AMPL 1.5.0 release

• Updated AMPL to deepchem 2.7.1 and the related libraries
  -- Python 3.8.x
  -- numpy 1.21.6
  -- rdkit 2022.9.3
  -- rdkit-pypi 2022.3.5

• Changed the environment setup from a mixture of conda and pip packages to pip exclusively
  -- Updated the related document to reflect the change
  -- Removed unused packages from the requirements list

• Feature enhancements/code clean-up
  -- Added ability to highlight substructures and SMARTS pattern matches in molecules rendered with rdkit_easy functions mol_to_svg, mol_to_html, etc.
  -- Updated hyper_perf_plots.py to work with minimal examples
  -- Changed splitting code to allow many-to-one mapping from compound IDs to SMILES strings
  -- Change to support AD index computation for graphconv models using embeddings as features
  -- Added max_dataset_rows parameter to limit number of training set records used for AD index computation, so that AD computation is feasible for models trained on large datasets.
  -- Replaced all uses of deepchem.data.DiskDataset with NumpyDataset to boost performance and reduce creation of temporary files
  -- Added workaround for DeepChem issue #1821, which was causing predictions to fail on single-compound batches.
  -- Implemented tar archive safe extract to fix vulnerability CVE-2007-4559
  -- Turned off uncertainty for multi_class_config_delaney_fit_NN_graphconv.json
  -- Refined AMPL version/model version compatibility checking to define groups of compatible versions according to whether the associated DeepChem versions have the same format of model checkpoint files. The current compatibility groups are:
  -- Group1: '1.2', '1.3'
  -- Group2: '1.4'
  -- Group3: '1.5'

• Bug fixes