Searched refs:weights (Results 1 - 7 of 7) sorted by relevance

/frameworks/compile/libbcc/lib/ScriptCRT/
H A Drs_sample.c96 getSample##vecsize(rs_allocation a, float2 weights, \
102 return p0 * weights.x + p1 * weights.y; \
106 getSample##vecsize(rs_allocation a, float4 weights, \
116 return p0 * weights.x + p1 * weights.y + p2 * weights.z + p3 * weights.w; \
184 result.xyz = getSample565(a, weights, iPixel, next, lod); \
190 result.x = getSample1(a, weights, iPixe
234 getBilinearSample(rs_allocation a, float2 weights, uint32_t iPixel, uint32_t next, uint32_t vecSize, rs_data_type dt, uint32_t lod) argument
241 getBilinearSample(rs_allocation a, float4 weights, uint2 iPixel, uint2 next, uint32_t vecSize, rs_data_type dt, uint32_t lod) argument
279 float2 weights; local
335 float4 weights; local
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/frameworks/ml/bordeaux/learning/stochastic_linear_ranker/java/android/bordeaux/learning/
H A DStochasticLinearRanker.java42 public HashMap<String, Float> weights = new HashMap<String, Float>(); field in class:StochasticLinearRanker.Model
95 slrModel.weights.put(wKeys[i], wValues[i]);
109 String[] wKeys = new String[model.weights.size()];
110 float[] wValues = new float[model.weights.size()];
112 for (Map.Entry<String, Float> e : model.weights.entrySet()){
144 for (Map.Entry<String, Float> e : model.weights.entrySet())
/frameworks/base/media/mca/filterpacks/java/android/filterpacks/imageproc/
H A DSaturateFilter.java48 "uniform vec3 weights;\n" +
52 " float kv = dot(color.rgb, weights) + shift;\n" +
60 "uniform vec3 weights;\n" +
65 " float de = dot(color.rgb, weights);\n" +
145 float weights[] = { 2f/8f, 5f/8f, 1f/8f};
147 mBenProgram.setHostValue("weights", weights);
150 mHerfProgram.setHostValue("weights", weights);
H A DSepiaFilter.java106 float weights[] = { 805.0f / 2048.0f, 715.0f / 2048.0f, 557.0f / 2048.0f,
109 mProgram.setHostValue("matrix", weights);
/frameworks/ml/bordeaux/service/src/android/bordeaux/services/
H A DLearning_StochasticLinearRanker.java90 HashMap<String, Float> weights = new HashMap<String, Float>();
92 weights.put(temp.get(i).key, temp.get(i).value);
95 return mLearningSlRanker.setModelPriorWeights(weights);
/frameworks/base/libs/hwui/
H A DFontRenderer.h381 void computeGaussianWeights(float* weights, int32_t radius);
382 void horizontalBlur(float* weights, int32_t radius, const uint8_t *source, uint8_t *dest,
384 void verticalBlur(float* weights, int32_t radius, const uint8_t *source, uint8_t *dest,
H A DFontRenderer.cpp1109 void FontRenderer::computeGaussianWeights(float* weights, int32_t radius) { argument
1110 // Compute gaussian weights for the blur
1135 weights[r + radius] = coeff1 * pow(e, floatR * floatR * coeff2);
1136 normalizeFactor += weights[r + radius];
1139 //Now we need to normalize the weights because all our coefficients need to add up to one
1142 weights[r + radius] *= normalizeFactor;
1146 void FontRenderer::horizontalBlur(float* weights, int32_t radius, argument
1158 const float* gPtr = weights;
1190 void FontRenderer::verticalBlur(float* weights, int32_t radius, argument
1201 const float* gPtr = weights;
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