- Sort Score
- Result 10 results
- Languages All
Results 21 - 30 of 41 for permutation (0.19 sec)
-
tensorflow/compiler/mlir/lite/transforms/optimize_batch_matmul.cc
// Create a 1D I32 tensor for representing the dimension permutation. auto permuation_tensor_type = RankedTensorType::get({input_rank}, rewriter.getIntegerType(32)); llvm::SmallVector<Attribute, 4> permute; permute.reserve(input_rank); // First create an identity permutation tensor. for (int i = 0; i < input_rank; i++) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.6K bytes - Viewed (0) -
src/math/rand/example_test.go
show("Intn(10)", r.Intn(10), r.Intn(10), r.Intn(10)) show("Int31n(10)", r.Int31n(10), r.Int31n(10), r.Int31n(10)) show("Int63n(10)", r.Int63n(10), r.Int63n(10), r.Int63n(10)) // Perm generates a random permutation of the numbers [0, n). show("Perm", r.Perm(5), r.Perm(5), r.Perm(5)) // Output: // Float32 0.2635776 0.6358173 0.6718283 // Float64 0.628605430454327 0.4504798828572669 0.9562755949377957
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Oct 26 16:24:57 UTC 2022 - 4.2K bytes - Viewed (0) -
pkg/config/analysis/analyzers/webhook/webhook.go
for rev := range revisions { for _, base := range getObjectLabels() { base[label.IoIstioRev.Name] = rev objectLabels = append(objectLabels, base) } } // For each permutation, we check which webhooks it matches. It must match exactly 0 or 1! for _, nl := range namespaceLabels { for _, ol := range objectLabels { matches := sets.New[string]() for name, whs := range webhooks {
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Sun May 05 03:44:57 UTC 2024 - 6K bytes - Viewed (0) -
staging/src/k8s.io/apimachinery/pkg/util/rand/rand.go
// Seed seeds the rng with the provided seed. func Seed(seed int64) { rng.Lock() defer rng.Unlock() rng.rand = rand.New(rand.NewSource(seed)) } // Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n) // from the default Source. func Perm(n int) []int { rng.Lock() defer rng.Unlock() return rng.rand.Perm(n) } const (
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Thu Oct 11 11:02:01 UTC 2018 - 3.5K bytes - Viewed (0) -
testing/internal-integ-testing/src/main/groovy/org/gradle/integtests/fixtures/executer/TaskOrderSpecs.java
import java.util.Set; /** * Provides common assertions for querying task order. * * An 'any' rule asserts that all of the specified tasks occur in any order. * * any(':a', ':b', ':c') would match on any permutation of ':a', ':b', ':c'. * * An 'exact' rule asserts that all of the specified tasks occur in the order * provided. Note that other tasks may appear - it only verifies that the * given tasks occur in order. *
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 07:21:38 UTC 2024 - 5.1K bytes - Viewed (0) -
src/math/rand/v2/example_test.go
show("IntN(10)", r.IntN(10), r.IntN(10), r.IntN(10)) show("Int32N(10)", r.Int32N(10), r.Int32N(10), r.Int32N(10)) show("Int64N(10)", r.Int64N(10), r.Int64N(10), r.Int64N(10)) // Perm generates a random permutation of the numbers [0, n). show("Perm", r.Perm(5), r.Perm(5), r.Perm(5)) // Output: // Float32 0.95955694 0.8076733 0.8135684 // Float64 0.4297927436037299 0.797802349388613 0.3883664855410056
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Oct 30 17:09:26 UTC 2023 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_subgraphs_pass.h
// 'input_permutation' is a mapping from old argument numbers to new argument // numbers, whereas 'output_permutation' is the same for outputs. Both // 'input_permutation' and 'output_permutation' are initialized to the identity // permutation. 'nodedef' is the NodeDef for the call to the function under // construction, provided to allow additional attributes to be set. // The rewrite may also change the NodeDef's operator name, and that
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 12 03:59:36 UTC 2022 - 4.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/g3doc/space_to_depth.md
to do the transform. There are three parts of automatically space to depth transformation: 1. Transform input on the host. Space-to-depth performs the following permutation, which is equivalent to `tf.nn.space_to_depth`. ```python images = tf.reshape(images, [batch, h // block_size, block_size, w // block_size, block_size, c])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Oct 24 02:51:43 UTC 2020 - 8.3K bytes - Viewed (0) -
src/io/pipe_test.go
t.Errorf("Write() = (%d, %v); want (%d, nil)", n, err, len(input)) } } // Since each read is independent, the only guarantee about the output // is that it is a permutation of the input in readSized groups. got := make([]byte, 0, count*len(input)) for i := 0; i < cap(c); i++ { got = append(got, (<-c)...) } got = sortBytesInGroups(got, readSize)
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu May 23 01:00:11 UTC 2024 - 9K bytes - Viewed (0) -
staging/src/k8s.io/apiserver/pkg/util/shufflesharding/shufflesharding_test.go
fallingFactorial := ff(test.deckSize, test.handSize) permutations := ff(test.handSize, test.handSize) allCoordinateCount := fallingFactorial / permutations nff := float64(test.hashMax) / float64(fallingFactorial) minCount := permutations * int(math.Floor(nff)) maxCount := permutations * int(math.Ceil(nff)) aHand := make([]int, test.handSize) for i := 0; i < test.hashMax; i++ {
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Mon Jan 25 06:44:08 UTC 2021 - 6.7K bytes - Viewed (0)