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Results 1 - 6 of 6 for Completed (1.3 sec)

  1. tensorflow/c/eager/c_api_experimental.h

    TF_CAPI_EXPORT extern void TFE_ContextAsyncWait(TFE_Context* ctx,
                                                    TF_Status* status);
    
    // This function will block till the operation that produces `h` has
    // completed. This is only valid on local TFE_TensorHandles. The pointer
    // returned will be on the device in which the TFE_TensorHandle resides (so e.g.
    // for a GPU tensor this will return a pointer to GPU memory). The pointer is
    C
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Wed Feb 21 22:37:46 GMT 2024
    - 39.5K bytes
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  2. tensorflow/c/eager/c_api.cc

      buf->Unref();
      return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(
          std::move(t), device, device, context));
    }
    
    // This function will block till the operation that produces `h` has
    // completed. This is only valid on local TFE_TensorHandles. Returns the size in
    // bytes of the memory pointed to by the device pointer returned above.
    size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle* h,
    C++
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Tue Mar 12 20:00:09 GMT 2024
    - 43.9K bytes
    - Viewed (2)
  3. tensorflow/c/eager/parallel_device/parallel_device_lib.cc

      if (TF_GetCode(status) != TF_OK) {
        std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> await_status(
            TF_NewStatus(), TF_DeleteStatus);
        // Wait until all pending nodes have completed since they may have a
        // reference to default_cancellation_manager_. We ignore the status return
        // since we already have a bad status to propagate.
        TFE_ContextAsyncWait(context, await_status.get());
    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)
  4. RELEASE.md

        on Ampere based GPUs. TensorFloat-32, or TF32 for short, is a math mode for
        NVIDIA Ampere based GPUs and is enabled by default.
    
    *   A major refactoring of the internals of the Keras Functional API has been
        completed, that should improve the reliability, stability, and performance
        of constructing Functional models.
    
    *   Keras mixed precision API
    Plain Text
    - Registered: Tue May 07 12:40:20 GMT 2024
    - Last Modified: Mon Apr 29 19:17:57 GMT 2024
    - 727.7K bytes
    - Viewed (8)
  5. .bazelrc

    # These you may need to change for your own GCP project.
    common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance
    
    # TODO(kanglan): Remove it after toolchain update is complete.
    build:rbe_linux_cpu_old --config=rbe_linux
    build:rbe_linux_cpu_old --host_crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
    Plain Text
    - Registered: Tue May 07 12:40:20 GMT 2024
    - Last Modified: Thu May 02 19:34:20 GMT 2024
    - 52.8K bytes
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  6. configure.py

      write_to_bazelrc('test --test_size_filters=small,medium')
    
      # Each instance of --test_tag_filters or --build_tag_filters overrides all
      # previous instances, so we need to build up a complete list and write a
      # single list of filters for the .bazelrc file.
    
      # Filters to use with both --test_tag_filters and --build_tag_filters
      test_and_build_filters = ['-benchmark-test', '-no_oss', '-oss_excluded']
    Python
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Mon Apr 15 18:25:36 GMT 2024
    - 53.8K bytes
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