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Results 1 - 5 of 5 for pseudos (0.05 sec)
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src/cmd/asm/internal/asm/asm.go
return false } return true } // evalInteger evaluates an integer constant for a pseudo-op. func (p *Parser) evalInteger(pseudo string, operands []lex.Token) int64 { addr := p.address(operands) return p.getConstantPseudo(pseudo, &addr) } // validImmediate checks that addr represents an immediate constant. func (p *Parser) validImmediate(pseudo string, addr *obj.Addr) bool {
Registered: Tue Sep 09 11:13:09 UTC 2025 - Last Modified: Tue Aug 05 17:31:25 UTC 2025 - 26.2K bytes - Viewed (0) -
okhttp/src/commonJvmAndroid/kotlin/okhttp3/internal/connection/ConnectPlan.kt
} catch (e: ConnectException) { throw ConnectException("Failed to connect to ${route.socketAddress}").apply { initCause(e) } } // The following try/catch block is a pseudo hacky way to get around a crash on Android 7.0 // More details: // https://github.com/square/okhttp/issues/3245 // https://android-review.googlesource.com/#/c/271775/ try {
Registered: Fri Sep 05 11:42:10 UTC 2025 - Last Modified: Thu Jul 31 04:18:40 UTC 2025 - 18.6K bytes - Viewed (0) -
android/guava-tests/test/com/google/common/math/IntMathTest.java
// Check the first 100,000 integers for (int i = 0; i < 100000; i++) { assertEquals(LongMath.isPrime(i), IntMath.isPrime(i)); } // Then check 1000 deterministic pseudo-random int values. Random rand = new Random(1); for (int i = 0; i < 1000; i++) { int n = rand.nextInt(Integer.MAX_VALUE); assertEquals(LongMath.isPrime(n), IntMath.isPrime(n)); } }
Registered: Fri Sep 05 12:43:10 UTC 2025 - Last Modified: Mon Aug 11 19:31:30 UTC 2025 - 24.1K bytes - Viewed (0) -
cmd/erasure-sets.go
- Any JBOD inconsistent - return failure - Some are corrupt (missing format.json) - Any unrecognized disks - return failure No read quorum ----------------- failure for all cases. // Pseudo code for managing `format.json`. // Generic checks. if (no quorum) return error if (any disk is corrupt) return error // Always error if (jbod inconsistent) return error // Always error.
Registered: Sun Sep 07 19:28:11 UTC 2025 - Last Modified: Fri Aug 29 02:39:48 UTC 2025 - 37K bytes - Viewed (1) -
RELEASE.md
* Clean up `BatchNormalization` layer's `trainable` property to act like standard python state when it's used inside `tf.functions` (frozen at tracing time), instead of acting like a pseudo-variable whose updates *kind of sometimes* get reflected in already-traced `tf.function` traces. * Add the `Conv1DTranspose` layer. * Refine the semantics of `SensitivitySpecificityBase` derived metrics. See
Registered: Tue Sep 09 12:39:10 UTC 2025 - Last Modified: Mon Aug 18 20:54:38 UTC 2025 - 740K bytes - Viewed (2)