<jupyter_start><jupyter_text>Find the number of GPU devises availableNote that this does not recognize AMD GPU on iMac and macbooks<jupyter_code>from catboost.utils import get_gpu_device_count
print('I see %i GPU devices' % get_gpu_device_count())
import tensorflow as tf
print("GPU Available :",tf.test.is_gpu_available())
print("GPU devise name :",tf.test.gpu_device_name())
print("Built with CUDA :", tf.test.is_built_with_cuda())
print("Built with GPU Support :",tf.test.is_built_with_gpu_support())<jupyter_output>GPU Available : False
GPU devise name : 
Built with CUDA : False
Built with GPU Support : False<jupyter_text>Check if OpenBLAS or MKL is included in the numpy install<jupyter_code>import numpy as np
print(np.__version__)
np.show_config()<jupyter_output>1.17.4
blas_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/anaconda3/envs/regular/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/anaconda3/envs/regular/include']
blas_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/anaconda3/envs/regular/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/anaconda3/envs/regular/include']
lapack_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/anaconda3/envs/regular/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/anaconda3/envs/regular/include']
lapack_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/opt/anaconda3/envs/regular/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/opt/anaconda3/envs/regular/include']<jupyter_text>Check the system path<jupyter_code>import sys
sys.path<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.141280353200883, 'fraction_numerical': 0.006622516556291391, 'mean_word_length': 5.616788321167883, 'pattern_counts': {'":': 0, '<': 11, '<?xml version=': 0, '>': 11, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '643742', 'license': 'MIT', 'n_tokens_mistral': 699, 'n_tokens_neox': 688, 'n_words': 133, 'path': 'utility_checks.ipynb', 'repo_name': 'radhavrmk/myutil', 'size': '1812'}