| /external/XNNPACK/src/ |
| D | indirection.c | 51 const size_t output_y = output_y_x.quotient; in xnn_indirection_init_conv2d() local
53 … const size_t input_y = output_y * stride_height + kernel_y * dilation_height - input_padding_top; in xnn_indirection_init_conv2d()
113 const size_t output_y = output_y_x.quotient; in xnn_indirection_init_deconv2d() local
115 const size_t y = output_y + padding_top - kernel_y * dilation_height; in xnn_indirection_init_deconv2d()
167 for (size_t output_y = output_y_start; output_y < output_height; output_y += stride_height) { in xnn_indirection_init_subconv2d() local
170 assert(doz(output_y + padding_top, kernel_y) % stride_height == 0); in xnn_indirection_init_subconv2d()
171 const size_t y = output_y + padding_top - kernel_y; in xnn_indirection_init_subconv2d()
221 for (size_t output_y = 0; output_y < output_height; output_y++) { in xnn_indirection_init_dwconv2d() local
223 … const size_t input_y = output_y * stride_height + kernel_y * dilation_height - input_padding_top; in xnn_indirection_init_dwconv2d()
228 …const size_t index = output_y * step_height + output_x * step_width * kernel_height + kernel_x * k… in xnn_indirection_init_dwconv2d()
[all …]
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| D | im2col.c | 30 for (size_t output_y = 0; output_y < output_height; output_y++) { in xnn_im2col_conv2d() local
33 …const size_t input_y = output_y * subsampling_height + kernel_y * dilation_height - input_padding_… in xnn_im2col_conv2d()
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| D | operator-run.c | 371 size_t output_y) in xnn_compute_dwconv_unipass() argument
374 …(const void**) ((uintptr_t) context->indirect_input + output_y * context->indirect_input_height_st… in xnn_compute_dwconv_unipass()
377 batch_index * context->output_batch_stride + output_y * context->output_height_stride); in xnn_compute_dwconv_unipass()
462 size_t output_y) in xnn_compute_argmax_pooling_unipass() argument
465 output_y * context->indirect_input_height_stride); in xnn_compute_argmax_pooling_unipass()
468 batch_index * context->output_batch_stride + output_y * context->output_height_stride); in xnn_compute_argmax_pooling_unipass()
470 batch_index * context->index_batch_stride + output_y * context->index_height_stride); in xnn_compute_argmax_pooling_unipass()
481 size_t output_y) in xnn_compute_argmax_pooling_multipass() argument
484 output_y * context->indirect_input_height_stride); in xnn_compute_argmax_pooling_multipass()
487 batch_index * context->output_batch_stride + output_y * context->output_height_stride); in xnn_compute_argmax_pooling_multipass()
[all …]
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| /external/tensorflow/tensorflow/lite/micro/examples/person_detection/himax_driver/ |
| D | HM01B0_optimized.c | 67 const uint32_t output_y = (hsync_count - offset_y) >> kStrideShift; in hm01b0_blocking_read_oneframe_scaled() local
79 if (output_x < w && output_y < h) { in hm01b0_blocking_read_oneframe_scaled()
80 const int output_idx = (output_y * w + output_x) * channels; in hm01b0_blocking_read_oneframe_scaled()
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| /external/XNNPACK/test/ |
| D | resize-bilinear-operator-tester.h | 242 for (size_t output_y = 0; output_y < output_height(); output_y++) { in TestNHWCxF32() local
243 const float input_y = (float(output_y) + offset) * height_scale() - offset; in TestNHWCxF32()
253 …output_ref[((batch_index * output_height() + output_y) * output_width() + output_x) * channels() +… in TestNHWCxF32()
327 for (size_t output_y = 0; output_y < output_height(); output_y++) { in TestNCHWxF32() local
328 const float input_y = (float(output_y) + offset) * height_scale() - offset; in TestNCHWxF32()
338 …output_ref[batch_index * output_num_elements + c * output_num_pixels + output_y * output_width() +… in TestNCHWxF32()
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| /external/tensorflow/tensorflow/core/kernels/image/ |
| D | image_ops.h | 141 const int64 output_y = coords[1];
147 float projection = transform[6] * output_x + transform[7] * output_y + 1.f;
154 (transform[0] * output_x + transform[1] * output_y + transform[2]) /
157 (transform[3] * output_x + transform[4] * output_y + transform[5]) /
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| /external/XNNPACK/src/xnnpack/ |
| D | compute.h | 411 size_t output_y);
513 size_t output_y);
565 size_t output_y);
570 size_t output_y);
601 size_t output_y);
606 size_t output_y);
639 size_t output_y);
644 size_t output_y);
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| /external/XNNPACK/src/f32-conv-hwc2chw/ |
| D | 3x3s2p1c3x4-sse-1x1.c | 52 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 1) { in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__sse_1x1() local
53 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__sse_1x1()
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| D | 3x3s2p1c3x4-scalar-1x1.c | 50 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 1) { in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__scalar_1x1() local
51 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__scalar_1x1()
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| D | 3x3s2p1c3x4-neonfma-2x2.c | 55 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__neonfma_2x2() local
56 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__neonfma_2x2()
67 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc2chw_ukernel_3x3s2p1c3x4__neonfma_2x2()
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| /external/XNNPACK/src/f32-conv-hwc/gen/ |
| D | 3x3s2p0p1c3x4-neon-2x1.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x1() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x1()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x1()
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| D | 3x3s2p1c3x4-neonfma-2x1.c | 62 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neonfma_2x1() local
63 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neonfma_2x1()
77 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neonfma_2x1()
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| D | 3x3s2p1c3x4-neon-2x1.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x1() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x1()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x1()
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| D | 3x3s2p0p1c3x4-neonfma-2x1.c | 62 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x1() local
63 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x1()
77 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x1()
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| D | 3x3s2p1c3x8-neon-2x1.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neon_2x1() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neon_2x1()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neon_2x1()
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| D | 3x3s2p0p1c3x8-neonfma-2x1.c | 62 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neonfma_2x1() local
63 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neonfma_2x1()
77 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neonfma_2x1()
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| D | 3x3s2p1c3x8-neonfma-2x1.c | 62 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neonfma_2x1() local
63 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neonfma_2x1()
77 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x8__neonfma_2x1()
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| D | 3x3s2p0p1c3x8-neon-2x1.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neon_2x1() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neon_2x1()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x8__neon_2x1()
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| D | 3x3s2p0p1c3x4-neonfma-2x2.c | 62 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x2() local
63 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x2()
77 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neonfma_2x2()
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| D | 3x3s2p1c3x4-neon-2x2.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x2() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x2()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__neon_2x2()
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| D | 3x3s2p0p1c3x4-neon-2x2.c | 60 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 2) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x2() local
61 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x2()
75 if XNN_UNPREDICTABLE(output_y + 2 > output_y_end) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__neon_2x2()
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | kernelized_test.py | 348 output_y = math.sqrt(2.0 / small_output_dim) * rff_layer(y)
354 approx_kernel_value = kernelized_utils.inner_product(output_x, output_y)
392 output_y = math.sqrt(2.0 / output_dim) * rff_layer(y)
394 approx_kernel_matrix = kernelized_utils.inner_product(output_x, output_y)
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| /external/XNNPACK/src/operators/ |
| D | average-pooling-nhwc.c | 559 for (size_t output_y = 0; output_y < output_height; output_y++) { in setup_average_pooling2d() local
560 …const size_t input_y_start = doz(output_y * average_pooling_op->stride_height, average_pooling_op-… in setup_average_pooling2d()
562 …min(doz(output_y * average_pooling_op->stride_height + average_pooling_op->kernel_height, average_… in setup_average_pooling2d()
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| /external/XNNPACK/src/f32-conv-hwc/ |
| D | 3x3s2p1c3x4-scalar-1x1.c | 51 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 1) { in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__scalar_1x1() local
52 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p1c3x4__scalar_1x1()
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| D | 3x3s2p0p1c3x4-scalar-1x1.c | 51 for (size_t output_y = output_y_start; output_y < output_y_end; output_y += 1) { in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__scalar_1x1() local
52 const size_t input_y2 = output_y * 2 + 2 - input_padding_top; in xnn_f32_conv_hwc_ukernel_3x3s2p0p1c3x4__scalar_1x1()
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