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3. This `yield from` tells the function to iterate over that thing named `file_like`. And then, for each part iterated, yield that part as coming from this generator function.

    So, it is a generator function that transfers the "generating" work to something else internally.

    By doing it this way, we can put it in a `with` block, and that way, ensure that it is closed after finishing.

!!! tip

    distributing datasets. For this to work, the dispatcher's `work_dir` must be
    accessible from workers. If the worker fails to read from the `work_dir`, it
    falls back to using RPC for dataset graph transfer.
*   Adds support for a new "distributed_epoch" processing mode. This processing
    mode distributes a dataset across all tf.data workers, instead of having
    each worker process the full dataset. See

			if data == endOfRow {
				continue RowLoop
			}
			row[x] = data + bias(x, y)
		}
	}
</pre>

<h3 id="Goto_statements">Goto statements</h3>

<p>
A "goto" statement transfers control to the statement with the corresponding label
within the same function.
</p>

<pre class="ebnf">
GotoStmt = "goto" Label .
</pre>

<pre>
goto Error
</pre>

<p>

			if data == endOfRow {
				continue RowLoop
			}
			row[x] = data + bias(x, y)
		}
	}
</pre>

<h3 id="Goto_statements">Goto statements</h3>

<p>
A "goto" statement transfers control to the statement with the corresponding label
within the same function.
</p>

<pre class="ebnf">
GotoStmt = "goto" Label .
</pre>

<pre>
goto Error
</pre>

<p>