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src/runtime/tracestring.go
// traceStringTable is map of string -> unique ID that also manages // writing strings out into the trace. type traceStringTable struct { // lock protects buf. lock mutex buf *traceBuf // string batches to write out to the trace. // tab is a mapping of string -> unique ID. tab traceMap } // put adds a string to the table, emits it, and returns a unique ID for it.
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Apr 15 17:03:35 UTC 2024 - 2.4K bytes - Viewed (0) -
src/crypto/cipher/cfb.go
if x.outUsed == len(x.out) { x.b.Encrypt(x.out, x.next) x.outUsed = 0 } if x.decrypt { // We can precompute a larger segment of the // keystream on decryption. This will allow // larger batches for xor, and we should be // able to match CTR/OFB performance. copy(x.next[x.outUsed:], src) } n := subtle.XORBytes(dst, src, x.out[x.outUsed:]) if !x.decrypt { copy(x.next[x.outUsed:], dst) }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Oct 13 17:09:47 UTC 2023 - 2K bytes - Viewed (0) -
src/runtime/traceexp.go
// Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package runtime // traceExpWriter is a wrapper around trace writer that produces traceEvExperimentalBatch // batches. This means that the data written to the writer need not conform to the standard // trace format. type traceExpWriter struct { traceWriter exp traceExperiment }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 17:47:01 UTC 2024 - 2.4K bytes - Viewed (0) -
pilot/pkg/xds/discovery_test.go
expect(0, 0) }, }, { name: "Should send full updates in batches", test: func(updateCh chan *model.PushRequest, expect func(partial, full int32)) { updateCh <- &model.PushRequest{Full: true} updateCh <- &model.PushRequest{Full: true} expect(0, 1) }, }, { name: "Should send full updates in batches, partial updates immediately",
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Tue Apr 30 00:26:45 UTC 2024 - 9.2K bytes - Viewed (0) -
subprojects/core/src/main/java/org/gradle/internal/buildtree/IntermediateBuildActionRunner.java
import org.gradle.internal.operations.RunnableBuildOperation; import java.util.ArrayList; import java.util.Collection; import java.util.List; import java.util.function.Supplier; /** * Executor for batches of intermediate build actions that can be initiated * from the top-level build action or from model builders. * <p> * All actions are always executed, and <b>may run in {@link #isParallel() parallel}</b>.
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Feb 08 07:46:55 UTC 2024 - 4.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tfrt_fallback/batch_function_fallback_benchmark_test.cc
func->Execute(exec_ctx, arguments.values(), results); host->Await(results); for (auto& result : results) { EXPECT_FALSE(result->IsError()); } } // Runs a BEF function that batches a function that does nothing just to measure // the runtime overhead. The BEF function signature is adapted from a real model // and is useful for benchmarking ops with large attributes and many // input/output.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 08 08:08:48 UTC 2023 - 6.3K bytes - Viewed (0) -
platforms/software/dependency-management/src/testFixtures/groovy/org/gradle/resolve/scenarios/VersionRangeResolveTestScenarios.groovy
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Tue Oct 10 21:10:11 UTC 2023 - 27.8K bytes - Viewed (0) -
platforms/core-runtime/daemon-services/src/test/groovy/org/gradle/internal/daemon/clientinput/StdInStreamTest.groovy
thread.block() stream.received(bytes) } then: 1 * dispatch.onOutput({ it instanceof ReadStdInEvent }) >> { instant.requested } } def "can read multiple batches of input from client"() { def dispatch = Mock(OutputEventListener) def stream = new StdInStream(dispatch) def text1 = "some text" def bytes1 = text1.bytes def text2 = "more"
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Wed May 15 19:51:37 UTC 2024 - 5.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/reconfig_batch_op.mlir
// RUN: tf-tfrt-opt -split-input-file -tfrt-reconfig-batch-op="tfrt-min-num-batch-threads=2 tfrt-min-max-enqueued-batches=3" %s | FileCheck %s --dump-input=always // ----- // The num_batch_threads is lowered bound to 2 from the original attribute of 1 // CHECK-LABEL: func private @batched_function func.func private @batched_function(%arg0: tensor<1x3xf32>) -> tensor<1x3xf32> { %2 = "tf.Identity"(%arg0) : (tensor<1x3xf32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 17:38:34 UTC 2024 - 5.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/nms_utils.cc
// The TFLite fused op does not support batching yet. // TODO(b/158709815): Add support for batches with padded NMS. auto boxes_type = mlir::dyn_cast<RankedTensorType>(func_.getFunctionType().getInput(0)); if (boxes_type == nullptr || !boxes_type.hasRank() || boxes_type.getRank() != 2) { return func_.emitWarning() << "TFLite does not support batched input for " "non_max_suppression_padded"; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.1K bytes - Viewed (0)