ncnn

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// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#version 450
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#if NCNN_fp16_storage
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#extension GL_EXT_shader_16bit_storage: require
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#endif
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#if NCNN_fp16_arithmetic
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#extension GL_EXT_shader_explicit_arithmetic_types_float16: require
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#endif
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#extension GL_GOOGLE_include_directive: enable
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#include "vulkan_activation.comp"
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layout (constant_id = 0) const int kernel_w = 1;
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layout (constant_id = 1) const int kernel_h = 1;
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layout (constant_id = 2) const int dilation_w = 1;
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layout (constant_id = 3) const int dilation_h = 1;
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layout (constant_id = 4) const int stride_w = 1;
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layout (constant_id = 5) const int stride_h = 1;
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layout (constant_id = 6) const int bias_term = 0;
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layout (constant_id = 7) const int group = 1;
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layout (constant_id = 8) const int activation_type = 0;
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layout (constant_id = 9) const float activation_param_0 = 0;
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layout (constant_id = 10) const float activation_param_1 = 0;
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#define shape_constant_id_offset 11
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layout (constant_id = shape_constant_id_offset + 0) const int dims = 0;
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layout (constant_id = shape_constant_id_offset + 1) const int w = 0;
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layout (constant_id = shape_constant_id_offset + 2) const int h = 0;
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layout (constant_id = shape_constant_id_offset + 3) const int c = 0;
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layout (constant_id = shape_constant_id_offset + 4) const int cstep = 0;
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layout (constant_id = shape_constant_id_offset + 5) const int outdims = 0;
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layout (constant_id = shape_constant_id_offset + 6) const int outw = 0;
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layout (constant_id = shape_constant_id_offset + 7) const int outh = 0;
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layout (constant_id = shape_constant_id_offset + 8) const int outc = 0;
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layout (constant_id = shape_constant_id_offset + 9) const int outcstep = 0;
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#if NCNN_image_shader
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layout (binding = 0) uniform unfp sampler3D bottom_blob;
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layout (binding = 1, imfmtc1) writeonly uniform unfp image3D top_blob;
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layout (binding = 2) uniform unfp sampler3D weight_blob;
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layout (binding = 3) uniform unfp sampler3D bias_blob;
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#else
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layout (binding = 0) readonly buffer bottom_blob { sfp bottom_blob_data[]; };
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layout (binding = 1) writeonly buffer top_blob { sfp top_blob_data[]; };
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layout (binding = 2) readonly buffer weight_blob { sfp weight_data[]; };
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layout (binding = 3) readonly buffer bias_blob { sfp bias_data[]; };
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#endif
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layout (push_constant) uniform parameter
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{
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    int dims;
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    int w;
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    int h;
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    int c;
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    int cstep;
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    int outdims;
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    int outw;
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    int outh;
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    int outc;
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    int outcstep;
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} p;
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void main()
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{
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    int gx = int(gl_GlobalInvocationID.x);
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    int gy = int(gl_GlobalInvocationID.y);
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    int gz = int(gl_GlobalInvocationID.z);
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    if (gx >= psc(outw) || gy >= psc(outh) || gz >= psc(outc))
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        return;
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    afp sum;
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    if (bias_term == 1)
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    {
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#if NCNN_image_shader
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        sum = image3d_ld1(bias_blob, ivec3(gz, 0, 0));
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#else
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        sum = buffer_ld1(bias_data, gz);
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#endif
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    }
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    else
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    {
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        sum = afp(0.f);
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    }
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    // depth-wise convolution
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#if NCNN_image_shader
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    int sy = gy * stride_h;
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    int wx = 0;
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    for (int y = 0; y < kernel_h; y++)
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    {
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        int sx = gx * stride_w;
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        for (int x = 0; x < kernel_w; x++)
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        {
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            sum += image3d_ld1(weight_blob, ivec3(wx, gz, 0)) * image3d_ld1(bottom_blob, ivec3(sx, sy, gz));
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            sx += dilation_w;
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            wx += 1;
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        }
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        sy += dilation_h;
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    }
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#else
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    int w_offset = gz * kernel_w * kernel_h;
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    int v_offset = gz * psc(cstep) + gy * stride_h * psc(w) + gx * stride_w;
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    for (int y = 0; y < kernel_h; y++)
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    {
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        for (int x = 0; x < kernel_w; x++)
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        {
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            sum += buffer_ld1(weight_data, w_offset + x) * buffer_ld1(bottom_blob_data, v_offset + x * dilation_w);
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        }
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        v_offset += dilation_h * psc(w);
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        w_offset += kernel_w;
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    }
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#endif
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    sum = activation_afp(sum, activation_type, activation_param_0, activation_param_1);
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#if NCNN_image_shader
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    image3d_st1(top_blob, ivec3(gx, gy, gz), sum);
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#else
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    const int gi = gz * psc(outcstep) + gy * psc(outw) + gx;
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    buffer_st1(top_blob_data, gi, sum);
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#endif
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}
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