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c5a91cbb
编写于
9月 01, 2018
作者:
L
liuruilong
浏览文件
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电子邮件补丁
差异文件
fix conv add 1x5 error
上级
79897ccb
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
61 addition
and
0 deletion
+61
-0
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddKernel.swift
...obile/paddle-mobile/Operators/Kernels/ConvAddKernel.swift
+2
-0
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/ConvAddMetal.metal
.../paddle-mobile/Operators/Kernels/metal/ConvAddMetal.metal
+59
-0
未找到文件。
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddKernel.swift
浏览文件 @
c5a91cbb
...
...
@@ -33,6 +33,8 @@ class ConvAddKernel<P: PrecisionType>: Kernel, Computable {
super
.
init
(
device
:
device
,
inFunctionName
:
"depthwise_conv_add_3x3"
)
}
else
if
param
.
filter
.
width
==
1
&&
param
.
filter
.
height
==
5
{
super
.
init
(
device
:
device
,
inFunctionName
:
"conv_add_5x1"
)
}
else
if
param
.
filter
.
width
==
5
&&
param
.
filter
.
height
==
1
{
super
.
init
(
device
:
device
,
inFunctionName
:
"conv_add_1x5"
)
}
else
{
super
.
init
(
device
:
device
,
inFunctionName
:
"conv_add_3x3"
)
}
...
...
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/ConvAddMetal.metal
浏览文件 @
c5a91cbb
...
...
@@ -183,10 +183,69 @@ kernel void conv_add_5x1(texture2d_array<float, access::sample> inTexture [[text
output.w += dot(input[j], weight_w);
}
}
output = output + biase[gid.z];
outTexture.write(output, gid.xy, gid.z);
}
kernel void conv_add_1x5(texture2d_array<float, access::sample> inTexture [[texture(0)]],
texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvParam ¶m [[buffer(0)]],
const device float4 *weights [[buffer(1)]],
const device float4 *biase [[buffer(2)]],
uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) {
return;
}
ushort2 stride = ushort2(param.strideX, param.strideY);
const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
const uint kernelHXW = 5;
uint input_arr_size = inTexture.get_array_size();
uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
float4 output = float4(0.0);
ushort dilation_x = param.dilationX;
float4 input[5];
for (uint i = 0; i < input_arr_size; ++i) {
input[0] = inTexture.sample(sample, float2(posInInput.x - 2 * dilation_x, posInInput.y), i);
input[1] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y), i);
input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
input[3] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y), i);
input[4] = inTexture.sample(sample, float2(posInInput.x + 2 * dilation_x, posInInput.y), i);
for (int j = 0; j < 5; ++j) {
float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
output.x += dot(input[j], weight_x);
float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
output.y += dot(input[j], weight_y);
float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
output.z += dot(input[j], weight_z);
float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
output.w += dot(input[j], weight_w);
}
}
output = output + biase[gid.z];
outTexture.write(output, gid.xy, gid.z);
}
kernel void depthwise_conv_add_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
texture2d_array<float, access::write> outTexture [[texture(1)]],
...
...
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