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Results 1 - 10 of 21 for Densify (0.22 sec)
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tensorflow/compiler/mlir/lite/transforms/dense_to_sparse.cc
cst.erase(); } if (result.needs_densify) { auto value = op->getOperand(operand); auto densify = builder.create<DensifyOp>(op->getLoc(), value.getType(), value); value.replaceAllUsesWith(densify); densify.setOperand(value); } } }); } } // namespace
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/passes.td
let summary = "Convert dense tensor to sparse format."; let description = [{ This pass encodes sparse weights in the model in the proper format, and adds Densify() op if necessary. The general algorithm is: 1. Get list of operands (weights) of an op that can be sparse. 2. Get list of supported block configurations of the op. 3. Calculate random sparsity of the weight.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 22.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/test_schema.fbs
MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126 } // Options for the builtin operators. union BuiltinOptions { Conv2DOptions, DepthwiseConv2DOptions, ConcatEmbeddingsOptions,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 19 19:46:06 UTC 2021 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126, PLACEHOLDER_FOR_GREATER_OP_CODES = 127, CUMSUM = 128, CALL_ONCE = 129, BROADCAST_TO = 130, RFFT2D = 131, CONV_3D = 132, IMAG=133,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126, PLACEHOLDER_FOR_GREATER_OP_CODES = 127, CUMSUM = 128, CALL_ONCE = 129, BROADCAST_TO = 130, RFFT2D = 131, CONV_3D = 132, IMAG=133,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
); let results = (outs TFL_TensorOf<[QI4, QI8, QUI8, QI16, TFL_Quint8]>:$output); } def TFL_DensifyOp: TFL_Op<"densify", [ Pure, PredOpTrait<"input and output must have same element type", TFL_TCresVTEtIsSameAsOp<0, 0>>]> { let summary = "Densify operator"; let description = [{ Converts sparse tensor to dense format. }];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
func.return %0 : tensor<1x64x84x31xf32> } // ----- // CHECK-LABEL: testDensify func.func @testDensify(%arg0: tensor<? x f32>) -> tensor<? x f32> { // CHECK: "tfl.densify"(%arg0) : (tensor<?xf32>) -> tensor<?xf32> %0 = "tfl.densify"(%arg0): (tensor<? x f32>) -> tensor<? x f32> func.return %0 : tensor<? x f32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0) -
src/runtime/mpagecache.go
// slower, safer thing by iterating over each bit individually. for i := uint(0); i < 64; i++ { if c.cache&(1<<i) != 0 { p.chunkOf(ci).free1(pi + i) // Update density statistics. p.scav.index.free(ci, pi+i, 1) } if c.scav&(1<<i) != 0 { p.chunkOf(ci).scavenged.setRange(pi+i, 1) } } // Since this is a lot like a free, we need to make sure
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Apr 19 14:30:00 UTC 2023 - 5.6K bytes - Viewed (0) -
android/guava-tests/test/com/google/common/math/MathBenchmarking.java
BigInteger result = randomPositiveBigInteger(numBits); return RANDOM_SOURCE.nextBoolean() ? result : result.negate(); } /** * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of * lower magnitude. */ static BigInteger randomBigInteger(int numBits) { while (true) { if (RANDOM_SOURCE.nextBoolean()) {
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Dec 04 17:37:03 UTC 2017 - 4.1K bytes - Viewed (0) -
guava-tests/test/com/google/common/math/MathBenchmarking.java
BigInteger result = randomPositiveBigInteger(numBits); return RANDOM_SOURCE.nextBoolean() ? result : result.negate(); } /** * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of * lower magnitude. */ static BigInteger randomBigInteger(int numBits) { while (true) { if (RANDOM_SOURCE.nextBoolean()) {
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Dec 04 17:37:03 UTC 2017 - 4.1K bytes - Viewed (0)