from fastapi import FastAPI
from pydantic import BaseModel


class DataInput(BaseModel):
    description: str
    data: bytes

    model_config = {"val_json_bytes": "base64"}


class DataOutput(BaseModel):
    description: str
    data: bytes

    model_config = {"ser_json_bytes": "base64"}


class DataInputOutput(BaseModel):
    description: str
    data: bytes

    model_config = {

  }

  public void testReadFully() throws IOException {
    DataInput in = new LittleEndianDataInputStream(new ByteArrayInputStream(data));
    byte[] b = new byte[data.length];
    in.readFully(b);
    assertEquals(Bytes.asList(data), Bytes.asList(b));
  }

  public void testReadUnsignedByte_eof() throws IOException {
    DataInput in = new LittleEndianDataInputStream(new ByteArrayInputStream(new byte[0]));

import static java.nio.charset.StandardCharsets.ISO_8859_1;

import com.google.common.primitives.Bytes;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.DataInput;
import java.io.DataInputStream;
import java.io.IOException;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Test class for {@link LittleEndianDataOutputStream}.
 *

import static java.nio.charset.StandardCharsets.ISO_8859_1;

import com.google.common.primitives.Bytes;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.DataInput;
import java.io.DataInputStream;
import java.io.IOException;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Test class for {@link LittleEndianDataOutputStream}.
 *

import com.google.common.math.IntMath;
import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.DataInput;
import java.io.DataInputStream;
import java.io.DataOutput;
import java.io.DataOutputStream;
import java.io.EOFException;
import java.io.FilterInputStream;
import java.io.IOException;
import java.io.InputStream;

`tf.split(value, num_or_size_splits, axis)`. * `tf.sparse_split` now takes
arguments in reversed order and with different keywords. In particular we now
match NumPy order as `tf.sparse_split(sp_input, num_split, axis)`. NOTE: we have
temporarily made `tf.sparse_split` require keyword arguments. * `tf.concat` now
takes arguments in reversed order and with different keywords. In particular we