text: Title: BUG: to_numpy() ignores dtype argument for datetime64 column
  Body: ### Modin version checks
  
  - [X] I have checked that this issue has not already been reported.
  
  - [X] I have confirmed this bug exists on the latest released version of Modin.
  
  - [ ] I have confirmed this bug exists on the main branch of Modin. (In order to do this you can follow [this guide](https://modin.readthedocs.io/en/stable/getting_started/installation.html#installing-from-the-github-master-branch).)
  
  
  ### Reproducible Example
  
  ```python
  import modin.pandas as pd
  import pandas
  import numpy as np
  
  s = pd.Series(np.datetime64(3, 's'))
  print(s.to_numpy(dtype='int64').dtype)
  
  sp = pandas.Series(np.datetime64(3, 's'))
  print(sp.to_numpy(dtype='int64').dtype)
  ```
  
  
  ### Issue Description
  
  modin result is a datetime64[ns] array, while pandas result is an int64 array.
  
  ### Expected Behavior
  
  Should match dtype in `dtype` argument, as pandas does.
  
  ### Error Logs
  
  N/A
  
  ### Installed Versions
  
  <details>
  
  UserWarning: Setuptools is replacing distutils.
  
  INSTALLED VERSIONS
  ------------------
  commit              : e12b21703494dcbb8f7aa951b40ebe1d033307ba
  python              : 3.9.18.final.0
  python-bits         : 64
  OS                  : Darwin
  OS-release          : 23.0.0
  Version             : Darwin Kernel Version 23.0.0: Fri Sep 15 14:43:05 PDT 2023; root:xnu-10002.1.13~1/RELEASE_ARM64_T6020
  machine             : arm64
  processor           : arm
  byteorder           : little
  LC_ALL              : None
  LANG                : en_US.UTF-8
  LOCALE              : en_US.UTF-8
  
  Modin dependencies
  ------------------
  modin               : 0.25.0
  ray                 : 2.8.0
  dask                : None
  distributed         : None
  hdk                 : None
  
  pandas dependencies
  -------------------
  pandas              : 2.1.2
  numpy               : 1.26.1
  pytz                : 2023.3.post1
  dateutil            : 2.8.2
  setuptools          : 68.0.0
  pip                 : 23.3
  Cython              : None
  pytest              : None
  hypothesis          : None
  sphinx              : None
  blosc               : None
  feather             : None
  xlsxwriter          : None
  lxml.etree          : None
  html5lib            : None
  pymysql             : None
  psycopg2            : None
  jinja2              : None
  IPython             : 8.17.2
  pandas_datareader   : None
  bs4                 : None
  bottleneck          : None
  dataframe-api-compat: None
  fastparquet         : None
  fsspec              : 2023.10.0
  gcsfs               : None
  matplotlib          : 3.8.1
  numba               : None
  numexpr             : None
  odfpy               : None
  openpyxl            : None
  pandas_gbq          : None
  pyarrow             : 14.0.1
  pyreadstat          : None
  pyxlsb              : None
  s3fs                : None
  scipy               : None
  sqlalchemy          : None
  tables              : None
  tabulate            : None
  xarray              : None
  xlrd                : None
  zstandard           : None
  tzdata              : 2023.3
  qtpy                : None
  pyqt5               : None
  
  </details>
  