* cancelled.
     *
     * <p>If the combiningCallable throws an {@code ExecutionException}, the cause of the thrown
     * {@code ExecutionException} will be extracted and used as the failure of the derived step.
     */
    public <V extends @Nullable Object> ClosingFuture<V> call(
        final CombiningCallable<V> combiningCallable, Executor executor) {
      Callable<V> callable =

		objInfo.ETag = origETag
		enqueueTransitionImmediate(objInfo, lcEventSrc_s3PutObject)
		os.Sweep()
	}
}

// PutObjectExtractHandler - PUT Object extract is an extended API
// based off from AWS Snowball feature to auto extract compressed
// stream will be extracted in the same directory it is stored in
// and the folder structures will be built out accordingly.

        description: Annotated[
            Optional[str],
            Doc(
                """
                A description for the *path operation*.

                If not provided, it will be extracted automatically from the docstring
                of the *path operation function*.

                It can contain Markdown.

                It will be added to the generated OpenAPI (e.g. visible at `/docs`).

}

def ExtractTPUCopyWithDynamicShapeOpPass : Pass<"tf-extract-tpu-copy-with-dynamic-shape-op", "mlir::func::FuncOp"> {
  let summary = "Extract the TPUCopyWithDynamicShapeOp out of the host launch and place it on device launch";

  let description = [{
    This pass looks for TPUCopyWithDynamicShapeOp which wraps in a
    `tf_device.launch` with host device attribute. It extracts the ops and wrap

	}
	if extraNames := extractedNames.Difference(expectedSecretPaths); len(extraNames) > 0 {
		t.Logf("Extra secret names:\n%s", strings.Join(sets.List[string](extraNames), "\n"))
		t.Error("Extra secret names extracted. Verify VisitPodSecretNames() is correctly extracting secret names")
	}

	// emptyPod is a stub containing empty object names
	emptyPod := &api.Pod{
		Spec: api.PodSpec{
			Containers: []api.Container{{

      slice_begin, slice_end, slice_stride);
  return true;
}

OpFoldResult StridedSliceOp::fold(FoldAdaptor) {
  // Fold StridedSlice operation if it extracts statically known dimensions.
  //
  // For example,
  //
  //   %shape  = tf.Shape(%arg)                   // %arg: tensor<?x2x3x1xf32>
  //   %height = tf.StridedSlice(%shape, 1, 2, 1)
  //

                                PatternRewriter& rewriter) const override;
};

LogicalResult FoldConstantCaseOp::matchAndRewrite(
    TF::CaseOp op, PatternRewriter& rewriter) const {
  // Extract the constant cond value.
  DenseIntElementsAttr branch;
  if (!matchPattern(op.getBranchIndex(), m_Constant(&branch))) return failure();

  int index = *branch.getValues<int>().begin();

	response, err = s.client.Do(request)
	c.Assert(err, nil)
	// assert the http response status code.
	c.Assert(response.StatusCode, http.StatusOK)

	var buffer bytes.Buffer
	// extract the body of the response.
	responseBody, err := io.ReadAll(response.Body)
	c.Assert(err, nil)
	// assert the http response body content.
	c.Assert(true, bytes.Equal(responseBody, buffer.Bytes()))
}

  }
  if (padding_attr == tflite::Padding_VALID) {
    return kTfLitePaddingValid;
  }

  return inst->emitOpError() << "Invalid padding attribute: " << padding,
         std::nullopt;
}

// Extracts TfLitePoolParams from a TFL custom op.
// Template parameter, TFLOp, should be a TFL custom op containing attributes
// generated from TfLitePoolParams.
// Returns std::nullopt if conversion fails.
template <typename TFLOp>

  if (failed(InferShapeForFunctionReturnType(func))) return false;

  return false;
}

bool ShapeInference::InferShapeForXlaHostComputeMlir(
    _XlaHostComputeMlirOp host_compute_op) {
  // Extract the module and function.
  // The '_XlaHostComputeMlir` verifier verifies that `host_mlir_module`
  // attribute is well formed, so we just return in case of an error in