class_docstr: Implements an icml model as configured in a model_config.proto.
class_docstr_tok: ["Implements","an","icml","model","as","configured","in","a","model_config.proto","."]
docstr: Construct a feed dictionary from minibatch data.
  
  TODO(rbharath): ids_b is not used here. Can we remove it?
  
  Args:
    X_b: np.ndarray of shape (batch_size, n_features)
    y_b: np.ndarray of shape (batch_size, n_tasks)
    w_b: np.ndarray of shape (batch_size, n_tasks)
    ids_b: List of length (batch_size) with datapoint identifiers.
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code: def construct_feed_dict(self, X_b, y_b=None, w_b=None, ids_b=None):
      """Construct a feed dictionary from minibatch data.
  
      TODO(rbharath): ids_b is not used here. Can we remove it?
  
      Args:
        X_b: np.ndarray of shape (batch_size, n_features)
        y_b: np.ndarray of shape (batch_size, n_tasks)
        w_b: np.ndarray of shape (batch_size, n_tasks)
        ids_b: List of length (batch_size) with datapoint identifiers.
      """
      orig_dict = {}
      orig_dict["mol_features"] = X_b
      for task in range(self.n_tasks):
          if y_b is not None:
              orig_dict["labels_%d" % task] = y_b[:, task]
          else:
              # Dummy placeholders
              orig_dict["labels_%d" % task] = np.squeeze(
                  np.zeros((self.batch_size,))
              )
          if w_b is not None:
              orig_dict["weights_%d" % task] = w_b[:, task]
          else:
              # Dummy placeholders
              orig_dict["weights_%d" % task] = np.ones(
                  (self.batch_size,)
              )
      return TensorflowGraph.get_feed_dict(orig_dict)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import collections
  import pickle
  import os
  import time
  import warnings
  import numpy
  import pandas
  import tensorflow
  import tempfile
  from deepchem.models import Model
  from deepchem.metrics import from_one_hot
  from deepchem.nn import model_ops
  from deepchem.models.tensorflow_models import utils
  from deepchem.trans import undo_transforms
  from deepchem.utils.save import log
  from deepchem.utils.evaluate import Evaluator
  from deepchem.data import pad_features
  from tensorflow.contrib.layers.python.layers import batch_norm
label_desc: Use image node_id 2 for calling the TensorflowMultiTaskRegressor obj's underlying member method code with example usage: obj.construct_feed_dict(X_b, y_b, w_b, ids_b) and returns: TensorflowGraph