if b1 != b {
		t.Error("NewReaderSize did not detect underlying Reader")
	}
	// Does it wrap if existing buffer is too small?
	b2 := NewReaderSize(b, 2*BufSize)
	if b2 == b {
		t.Error("NewReaderSize did not enlarge buffer")
	}
}

func TestNewWriterSizeIdempotent(t *testing.T) {
	const BufSize = 1000
	b := NewWriterSize(new(bytes.Buffer), BufSize)
	// Does it recognize itself?
	b1 := NewWriterSize(b, BufSize)

  TF_TString* data = static_cast<TF_TString*>(TF_TensorData(t));
  for (int i = 0; i < batch_size; ++i) {
    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());
  }

		}
	}
	return hdr, &tr.blk, p.err
}

// readOldGNUSparseMap reads the sparse map from the old GNU sparse format.
// The sparse map is stored in the tar header if it's small enough.
// If it's larger than four entries, then one or more extension headers are used
// to store the rest of the sparse map.
//
// The Header.Size does not reflect the size of any extended headers used.

 *  Fix: Attempt to read the response even if sending the request failed. This makes it possible
    to handle response statuses like `HTTP/1.1 431 "Request Header Fields Too Large`.

 *  Fix: Handle multiple 1xx responses.

 *  Fix: Address a performance bug in our internal task runner. We had a race condition that could

                    logger.warn("Failed to write cache: sessionId={}, responseData={}", sessionId, responseData, e);
                }
            } else {
                logger.debug("Content size is too large({} > {}): {}", responseData.getContentLength(),
                        fessConfig.getCrawlerDocumentCacheMaxSizeAsInteger(), responseData.getUrl());
            }
        }
        // digest

Comme les paramètres sont décrits avec des types TypeScript (similaires aux type hints de Python), la prise en charge
par l'éditeur est assez bonne.

	if err != nil {
		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}

	// We have to adjust the size of encrypted parts since encrypted parts
	// are slightly larger due to encryption overhead.
	// Further, we have to adjust the ETags of parts when using SSE-S3.
	// Due to AWS S3, SSE-S3 encrypted parts return the plaintext ETag

## Running on Startup and Restarts { #running-on-startup-and-restarts }

There is normally another tool in charge of **starting and running** your container.

It could be **Docker** directly, **Docker Compose**, **Kubernetes**, a **cloud service**, etc.

- Fix: incorrect max azure disk max count ([#92331](https://github.com/kubernetes/kubernetes/pull/92331), [@andyzhangx](https://github.com/andyzhangx)) [SIG Cloud Provider and Storage]
- Fixed bug in reflector that couldn't recover from "Too large resource version" errors with API servers 1.17.0-1.18.5 ([#94316](https://github.com/kubernetes/kubernetes/pull/94316), [@janeczku](https://github.com/janeczku)) [SIG API Machinery]

        protected String similarDocHash;
        /** Type of search request */
        protected SearchRequestType searchRequestType = SearchRequestType.SEARCH;
        /** Whether scroll mode is enabled for large result sets */
        protected boolean isScroll = false;
        /** Track total hits configuration */
        protected String trackTotalHits = null;
        /** Minimum score threshold for results */