| // Copyright 2019 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <assert.h> |
| |
| #include <xnnpack/dwconv.h> |
| #include <xnnpack/math.h> |
| |
| |
| void xnn_f32_dwconv_chw_ukernel_5x5p2__scalar( |
| size_t input_height, |
| size_t input_width, |
| const float* input, |
| const float* weights, |
| const float* zero, |
| float* output, |
| uint32_t padding_top, |
| const union xnn_f32_chw_params params[restrict XNN_MIN_ELEMENTS(1)]) |
| { |
| assert(input_width != 0); |
| assert(input_height != 0); |
| assert(padding_top == 2); |
| |
| const size_t input_tuple_stride = sizeof(float); |
| const size_t output_tuple_stride = sizeof(float); |
| const size_t input_width_stride = input_width * sizeof(float); |
| const size_t output_width = input_width; |
| const size_t output_width_stride = output_width * sizeof(float); |
| |
| const size_t padded_input_height = input_height + padding_top + 2 /* padding_bottom */; |
| size_t output_height = padded_input_height - 5 + 1; |
| |
| const float params_max = params->scalar.max; |
| const float params_min = params->scalar.min; |
| |
| const size_t input_width_decrement_single = input_width * input_tuple_stride; |
| const size_t input_width_increment_single = input_width_stride - input_width_decrement_single;; |
| const size_t output_width_increment_single = output_width_stride - (input_width - 1) * output_tuple_stride; |
| |
| const float* i0 = zero; |
| const float* i1 = zero;; |
| const float* i2 = input; |
| const float* i3 = (const float*) ((uintptr_t) i2 + input_width_stride); |
| const float* i4 = (const float*) ((uintptr_t) i3 + input_width_stride); |
| if (input_height <= 2) { |
| i4 = zero; |
| } |
| if (input_height == 1) { |
| i3 = zero; |
| } |
| |
| // this almost certainly will use too many scalar registers |
| // hope the compiler is good at spilling... |
| const float vw0 = weights[0]; |
| const float vw1 = weights[1]; |
| const float vw2 = weights[2]; |
| const float vw3 = weights[3]; |
| const float vw4 = weights[4]; |
| const float vw5 = weights[5]; |
| const float vw6 = weights[6]; |
| const float vw7 = weights[7]; |
| const float vw8 = weights[8]; |
| const float vw9 = weights[9]; |
| const float vw10 = weights[10]; |
| const float vw11 = weights[11]; |
| const float vw12 = weights[12]; |
| const float vw13 = weights[13]; |
| const float vw14 = weights[14]; |
| const float vw15 = weights[15]; |
| const float vw16 = weights[16]; |
| const float vw17 = weights[17]; |
| const float vw18 = weights[18]; |
| const float vw19 = weights[19]; |
| const float vw20 = weights[20]; |
| const float vw21 = weights[21]; |
| const float vw22 = weights[22]; |
| const float vw23 = weights[23]; |
| const float vw24 = weights[24]; |
| const float vw25 = weights[25]; |
| |
| do { |
| float vi0x0 = 0.0f; |
| float vi1x0 = 0.0f; |
| float vi2x0 = 0.0f; |
| float vi3x0 = 0.0f; |
| float vi4x0 = 0.0f; |
| float vi0x1 = 0.0f; |
| float vi1x1 = 0.0f; |
| float vi2x1 = 0.0f; |
| float vi3x1 = 0.0f; |
| float vi4x1 = 0.0f; |
| float vi0x2 = *i0++; |
| float vi1x2 = *i1++; |
| float vi2x2 = *i2++; |
| float vi3x2 = *i3++; |
| float vi4x2 = *i4++; |
| |
| float vi0x3; |
| float vi1x3; |
| float vi2x3; |
| float vi3x3; |
| float vi4x3; |
| if XNN_LIKELY(input_width > 1) { |
| vi0x3 = *i0++; |
| vi1x3 = *i1++; |
| vi2x3 = *i2++; |
| vi3x3 = *i3++; |
| vi4x3 = *i4++; |
| } |
| |
| size_t w = input_width; |
| for (; w > 2; w -= 1) { |
| const float vi0x4 = *i0++; |
| const float vi1x4 = *i1++; |
| const float vi2x4 = *i2++; |
| const float vi3x4 = *i3++; |
| const float vi4x4 = *i4++; |
| |
| const float vrow0_accum = vw1 * vi0x0 + vw2 * vi0x1 + vw3 * vi0x2 + vw4 * vi0x3 + vw5 * vi0x4; |
| vi0x0 = vi0x1; |
| vi0x1 = vi0x2; |
| vi0x2 = vi0x3; |
| vi0x3 = vi0x4; |
| const float vrow1_accum = vw6 * vi1x0 + vw7 * vi1x1 + vw8 * vi1x2 + vw9 * vi1x3 + vw10 * vi1x4; |
| vi1x0 = vi1x1; |
| vi1x1 = vi1x2; |
| vi1x2 = vi1x3; |
| vi1x3 = vi1x4; |
| const float vrow2_accum = vw11 * vi2x0 + vw12 * vi2x1 + vw13 * vi2x2 + vw14 * vi2x3 + vw15 * vi2x4; |
| vi2x0 = vi2x1; |
| vi2x1 = vi2x2; |
| vi2x2 = vi2x3; |
| vi2x3 = vi2x4; |
| const float vrow3_accum = vw16 * vi3x0 + vw17 * vi3x1 + vw18 * vi3x2 + vw19 * vi3x3 + vw20 * vi3x4; |
| vi3x0 = vi3x1; |
| vi3x1 = vi3x2; |
| vi3x2 = vi3x3; |
| vi3x3 = vi3x4; |
| const float vrow4_accum = vw21 * vi4x0 + vw22 * vi4x1 + vw23 * vi4x2 + vw24 * vi4x3 + vw25 * vi4x4; |
| vi4x0 = vi4x1; |
| vi4x1 = vi4x2; |
| vi4x2 = vi4x3; |
| vi4x3 = vi4x4; |
| |
| float voutput = (vw0 + vrow0_accum) + (vrow1_accum + vrow2_accum) + (vrow3_accum + vrow4_accum); |
| |
| voutput = math_max_f32(voutput, params_min); |
| voutput = math_min_f32(voutput, params_max); |
| |
| *output++ = voutput; |
| } |
| if XNN_LIKELY(w > 1) { |
| const float vrow0_accum = vw1 * vi0x0 + vw2 * vi0x1 + vw3 * vi0x2 + vw4 * vi0x3; |
| vi0x0 = vi0x1; |
| vi0x1 = vi0x2; |
| vi0x2 = vi0x3; |
| const float vrow1_accum = vw6 * vi1x0 + vw7 * vi1x1 + vw8 * vi1x2 + vw9 * vi1x3; |
| vi1x0 = vi1x1; |
| vi1x1 = vi1x2; |
| vi1x2 = vi1x3; |
| const float vrow2_accum = vw11 * vi2x0 + vw12 * vi2x1 + vw13 * vi2x2 + vw14 * vi2x3; |
| vi2x0 = vi2x1; |
| vi2x1 = vi2x2; |
| vi2x2 = vi2x3; |
| const float vrow3_accum = vw16 * vi3x0 + vw17 * vi3x1 + vw18 * vi3x2 + vw19 * vi3x3; |
| vi3x0 = vi3x1; |
| vi3x1 = vi3x2; |
| vi3x2 = vi3x3; |
| const float vrow4_accum = vw21 * vi4x0 + vw22 * vi4x1 + vw23 * vi4x2 + vw24 * vi4x3; |
| vi4x0 = vi4x1; |
| vi4x1 = vi4x2; |
| vi4x2 = vi4x3; |
| |
| float voutput = (vw0 + vrow0_accum) + (vrow1_accum + vrow2_accum) + (vrow3_accum + vrow4_accum); |
| |
| voutput = math_max_f32(voutput, params_min); |
| voutput = math_min_f32(voutput, params_max); |
| |
| *output++ = voutput; |
| w -= 1; |
| } |
| assert(w == 1); |
| { |
| const float vrow0_accum = vw1 * vi0x0 + vw2 * vi0x1 + vw3 * vi0x2; |
| const float vrow1_accum = vw6 * vi1x0 + vw7 * vi1x1 + vw8 * vi1x2; |
| const float vrow2_accum = vw11 * vi2x0 + vw12 * vi2x1 + vw13 * vi2x2; |
| const float vrow3_accum = vw16 * vi3x0 + vw17 * vi3x1 + vw18 * vi3x2; |
| const float vrow4_accum = vw21 * vi4x0 + vw22 * vi4x1 + vw23 * vi4x2; |
| |
| float voutput = (vw0 + vrow0_accum) + (vrow1_accum + vrow2_accum) + (vrow3_accum + vrow4_accum); |
| |
| voutput = math_max_f32(voutput, params_min); |
| voutput = math_min_f32(voutput, params_max); |
| |
| *output = voutput;; |
| } |
| |
| i0 = (const float*) ((uintptr_t) i1 - input_width_decrement_single); |
| i1 = (const float*) ((uintptr_t) i2 - input_width_decrement_single); |
| i2 = (const float*) ((uintptr_t) i2 + input_width_increment_single); |
| i3 = (const float*) ((uintptr_t) i3 + input_width_increment_single); |
| i4 = (const float*) ((uintptr_t) i4 + input_width_increment_single); |
| output = (float*) ((uintptr_t) output + output_width_increment_single); |
| output_height -= 1; |
| if (output_height <= 2) { |
| i4 = zero; |
| } |
| if (output_height == 1) { |
| i3 = zero; |
| } |
| } while (output_height > 0); |
| } |