public:
  // Returns tensor dtype.
  virtual tensorflow::DataType DataType() const = 0;

  // Returns the status of the tensor handle. If it is a tfrt::TensorHandle,
  // the tensor handle can be an error and return non-OK status.
  virtual absl::Status TensorHandleStatus() const;

  // Returns tensor shape. If tensor has unknown rank, shape remains untouched.
  virtual absl::Status Shape(tensorflow::PartialTensorShape* shape) const = 0;

from fastapi import FastAPI
from fastapi.middleware.gzip import GZipMiddleware

app = FastAPI()

app.add_middleware(GZipMiddleware, minimum_size=1000, compresslevel=5)


@app.get("/")
async def main():

     *
     * The singleton context will use system properties for configuration as well as values specified in a file
     * specified through this <code>jcifs.properties</code> system property.
     *
     * @return a global context, initialized on first call
     */
    public static synchronized final SingletonContext getInstance() {
        if (INSTANCE == null) {
            try {

	LockingOptionsNoWait     = "NOWAIT"
)

type Locking struct {
	Strength string
	Table    Table
	Options  string
}

// Name where clause name
func (locking Locking) Name() string {
	return "FOR"
}

// Build build where clause
func (locking Locking) Build(builder Builder) {
	builder.WriteString(locking.Strength)
	if locking.Table.Name != "" {
		builder.WriteString(" OF ")

$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) # Ensure bucket exists, purging if asked to createBucket() { BUCKET=$1 POLICY=$2 PURGE=$3 VERSIONING=$4 OBJECTLOCKING=$5...

$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) # Ensure bucket exists, purging if asked to createBucket() { BUCKET=$1 POLICY=$2 PURGE=$3 VERSIONING=$4 OBJECTLOCKING=$5...

$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) # Ensure bucket exists, purging if asked to createBucket() { BUCKET=$1 POLICY=$2 PURGE=$3 VERSIONING=$4 # Purge...

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Annotated[list, Query()] = []):
    query_items = {"q": q}

from pydantic import BaseModel


def forwardref_method(input: "ForwardRefModel") -> "ForwardRefModel":
    return ForwardRefModel(x=input.x + 1)


class ForwardRefModel(BaseModel):

from fastapi import FastAPI

app = FastAPI()


@app.get("/keyword-weights/", response_model=dict[str, float])
async def read_keyword_weights():