tfp optional

# -*- coding: utf-8 -*-

import tensorflow as tf

import tensorflow_probability as tfp

import numpy as np

import collections

from tensorflow.keras import activations, initializers, backend

class WeaveGather(tf.keras.layers.Layer):

  """Implements the weave-gathering section of weave convolutions.

  Implements the gathering layer from the following paper:

  Kearnes, Steven, et al. "Molecular graph convolutions: moving beyond

  fingerprints." Journal of computer-aided molecular design 30.8 (2016): 595-608.

  The weave gathering layer gathers	per-atom features to create a

  molecule-level fingerprint in a weave convolutional network. This layer can

  also perform Gaussian histogram expansion as detailed in the original paper.

  """

  def __init__(self,

               batch_size,

    activation: str, optional

      Activation function applied

    """

    try:

      import tensorflow_probability as tfp

    except ModuleNotFoundError:

      raise ValueError(

          "This class requires tensorflow-probability to be installed.")

    super(WeaveGather, self).__init__(**kwargs)

    self.n_input = n_input

    self.batch_size = batch_size

from deepchem.models.optimizers import Adam

import numpy as np

import tensorflow as tf

import tensorflow_probability as tfp

import collections

import copy

import multiprocessing

class A2CLossContinuous(object):

  """This class computes the loss function for A2C with continuous action spaces."""

  """This class computes the loss function for A2C with continuous action spaces.

  Note

  ----

  This class requires tensorflow-probability to be installed.

  """

  def __init__(self, value_weight, entropy_weight, mean_index, std_index,

               value_index):

    try:

      import tensorflow_probability as tfp

    except ModuleNotFoundError:

      raise ValueError(

          "This class requires tensorflow-probability to be installed.")

    self.value_weight = value_weight

    self.entropy_weight = entropy_weight

    self.mean_index = mean_index