/frameworks/base/core/java/android/hardware/camera2/ |
CaptureResult.java | [all...] |
/frameworks/base/core/java/android/widget/ |
LinearLayout.java | 674 * Returns the desired weights sum. 685 * Defines the desired weights sum. If unspecified the weights sum is computed [all...] |
/frameworks/support/v7/appcompat/src/main/java/androidx/appcompat/widget/ |
LinearLayoutCompat.java | 522 * Returns the desired weights sum. 533 * Defines the desired weights sum. If unspecified the weights sum is computed [all...] |
/external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
layers_conv_variational.py | [all...] |
/external/freetype/include/freetype/ |
ftdriver.h | 118 * be the more critical direction anyway; the weights and spacing of 126 * 2) Alignment in the vertical direction: Weights and spacing along the [all...] |
/external/icu/android_icu4j/src/main/java/android/icu/text/ |
AlphabeticIndex.java | [all...] |
/external/icu/android_icu4j/src/main/tests/android/icu/dev/test/collator/ |
CollationRegressionTest.java | [all...] |
/external/icu/icu4c/source/test/intltest/ |
regcoll.cpp | 1097 // Compares and prints only 16-bit primary weights. 1123 // Compares and prints only 16-bit primary weights. [all...] |
/external/icu/icu4j/main/classes/collate/src/com/ibm/icu/text/ |
AlphabeticIndex.java | [all...] |
/external/icu/icu4j/main/tests/collate/src/com/ibm/icu/dev/test/collator/ |
CollationRegressionTest.java | [all...] |
/external/libavc/common/arm/ |
ih264_weighted_bi_pred_a9q.s | 390 @* weights for the weighted prediction in U and V 393 @* weights for the weighted prediction in U and V
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/external/libavc/common/armv8/ |
ih264_weighted_bi_pred_av8.s | 357 //* weights for the weighted prediction in U and V 360 //* weights for the weighted prediction in U and V
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/external/libxcam/modules/isp/ |
aiq_handler.cpp | 849 unsigned char* weights_map_ptr = (*out_weight_grid)->weights; [all...] |
/external/llvm/lib/IR/ |
Metadata.cpp | [all...] |
/external/llvm/test/CodeGen/X86/ |
switch.ll | 632 ; equal-sized sub-trees. When taking weights into account, case 70 becomes the 731 ; the left and {200,300} on the right. However, the jump table weights as much
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/external/mesa3d/src/mesa/main/ |
texcompress_bptc.c | 511 static const uint8_t *weights[] = { local 516 weight = weights[index_bits][index]; [all...] |
/external/tensorflow/tensorflow/compiler/xla/python/ |
xla_client.py | [all...] |
/external/tensorflow/tensorflow/contrib/eager/python/ |
network_test.py | [all...] |
/external/tensorflow/tensorflow/contrib/kfac/python/ops/ |
fisher_blocks.py | 367 [input_size, output_size] corresponding to layer's weights. If not, a 385 [input_size, output_size] corresponding to layer's weights. If not, a [all...] |
/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
state_space_model.py | 100 bayesian_prior_weighting: If True, weights the prior (covariance_prior_fn) 101 based on an estimate of the full dataset size. If False, weights it [all...] |
/external/tensorflow/tensorflow/docs_src/tutorials/ |
audio_recognition.md | 74 This is saving out the current trained weights to a checkpoint file. If your 595 will adjust the number of computations and weights automatically to fit with [all...] |
/external/tensorflow/tensorflow/python/ops/ |
resource_variable_ops.py | 249 constraints or value constraints for layer weights). The function must 322 constraints or value constraints for layer weights). The function must [all...] |
/prebuilts/go/darwin-x86/src/cmd/vendor/github.com/google/pprof/internal/graph/ |
graph.go | 334 // Update edge weights for all edges in stack, avoiding double counting. 1020 // at the flat and cum weights of the node and the incoming/outgoing
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/prebuilts/go/linux-x86/src/cmd/vendor/github.com/google/pprof/internal/graph/ |
graph.go | 334 // Update edge weights for all edges in stack, avoiding double counting. 1020 // at the flat and cum weights of the node and the incoming/outgoing
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/external/ImageMagick/ImageMagick/api/ |
effect.html | 577 <p>Using a separable kernel would be faster, but the negative weights cancel out on the corners of the kernel producing often undesirable ringing in the filtered result; this can be avoided by using a 2D gaussian shaped image sharpening kernel instead.</p>
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