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docs/en/docs/tutorial/first-steps.md
Normally you use: * `POST`: to create data. * `GET`: to read data. * `PUT`: to update data. * `DELETE`: to delete data. So, in OpenAPI, each of the HTTP methods is called an "operation". We are going to call them "**operations**" too. #### Define a *path operation decorator* {* ../../docs_src/first_steps/tutorial001.py hl[6] *}
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sat Oct 26 11:48:16 UTC 2024 - 11.8K bytes - Viewed (0) -
common-protos/k8s.io/api/authorization/v1beta1/generated.proto
// The list ordering isn't significant, may contain duplicates, and possibly be incomplete. repeated NonResourceRule nonResourceRules = 2; // Incomplete is true when the rules returned by this call are incomplete. This is most commonly // encountered when an authorizer, such as an external authorizer, doesn't support rules evaluation. optional bool incomplete = 3;
Registered: Wed Nov 06 22:53:10 UTC 2024 - Last Modified: Mon Mar 11 18:43:24 UTC 2024 - 11.9K bytes - Viewed (0) -
ci/official/README.md
all scripts can use them. - `utilities/setup_docker.sh` creates a container called `tf` with all `TFCI_` variables shared to it. 3. Top-level scripts (`wheel.sh`, etc.) reference `env` variables and call `utilities/` scripts. - The `tfrun` function makes a command run correctly in Docker if Docker
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Thu Feb 01 03:21:19 UTC 2024 - 8K bytes - Viewed (0) -
tensorflow/c/eager/dlpack.cc
auto tf_dlm_type = GetDlDataType(data_type, status); if (!status->status.ok()) { return nullptr; } TensorReference tensor_ref(*tensor); // This will call buf_->Ref() auto* tf_dlm_tensor_ctx = new TfDlManagedTensorCtx(tensor_ref); tf_dlm_tensor_ctx->reference = tensor_ref; DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor;
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 12.9K bytes - Viewed (0) -
RELEASE.md
requires all optimizer variables to be created at the first `apply_gradients()` or `minimize()` call. If your workflow calls optimizer to update different parts of model in multiple stages, please call `optimizer.build(model.trainable_variables)` before the training loop. * **Performance regression on `ParameterServerStrategy`.** This could be
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Tue Oct 22 14:33:53 UTC 2024 - 735.3K bytes - Viewed (0) -
android/guava-testlib/src/com/google/common/collect/testing/google/UnmodifiableCollectionTests.java
*/ @GwtCompatible @ElementTypesAreNonnullByDefault public class UnmodifiableCollectionTests { public static void assertMapEntryIsUnmodifiable(Entry<?, ?> entry) { try { // fine because the call is going to fail without modifying the entry @SuppressWarnings("unchecked") Entry<?, @Nullable Object> nullableValueEntry = (Entry<?, @Nullable Object>) entry; nullableValueEntry.setValue(null);
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Wed Oct 30 16:15:19 UTC 2024 - 14.6K bytes - Viewed (0) -
android/guava/src/com/google/common/io/Closer.java
* try-with-resources. To get the equivalent of that, you must wrap the above code in <i>another</i> * try block in order to catch any exception that may be thrown (including from the call to {@code * close()}). * * <p>This pattern ensures the following: * * <ul> * <li>Each {@code Closeable} resource that is successfully registered will be closed later.
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Tue May 07 15:26:58 UTC 2024 - 10.4K bytes - Viewed (0) -
src/main/java/jcifs/http/NtlmHttpFilter.java
} @Override public void destroy () {} /** * This method simply calls <tt>negotiate( req, resp, false )</tt> * and then <tt>chain.doFilter</tt>. You can override and call * negotiate manually to achive a variety of different behavior. */ @Override public void doFilter ( ServletRequest request, ServletResponse response, FilterChain chain ) throws IOException, ServletException {
Registered: Sun Nov 03 00:10:13 UTC 2024 - Last Modified: Sun Jul 01 13:12:10 UTC 2018 - 14.8K bytes - Viewed (0) -
docs/de/docs/tutorial/dependencies/classes-as-dependencies.md
Der springende Punkt ist, dass eine Abhängigkeit aufrufbar („callable“) sein sollte. Ein „**Callable**“ in Python ist etwas, das wie eine Funktion aufgerufen werden kann („to call“). Wenn Sie also ein Objekt `something` haben (das möglicherweise _keine_ Funktion ist) und Sie es wie folgt aufrufen (ausführen) können: ```Python something() ``` oder ```Python
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 12K bytes - Viewed (0) -
cmd/admin-handlers-users.go
encryptedData, err := madmin.EncryptData(cred.SecretKey, data) if err != nil { writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, err), r.URL) return } writeSuccessResponseJSON(w, encryptedData) // Call hook for cluster-replication if the service account is not for a // root user. if newCred.ParentUser != globalActiveCred.AccessKey { replLogIf(ctx, globalSiteReplicationSys.IAMChangeHook(ctx, madmin.SRIAMItem{
Registered: Sun Nov 03 19:28:11 UTC 2024 - Last Modified: Thu Oct 03 23:11:02 UTC 2024 - 85.1K bytes - Viewed (0)