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src/index/suffixarray/sais2.go
} } goto Same } New: id++ lastPos = j lastLen = n Same: sa[j/2] = int32(id) } return id } func assignID_64(text []int64, sa []int64, numLMS int) int { id := 0 lastLen := int64(-1) // impossible lastPos := int64(0) for _, j := range sa[len(sa)-numLMS:] { // Is the LMS-substring at index j new, or is it the same as the last one we saw?
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Mar 18 23:57:18 UTC 2024 - 52.3K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/userguide/authoring-builds/gradle-properties/working_with_files.adoc
Sometimes it's desirable to recreate archives exactly the same, byte for byte, on different machines. You want to be sure that building an artifact from source code produces the same result no matter when and where it is built. This is necessary for projects like https://reproducible-builds.org/[reproducible-builds.org].
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Wed Apr 24 04:19:09 UTC 2024 - 70.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/while_to_map_fn.mlir
// CHECK: tf_mlrt.tf_map_fn // CHECK-SAME: ([[max_iter]], [[tensor_list]], [[max_iter]], [[elems]], %arg0, %arg1) // CHECK-SAME: {body_fn = @"map/while_body/MapFnBody", num_tensor_list_or_flow_in = 1 : i32} // CHECK-NOT: tf.while
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 06:40:22 UTC 2024 - 68.6K bytes - Viewed (0) -
platforms/software/dependency-management/src/test/groovy/org/gradle/api/internal/artifacts/configurations/DefaultConfigurationSpec.groovy
0 * resolver._ config.state == RESOLVED // We get back the same resolution results previousResolutionResult == nextResolutionResult // We get back the same resolved configuration previousResolvedConfiguration == nextResolvedConfiguration // And the same files previousFiles == nextFiles }
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu May 23 17:30:13 UTC 2024 - 64.8K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/userguide/optimizing-performance/incremental_build.adoc
the outputs of tasks when selecting the next task to run and will avoid concurrent execution of tasks that write to the same output directory. Similarly, Gradle will use the information about what files a task destroys (e.g. specified by the `Destroys` annotation) and avoid running a task that removes a set of files while another task is running that consumes or creates those same files (and vice versa). It can also determine that a task that creates a set of files has already run and that a task...
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Wed Jan 24 23:14:04 UTC 2024 - 63.9K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass.cc
// the same cluster by the clustering algorithm then this function will return // the same Cluster instance for N1 and N2. // // Returns nullptr if `n` is not a compilation candidate. Cluster* GetClusterForNode(Node* n) { return cluster_for_node_[n->id()].Get(); } // Returns the cluster for a node in `cycles_graph_`. This uses the same
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 85.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
_Device assignment in TF dialect using the device specified in the function attribute._ ### `-tf-device-cluster-formation` _Form clusters from instructions assigned to same device_ Clusters operations with the same device assignment id. For each cluster, creates a "tf_device.device_launch" op with a Region containing the ops in each cluster and replaces the ops with the new launch op.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/userguide/api/kotlin_dsl.adoc
[[sec:kotlin_using_standard_api]] === Understanding what to do when type-safe model accessors are not available Consider the sample build script shown above that demonstrates the use of type-safe accessors. The following sample is exactly the same except that is uses the `apply()` method to apply the plugin.
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Mon Apr 22 20:16:10 UTC 2024 - 55.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/lower_static_tensor_list.cc
} else { return matchAndRewriteImplWithSliceAndConcat(op, adaptor, rewriter); } } // This function rewrites the original op into a series of slice and concat op // to produce the same result. It first slices the first `$index` rows. Then // expands the dimension of the `$item`, followed by another slice of the // remaining rows starting from `$index` + 1. Lastly it concatenates the // three parts together.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 70.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
%conv = "tfl.conv_2d"(%input, %weight, %bias) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3xf32>, tensor<32x3x3x3xf32>, tensor<32xf32>) -> tensor<1x112x112x32xf32> func.return %conv : tensor<1x112x112x32xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0)