metal: faster diagonal infinity
Although, to me it looks like one should simply fuse scale + diagnonal infinity + soft_max on the KQtensor.
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43ca76976d
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2 changed files with 24 additions and 13 deletions
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@ -815,15 +815,17 @@ void ggml_metal_graph_compute(
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case GGML_OP_DIAG_MASK_INF:
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{
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const int n_past = ((int32_t *)(dst->op_params))[0];
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const int64_t n00x01 = ne00*ne01;
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assert((n00x01*ne02)%8 == 0);
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[encoder setComputePipelineState:ctx->pipeline_diag_mask_inf];
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[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
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[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
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[encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
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[encoder setBytes:&ne01 length:sizeof(ne01) atIndex:3];
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[encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
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[encoder setBytes:&n00x01 length:sizeof(n00x01) atIndex:3];
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[encoder setBytes:&n_past length:sizeof(int) atIndex:4];
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[encoder dispatchThreadgroups:MTLSizeMake(ne00, ne01, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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[encoder dispatchThreadgroups:MTLSizeMake(n00x01*ne02/8, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
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} break;
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case GGML_OP_MUL_MAT:
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{
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@ -183,20 +183,29 @@ kernel void kernel_soft_max_4(
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}
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kernel void kernel_diag_mask_inf(
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device const float * src0,
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device float * dst,
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device const float4 * src0,
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device float4 * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int64_t & n00x01,
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constant int & n_past,
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uint3 tpig[[thread_position_in_grid]]) {
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const int64_t i02 = tpig[2];
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const int64_t i01 = tpig[1];
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const int64_t i00 = tpig[0];
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const int64_t i = 2*tpig[0];
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if (i00 > n_past + i01) {
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dst[i02*ne01*ne00 + i01*ne00 + i00] = -INFINITY;
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} else {
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dst[i02*ne01*ne00 + i01*ne00 + i00] = src0[i02*ne01*ne00 + i01*ne00 + i00];
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dst[i+0] = src0[i+0];
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dst[i+1] = src0[i+1];
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int64_t i4 = 4*i;
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const int64_t i02 = i4/n00x01;
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i4 -= i02*n00x01;
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const int64_t i01 = i4/ne00;
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const int64_t i00 = i4 - i01*ne00;
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for (int k = 3; k >= 0; --k) {
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if (i00 + 4 + k <= n_past + i01) {
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break;
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}
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dst[i+1][k] = -INFINITY;
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if (i00 + k > n_past + i01) {
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dst[i][k] = -INFINITY;
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}
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}
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}
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