Merge pull request #2466 from PascalIversen/master

import numpy as np

import tensorflow as tf

import os

import sys

import logging

from typing import Dict

from deepchem.data.datasets import pad_batch

from deepchem.models import KerasModel, layers

from deepchem.models import KerasModel

from deepchem.models.losses import L2Loss, SoftmaxCrossEntropy, SigmoidCrossEntropy

from deepchem.metrics import to_one_hot

from deepchem.models import chemnet_layers

from tensorflow.keras.layers import Input, Dense, Reshape, Softmax, Activation

from tensorflow.keras.layers import Dropout, Conv1D, Concatenate, Lambda, GRU, LSTM, Bidirectional

from tensorflow.keras.layers import Conv2D, ReLU, Add, GlobalAveragePooling2D

from tensorflow.keras.layers import Conv1D, GRU, LSTM, Bidirectional

from tensorflow.keras.layers import GlobalAveragePooling2D

DEFAULT_INCEPTION_BLOCKS = {"A": 3, "B": 3, "C": 3}

  """

  def __init__(self,

               img_spec="std",

               base_filters=16,

               inception_blocks=DEFAULT_INCEPTION_BLOCKS,

               n_tasks=10,

               n_classes=2,

               augment=False,

               mode="regression",

               img_spec: str = "std",

               img_size: int = 80,

               base_filters: int = 16,

               inception_blocks: Dict = DEFAULT_INCEPTION_BLOCKS,

               n_tasks: int = 10,

               n_classes: int = 2,

               augment: bool = False,

               mode: str = "regression",

               **kwargs):

    """

    Parameters

    ----------

    img_spec: str, default std

        Image specification used

    img_size: int, default 80

        Image size used

    base_filters: int, default 16

        Base filters used for the different inception and reduction layers

    inception_blocks: dict,

        Whether the model is used for regression or classification

    """

    if img_spec == "engd":

      self.input_shape = (80, 80, 4)

      self.input_shape = (img_size, img_size, 4)

    elif img_spec == "std":

      self.input_shape = (80, 80, 1)

      self.input_shape = (img_size, img_size, 1)

    self.base_filters = base_filters

    self.inception_blocks = inception_blocks

    self.n_tasks = n_tasks