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ci/devinfra/docker_windows/Dockerfile
"--quiet", "--wait", "--nocache", \ "--add", "Microsoft.VisualStudio.Workload.VCTools", \ "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", \ "--add", "Microsoft.VisualStudio.Component.Windows10SDK.19041" -Wait; \ Start-Process -FilePath C:/TEMP/vs_buildtools.exe -ArgumentList "--installPath", "C:/VS", \ "--quiet", "--wait", "--nocache", "--includeOptional", \
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Fri Aug 18 17:24:20 GMT 2023 - 13.6K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib.cc
StatusPtr first_bad_status(nullptr); for (const auto& dt : device_threads_) { StatusPtr async_wait_status(TF_NewStatus()); dt->AsyncWait(async_wait_status.get()); // Prefer non cancelled errors to uncover real failures. if (TF_GetCode(async_wait_status.get()) != TF_OK && (first_bad_status == nullptr || TF_GetCode(first_bad_status.get()) == TF_CANCELLED)) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Feb 09 07:47:20 GMT 2024 - 25.4K bytes - Viewed (1) -
tensorflow/c/eager/c_api_experimental_test.cc
// // 1. Create a variable on `remote_device`, using `ctx_0`. TFE_TensorHandle* handle_0 = CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var"); // 2. Wait for `var` to be created and initialized on the worker. TF_Status* status = TF_NewStatus(); TFE_ContextAsyncWait(ctx_0, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TF_DeleteStatus(status);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 03:14:26 GMT 2023 - 31.5K bytes - Viewed (1) -
tensorflow/c/eager/c_api_test.cc
// 1. Create a variable on `remote_device`, using `ctx_0`. TFE_TensorHandle* handle_0 = CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var2"); // 2. Wait for `var2` to be created and initialized on the worker. TF_Status* status = TF_NewStatus(); TFE_ContextAsyncWait(ctx_0, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TF_DeleteStatus(status);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 20:50:20 GMT 2023 - 94.6K bytes - Viewed (1) -
.github/workflows/issue-on-pr-rollback.yml
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Sep 12 16:40:29 GMT 2023 - 1.5K bytes - Viewed (0) -
configure.py
proc = subprocess.Popen( [environ_cp['PYTHON_BIN_PATH'], paths[0]] + cuda_libraries, stdout=subprocess.PIPE, env=maybe_encode_env(environ_cp)) if proc.wait(): # Errors from find_cuda_config.py were sent to stderr. print('Asking for detailed CUDA configuration...\n') return False config = dict(
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1) -
.github/workflows/trusted-partners.yml
const username = context.payload.pull_request.user.login; const domain = await script.get_email_domain({github, username}); switch(domain) { case "intel.com": console.log(await script.filter({github, context, domain})); break; case "apple.com": console.log(await script.filter({github, context, domain})); break; case "nvidia.com":
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Sep 12 14:49:29 GMT 2023 - 2.4K bytes - Viewed (0) -
RELEASE.md
`experimental_default_delegate_latest_features` to enable all default delegate features. * `tf.data` * Add `wait` to `tf.data.Dataset.load`. If `True`, for snapshots written with `distributed_save`, it reads the snapshot while it is being written. For snapshots written with regular `save`, it waits for the snapshot until it's finished. The default is `False` for backward compatibility. Users of
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.github/workflows/trusted_partners.js
} const resp_label = await github.rest.issues.addLabels({ issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, labels: labels }); if (resp_label.status >= 400) { console.log(resp_label); throw "Error adding labels to PR"; } if (assignees.length > 0) { const resp_assign = await github.rest.issues.addAssignees({
JavaScript - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Feb 07 13:52:04 GMT 2023 - 4.5K bytes - Viewed (0) -
tensorflow/c/eager/tape.h
// functions (and hence the tensors they keep alive). Instead, everything // is deleted in ~GradientTape. Persistent GradientTapes are useful when // users want to compute multiple gradients over the same tape. explicit GradientTape(bool persistent) : persistent_(persistent) {} ~GradientTape() { for (const auto& pair : op_tape_) {
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 02 12:40:29 GMT 2024 - 47.2K bytes - Viewed (1)