}

	req, err := http.NewRequest(method, urlStr, nil)
	if err != nil {
		return nil, err
	}

	if body == nil {
		// this is added to avoid panic during io.ReadAll(req.Body).
		// th stack trace can be found here  https://github.com/minio/minio/pull/2074 .
		// This is very similar to https://github.com/golang/go/issues/7527.
		req.Body = io.NopCloser(bytes.NewReader([]byte("")))
	}

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// `oper` and `num_dims` with the corresponding number of dimensions. On return,
// for every i where `num_dims[i]` > 0, `dims[i]` will be an array of
// `num_dims[i]` elements. A value of -1 for `num_dims[i]` indicates that the
// i-th shape in the list is unknown.
//
// The elements of `dims` will point to addresses in `storage` which must be
// large enough to hold at least `storage_size` int64_ts.  Ideally, `num_shapes`

the constants) to the values of a list of <a href="#Constant_expressions">constant expressions</a>.
The number of identifiers must be equal
to the number of expressions, and the <i>n</i>th identifier on
the left is bound to the value of the <i>n</i>th expression on the
right.
</p>

<pre class="ebnf">
ConstDecl      = "const" ( ConstSpec | "(" { ConstSpec ";" } ")" ) .

      status->status = absl::OkStatus();
      return;
    }
    count++;
  }
  status->status = OutOfRange("Operation only has ", count,
                              " attributes, can't get the ", i, "th");
}

void TF_OperationToNodeDef(TF_Operation* oper, TF_Buffer* output_node_def,
                           TF_Status* status) {
  status->status = MessageToBuffer(oper->node.def(), output_node_def);
}

    TF_TString_Init(&data[i]);
    // The following input string length is large enough to make sure that
    // copy to tstring in large mode.
    std::string source =
        "This is the " + std::to_string(i + 1) + "th. data element\n";
    TF_TString_Copy(&data[i], source.c_str(), source.length());
  }

  TF_DeleteTensor(t);
}

}  // namespace
}  // namespace tensorflow

// TODO(josh11b): Test:

bLimbs[i] // T[n+i] = addMulVVW(T[i:n+i], aLimbs, d) // } // // where d is a digit of the multiplier, T[i:n+i] is the shifted // position of the product of that digit, and T[n+i] is the final carry. // Note that T[i] isn't modified after processing the i-th digit. // // Instead of running two loops, one for Step 1 and one for Steps 2–6, // the result of Step 1 is computed during the next loop. This is // possible because each iteration only uses T[i] in Step 2 and then // discards it in Step 6. d := bLimbs[i]...

bLimbs[i] // T[n+i] = addMulVVW(T[i:n+i], aLimbs, d) // } // // where d is a digit of the multiplier, T[i:n+i] is the shifted // position of the product of that digit, and T[n+i] is the final carry. // Note that T[i] isn't modified after processing the i-th digit. // // Instead of running two loops, one for Step 1 and one for Steps 2–6, // the result of Step 1 is computed during the next loop. This is // possible because each iteration only uses T[i] in Step 2 and then // discards it in Step 6. d := bLimbs[i]...