},
		{
			name: "valid resources from file",
			args: []string{"--filename", validFilenameYAML},
		},
		{
			name:      "extra args",
			args:      []string{"--filename", validFilenameYAML, "extra-arg"},
			wantError: true,
		},
		{
			name:      "invalid resources from file",
			args:      []string{"--filename", invalidFilenameYAML},
			wantError: true,
		},
		{
			name:      "invalid filename",

				return nil
			}

			readers, err := gatherFiles(cmd, args)
			if err != nil {
				return err
			}
			cancel := make(chan struct{})

			// We use the "namespace" arg that's provided as part of root istioctl as a flag for specifying what namespace to use
			// for file resources that don't have one specified.
			selectedNamespace = ctx.Namespace()
			if useKube {

			// Otherwise ignored.
			continue
		}
		return tok
	}
}

// line consumes a single assembly line from p.lex of the form
//
//	{label:} WORD[.cond] [ arg {, arg} ] (';' | '\n')
//
// It adds any labels to p.pendingLabels and returns the word, cond,
// operand list, and true. If there is an error or EOF, it returns
// ok=false.
//
// line may reuse the memory from scratch.

        before

### Breaking Changes

*   `tf.summary.trace_on` now takes a `profiler_outdir` argument. This must be
    set if `profiler` arg is set to `True`.

    *   `tf.summary.trace_export`'s `profiler_outdir` arg is now a no-op.
        Enabling the profiler now requires setting `profiler_outdir` in
        `trace_on`.

*   `tf.estimator`

    *   The tf.estimator API is removed.

  EXPECT_EQ(TF_CANCELLED, TF_GetCode(s));
  EXPECT_EQ(string("cancel"), TF_Message(s));
  TF_DeleteStatus(s);
}

void Deallocator(void* data, size_t, void* arg) {
  tensorflow::cpu_allocator()->DeallocateRaw(data);
  *reinterpret_cast<bool*>(arg) = true;
}

TEST(CAPI, Tensor) {
  const int num_bytes = 6 * sizeof(float);
  float* values =
      reinterpret_cast<float*>(tensorflow::cpu_allocator()->AllocateRaw(

    assertEquals(reserialized, substitute(reserialized, String.class));
  }

  private static <T, X> TypeToken<T> substitute(TypeToken<T> type, Class<X> arg) {
    return type.where(new TypeParameter<X>() {}, arg);
  }

  private abstract static class ToReproduceGenericSignatureFormatError<V> {
    private abstract class BaseOuter {
      abstract class BaseInner {}
    }

	<remote>, so that C code can refer to it by that name. This
	mechanism makes it possible for C code to call back into Go or
	to share Go's data.

//go:cgo_ldflag "<arg>"

	In external linking mode, invoke the host linker (usually gcc)
	with "<arg>" as a command-line argument following the .o files.
	Note that the arguments are for "gcc", not "ld".

	Example:
	//go:cgo_ldflag "-lpthread"

    TFE_Context* ctx, const char* device_name, TF_DataType, const int64_t* dims,
    int num_dims, void* data, size_t len,
    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg, TF_Status* status);

// Retrieves the address space (i.e. job, replia, task) of the local host and
// saves it in the buffer.
TF_CAPI_EXPORT extern void TFE_HostAddressSpace(TFE_Context* ctx,

TFE_TensorHandle* TFE_NewTensorHandleFromDeviceMemory(
    TFE_Context* ctx, const char* device_name, TF_DataType dtype,
    const int64_t* dims, int num_dims, void* data, size_t len,
    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg, TF_Status* status) {
  tensorflow::Device* device = nullptr;
  tensorflow::EagerContext* context =
      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));

    assertEquals(reserialized, substitute(reserialized, String.class));
  }

  private static <T, X> TypeToken<T> substitute(TypeToken<T> type, Class<X> arg) {
    return type.where(new TypeParameter<X>() {}, arg);
  }

  private abstract static class ToReproduceGenericSignatureFormatError<V> {
    private abstract class BaseOuter {
      abstract class BaseInner {}
    }