### Read Heroes { #read-heroes }

We can **read** `Hero`s from the database using a `select()`. We can include a `limit` and `offset` to paginate the results.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[48:55] hl[51:52,54] *}

### Read One Hero { #read-one-hero }

We can **read** a single `Hero`.

//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.
//   - The number of `input_tensors` should be the same as the number of items
//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(

				}
				if len(incorrectConfigs) > 0 {
					logger.Info(fmt.Sprintf("Following servers have mismatching configuration %s", incorrectConfigs))
				}
				retries = 0 // reset to log again after 20 retries.
			}
			offlineEndpoints = nil
			incorrectConfigs = nil
		}
	}
	return nil
}

///

/// tip | Astuce

Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning.

///

### Déclarer un paramètre de chemin

        val testFramework = if (modularization == ModularizationOption.WITH_LIBRARY_PROJECTS) BuildInitTestFramework.JUNIT_JUPITER else descriptor.defaultTestFramework

        // clear the target directory to remove renamed files and reset the README file
        target.asFile.deleteRecursively()

				p.buf[bufIdx] = make([]byte, p.shardSize)
			}
			// For the last shard, the shardsize might be less than previous shard sizes.
			// Hence the following statement ensures that the buffer size is reset to the right size.
			p.buf[bufIdx] = p.buf[bufIdx][:p.shardSize]
			n, err := rr.ReadAt(p.buf[bufIdx], p.offset)
			if err != nil {
				switch {
				case errors.Is(err, errFileNotFound):

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}


/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

### Einen *Pfad-Parameter* deklarieren { #declare-a-path-parameter }

STATUS=$? ; until [ $STATUS = 0 ] do ATTEMPTS=`expr $ATTEMPTS + 1` ; echo \"Failed attempts: $ATTEMPTS\" ; if [ $ATTEMPTS -gt $LIMIT ]; then exit 1 ; fi ; sleep 2 ; # 1 second intervals between attempts $MC_COMMAND ; STATUS=$? ; done ; set -e ; # reset `e` as active return 0 } # checkBucketExists ($bucket) # Check if the bucket exists, by using the exit code of `mc ls` checkBucketExists() { BUCKET=$1 CMD=$(${MC} ls myminio/$BUCKET > /dev/null 2>&1) return $? } # createBucket ($bucket, $policy, $purge)...

STATUS=$? ; until [ $STATUS = 0 ] do ATTEMPTS=`expr $ATTEMPTS + 1` ; echo \"Failed attempts: $ATTEMPTS\" ; if [ $ATTEMPTS -gt $LIMIT ]; then exit 1 ; fi ; sleep 2 ; # 1 second intervals between attempts $MC_COMMAND ; STATUS=$? ; done ; set -e ; # reset `e` as active return 0 } # checkBucketExists ($bucket) # Check if the bucket exists, by using the exit code of `mc ls` checkBucketExists() { BUCKET=$1 CMD=$(${MC} ls myminio/$BUCKET > /dev/null 2>&1) return $? } # createBucket ($bucket, $policy, $purge)...

	}

	// However many we ask, versions must exist on ~50%
	listingQuorum := (set.setDriveCount + 1) / 2

	// How to resolve partial results.
	resolver := metadataResolutionParams{
		dirQuorum: listingQuorum, // make sure to capture all quorum ratios
		objQuorum: listingQuorum, // make sure to capture all quorum ratios
		bucket:    bucketName,
	}