof(float),
387 for (size_t x = 0; x < output_width(); x++) {
389 …ASSERT_GE(output[((i * output_channels() + c) * output_height() + y) * output_width() + x], output…
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| D | dwconv-spchw-microkernel-tester.h | 131 inline uint32_t output_width() const { in output_width() function
190 …return (this->output_width() + output_tuple_size() - 1) / output_tuple_size() * output_tuple_size(… in output_width_stride()
235 (output_width() - 1) / output_tuple_size() * output_tuple_stride() + output_tuple_size());
236 std::vector<float> output_ref(output_height() * output_width());
244 for (size_t ox = 0; ox < output_width(); ox++) {
257 output_ref[oy * output_width() + ox] = acc;
294 for (size_t x = 0; x < output_width(); x++) {
296 output_ref[y * output_width() + x],
298 std::abs(output_ref[y * output_width() + x]) * 1.0e-5)
304 if (output_width() % output_tuple_size() != 0) {
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| D | conv-hwc-microkernel-tester.h | 254 inline size_t output_width() const { in output_width() function
294 ASSERT_GE(output_width(), 1);
306 …std::vector<float> output(batch_size() * ((output_height() * output_width() - 1) * output_pixel_st…
307 …std::vector<float> output_ref(batch_size() * output_height() * output_width() * output_channels());
327 for (size_t ox = 0; ox < output_width(); ox++) {
345 … output_ref[((i * output_height() + oy) * output_width() + ox) * output_channels() + oc] = acc;
380 output_pixel_stride() * output_width() * sizeof(float),
387 for (size_t x = 0; x < output_width(); x++) {
389 …ASSERT_GE(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c], ou…
391 …ASSERT_LE(output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c], ou…
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| /external/libjpeg-turbo/simd/ |
| D | jsimd.h | 545 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
548 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
552 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
555 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
559 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
562 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
566 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
569 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
574 JSAMPARRAY *output_data_ptr, JDIMENSION output_width,
578 (int max_v_samp_factor, JDIMENSION output_width, JSAMPARRAY input_data,
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | spacetodepth_op_gpu.cu.cc | 37 const int output_width, const int output_depth, in S2D_NHWC() argument
56 output_depth * (out_w + output_width * (out_h + output_height * b)); in S2D_NHWC()
66 const int block_size, const int output_width, in S2D_NCHW() argument
81 const int n_iC_oY_bY = n_iC_oY_bY_oX / output_width; in S2D_NCHW()
82 const int oX = n_iC_oY_bY_oX - n_iC_oY_bY * output_width; in S2D_NCHW()
93 output_width; in S2D_NCHW()
104 const int output_width, const int input_width, in S2D_NCHW_LOOP() argument
120 const int n_iC_oY = thread_idx / output_width; in S2D_NCHW_LOOP()
121 const int oX = thread_idx - n_iC_oY * output_width; in S2D_NCHW_LOOP()
152 const int output_width = output.dimension(2); in operator ()() local
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| D | spectrogram_op.cc | 55 const int64 output_width = spectrogram.output_frequency_channels(); in Compute() local
69 0, TensorShape({output_slices, output_height, output_width}), in Compute()
76 output_flat + (channel * output_height * output_width); in Compute()
91 (spectrogram_output[0].size() == output_width), in Compute()
94 output_width, " but got ", spectrogram_output[0].size())); in Compute()
98 DCHECK_EQ(spectrogram_row.size(), output_width); in Compute()
99 float* output_row = output_slice + (row_index * output_width); in Compute()
101 for (int i = 0; i < output_width; ++i) { in Compute()
105 for (int i = 0; i < output_width; ++i) { in Compute()
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| D | depthtospace_op_gpu.cu.cc | 38 const int output_width, const int output_depth, in D2S_NHWC() argument
44 const int w = out_idx2 % output_width; in D2S_NHWC()
45 const int out_idx3 = out_idx2 / output_width; in D2S_NHWC()
103 const int input_width, const int output_width, in D2S_NCHW_LOOP() argument
127 auto output_ptr = output + (n_oC_iY * output_width + iX) * block_size; in D2S_NCHW_LOOP()
134 output_ptr[bY * output_width + bX] = ldg( in D2S_NCHW_LOOP()
155 const int output_width = output.dimension(2); in operator ()() local
159 batch_size * output_height * output_width * output_depth; in operator ()()
167 input_height, input_width, input_depth, output_height, output_width, in operator ()()
191 const int output_width = output.dimension(3); in operator ()() local
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| D | conv_ops_using_gemm.cc | 93 int output_height, int output_width) { in operator ()() argument
112 ((output_width - 1) * stride_cols + filter_width - input_width + 1) / in operator ()()
119 ((output_width - 1) * stride_cols + filter_width - input_width) / 2; in operator ()()
130 for (int out_x = 0; out_x < output_width; ++out_x) { in operator ()()
183 output_data[(batch * output_height * output_width * filter_count) + in operator ()()
184 (out_y * output_width * filter_count) + in operator ()()
216 int output_height, int output_width) { in operator ()() argument
230 if ((output_width <= 0) || (output_height <= 0)) { in operator ()()
232 << output_width << ", " << output_height; in operator ()()
273 ((output_width - 1) * stride_cols + filter_width - input_width + 1) / in operator ()()
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| /external/XNNPACK/src/ |
| D | resize-bilinear-nhwc.c | 95 size_t output_width, in xnn_setup_resize_bilinear2d_nhwc_f32() argument
126 if (output_width == 0 || output_height == 0) { in xnn_setup_resize_bilinear2d_nhwc_f32()
129 output_width, output_height); in xnn_setup_resize_bilinear2d_nhwc_f32()
133 if (max(output_width, output_height) >= 16777216) { in xnn_setup_resize_bilinear2d_nhwc_f32()
137 output_width, output_height); in xnn_setup_resize_bilinear2d_nhwc_f32()
146 …if (output_height * output_width != resize_op->last_output_height * resize_op->last_output_width) { in xnn_setup_resize_bilinear2d_nhwc_f32()
147 const size_t indirection_buffer_size = sizeof(void*) * (output_height * output_width * 4); in xnn_setup_resize_bilinear2d_nhwc_f32()
148 const size_t packed_weights_size = sizeof(float) * (output_height * output_width * 2); in xnn_setup_resize_bilinear2d_nhwc_f32()
169 output_width != resize_op->last_output_width) in xnn_setup_resize_bilinear2d_nhwc_f32()
175 output_height, output_width, in xnn_setup_resize_bilinear2d_nhwc_f32()
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| D | indirection.c | 30 const size_t output_width = op->output_width; in xnn_indirection_init_conv2d() local
40 const size_t output_size = output_height * output_width; in xnn_indirection_init_conv2d()
44 const struct fxdiv_divisor_size_t output_width_divisor = fxdiv_init_size_t(output_width); in xnn_indirection_init_conv2d()
93 const size_t output_width = op->output_width; in xnn_indirection_init_dwconv2d() local
108 for (size_t output_x = 0; output_x < output_width; output_x++) { in xnn_indirection_init_dwconv2d()
121 for (size_t output_x = 0; output_x < output_width; output_x++) { in xnn_indirection_init_dwconv2d()
145 const size_t output_width = op->output_width; in xnn_indirection_init_deconv2d() local
155 const size_t output_size = output_height * output_width; in xnn_indirection_init_deconv2d()
159 const struct fxdiv_divisor_size_t output_width_divisor = fxdiv_init_size_t(output_width); in xnn_indirection_init_deconv2d()
201 const size_t output_width = op->output_width; in xnn_indirection_init_subconv2d() local
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| /external/webrtc/talk/media/base/ |
| D | videoframefactory.cc | 39 int output_width, in CreateAliasedFrame() argument
46 if (cropped_input_width == output_width && in CreateAliasedFrame()
56 std::swap(output_width, output_height); in CreateAliasedFrame()
62 output_frame_->GetWidth() != static_cast<size_t>(output_width) || in CreateAliasedFrame()
65 cropped_input_frame->Stretch(output_width, output_height, true, true)); in CreateAliasedFrame()
67 LOG(LS_WARNING) << "Failed to stretch frame to " << output_width << "x" in CreateAliasedFrame()
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| /external/libaom/libaom/aom_dsp/x86/ |
| D | variance_impl_ssse3.c | 22 unsigned int output_width, const uint8_t *filter) { in aom_var_filter_block2d_bil_first_pass_ssse3() argument
35 if (output_width >= 8) { in aom_var_filter_block2d_bil_first_pass_ssse3()
37 for (j = 0; j < output_width; j += 8) { in aom_var_filter_block2d_bil_first_pass_ssse3()
59 a += src_pixels_per_line - output_width; in aom_var_filter_block2d_bil_first_pass_ssse3()
80 b += output_width; in aom_var_filter_block2d_bil_first_pass_ssse3()
88 unsigned int output_width, const uint8_t *filter) { in aom_var_filter_block2d_bil_second_pass_ssse3() argument
101 for (j = 0; j < output_width; j += 4) { in aom_var_filter_block2d_bil_second_pass_ssse3()
127 a += src_pixels_per_line - output_width; in aom_var_filter_block2d_bil_second_pass_ssse3()
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| /external/tensorflow/tensorflow/lite/kernels/internal/ |
| D | resize_bilinear_test.cc | 31 int input_height, int output_width, in TestOneResizeBilinear() argument
35 {batch, output_height, output_width, depth}); in TestOneResizeBilinear()
51 std::vector<int32> output_size_data = {output_height, output_width}; in TestOneResizeBilinear()
91 const int output_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST_P() local
95 input_height, output_width, output_height, in TEST_P()
110 const int output_width = input_width * 2; in TEST_P() local
120 input_height, output_width, output_height, in TEST_P()
135 const int output_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST_P() local
145 input_height, output_width, output_height, in TEST_P()
160 const int output_width = input_width * 2; in TEST_P() local
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| D | resize_nearest_neighbor_test.cc | 153 int input_height, int output_width, in TestOptimizedResizeNearestNeighbor() argument
159 RuntimeShape output_shape({batch, output_height, output_width, depth}); in TestOptimizedResizeNearestNeighbor()
168 std::vector<int32> output_size_data = {output_height, output_width}; in TestOptimizedResizeNearestNeighbor()
184 bool is_valid_scale(int input_width, int input_height, int output_width, in is_valid_scale() argument
189 static_cast<float>(input_width) / output_width; in is_valid_scale()
192 int32 width_scale_int = (input_width << 16) / output_width + 1; in is_valid_scale()
202 for (int x = 0; x < output_width; ++x) { in is_valid_scale()
223 const int output_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local
226 if (is_valid_scale(input_width, input_height, output_width, in TEST()
229 batch, depth, input_width, input_height, output_width, output_height); in TEST()
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| D | test_util.cc | 36 int output_width = 0; in ComputeConvSizes() local
44 output_width = (input_width + stride - dilated_filter_width) / stride; in ComputeConvSizes()
47 output_width = (input_width + stride - 1) / stride; in ComputeConvSizes()
52 if (output_width <= 0 || output_height <= 0) { in ComputeConvSizes()
61 ((output_width - 1) * stride + dilated_filter_width - input_width) / 2); in ComputeConvSizes()
63 output_shape->BuildFrom({batch, output_height, output_width, output_depth}); in ComputeConvSizes()
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| /external/libaom/libaom/test/ |
| D | convolve_test.cc | 74 unsigned int output_width, unsigned int output_height) { in filter_block2d_8_c() argument
95 1 - static_cast<int>(intermediate_height * output_width); in filter_block2d_8_c()
99 const int src_next_row_stride = src_stride - output_width; in filter_block2d_8_c()
102 for (j = 0; j < output_width; ++j) { in filter_block2d_8_c()
121 const int dst_next_row_stride = dst_stride - output_width; in filter_block2d_8_c()
123 for (j = 0; j < output_width; ++j) { in filter_block2d_8_c()
142 unsigned int output_width, unsigned int output_height) { in block2d_average_c() argument
145 for (j = 0; j < output_width; ++j) { in block2d_average_c()
156 unsigned int output_width, in filter_average_block2d_8_c() argument
160 assert(output_width <= kMaxDimension); in filter_average_block2d_8_c()
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| /external/libjpeg-turbo/ |
| D | jdmaster.c | 115 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
123 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
131 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
139 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
147 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
155 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
163 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
171 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
179 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
187 cinfo->output_width = (JDIMENSION) in jpeg_core_output_dimensions()
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| /external/tensorflow/tensorflow/lite/tools/evaluation/stages/ |
| D | image_preprocessing_stage.cc | 153 int output_height, output_width; in ResizeBilinear() local
160 output_width = params.target_size().width(); in ResizeBilinear()
163 output_width = static_cast<int>(round(image_data->width * ratio_h)); in ResizeBilinear()
168 output_width = params.target_size().width(); in ResizeBilinear()
171 std::vector<int32_t> output_size_data = {output_height, output_width}; in ResizeBilinear()
173 {1, output_height, output_width, kNumChannels}); in ResizeBilinear()
174 int output_size = output_width * output_height * kNumChannels; in ResizeBilinear()
180 image_data->width = output_width; in ResizeBilinear()
186 int output_width = params.target_size().width(); in Pad() local
195 static_cast<int>(round((output_width - image_data->width) / 2.0)); in Pad()
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