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	Signed-off-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: niansa <anton-sa@web.de> Co-authored-by: Adam Treat <treat.adam@gmail.com> Co-authored-by: Aaron Miller <apage43@ninjawhale.com> Co-authored-by: ToKiNoBug <tokinobug@163.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: slaren <slarengh@gmail.com>
		
			
				
	
	
		
			54 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			54 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
#version 450
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#include "common.comp"
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layout(local_size_x = 512) in;
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layout(binding = 0) buffer restrict readonly tensorIn { float in_[]; };
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layout(binding = 1) buffer restrict tensorOut { float out_[]; };
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layout(push_constant) uniform PushConstants {
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    uint inOff;
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    uint outOff;
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    uint ne00;
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    uint nb01;
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    float eps;
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} pcs;
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shared float sum[gl_WorkGroupSize.x];
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void main() {
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    const uint x = (gl_WorkGroupID.x*pcs.nb01/4) + pcs.inOff; // Based from in_
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    // parallel sum
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    sum[gl_LocalInvocationID.x] = 0.0;
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    for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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        sum[gl_LocalInvocationID.x] += in_[x+i00] * in_[x+i00];
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    }
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    // reduce
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    barrier();
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    memoryBarrierShared();
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    [[unroll]] for (uint i = gl_WorkGroupSize.x/2; i > 0; i /= 2) {
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        if (gl_LocalInvocationID.x < i) {
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            sum[gl_LocalInvocationID.x] += sum[gl_LocalInvocationID.x + i];
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        }
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        barrier();
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        memoryBarrierShared();
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    }
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    // broadcast
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    if (gl_LocalInvocationID.x == 0) {
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        sum[0] /= float(pcs.ne00);
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    }
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    barrier();
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    memoryBarrierShared();
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    const float scale = 1.0f/sqrt(sum[0] + pcs.eps);
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    const uint y = (gl_WorkGroupID.x*pcs.ne00) + pcs.outOff; // Based from out_
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    for (uint i00 = gl_LocalInvocationID.x; i00 < pcs.ne00; i00 += gl_WorkGroupSize.x) {
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        out_[y+i00] = in_[x+i00] * scale;
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    }
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}
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