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Python TensorflowGraph.get_feed_dict方法代码示例

本文整理汇总了Python中deepchem.models.tensorflow_models.TensorflowGraph.get_feed_dict方法的典型用法代码示例。如果您正苦于以下问题:Python TensorflowGraph.get_feed_dict方法的具体用法?Python TensorflowGraph.get_feed_dict怎么用?Python TensorflowGraph.get_feed_dict使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在deepchem.models.tensorflow_models.TensorflowGraph的用法示例。


在下文中一共展示了TensorflowGraph.get_feed_dict方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: construct_task_feed_dict

# 需要导入模块: from deepchem.models.tensorflow_models import TensorflowGraph [as 别名]
# 或者: from deepchem.models.tensorflow_models.TensorflowGraph import get_feed_dict [as 别名]
  def construct_task_feed_dict(self,
                               this_task,
                               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
    n_samples = len(X_b)
    for task in range(self.n_tasks):
      if (this_task == task) and y_b is not None:
        #orig_dict["labels_%d" % task] = np.reshape(y_b[:, task], (n_samples, 1))
        orig_dict["labels_%d" % task] = np.reshape(y_b[:, task], (n_samples,))
      else:
        # Dummy placeholders
        #orig_dict["labels_%d" % task] = np.zeros((n_samples, 1))
        orig_dict["labels_%d" % task] = np.zeros((n_samples,))
      if (this_task == task) and w_b is not None:
        #orig_dict["weights_%d" % task] = np.reshape(w_b[:, task], (n_samples, 1))
        orig_dict["weights_%d" % task] = np.reshape(w_b[:, task], (n_samples,))
      else:
        # Dummy placeholders
        #orig_dict["weights_%d" % task] = np.zeros((n_samples, 1)) 
        orig_dict["weights_%d" % task] = np.zeros((n_samples,))
    return TensorflowGraph.get_feed_dict(orig_dict)
开发者ID:joegomes,项目名称:deepchem,代码行数:37,代码来源:progressive_multitask.py

示例2: construct_feed_dict

# 需要导入模块: from deepchem.models.tensorflow_models import TensorflowGraph [as 别名]
# 或者: from deepchem.models.tensorflow_models.TensorflowGraph import get_feed_dict [as 别名]
  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] = to_one_hot(y_b[:, task])
      else:
        # Dummy placeholders
        orig_dict["labels_%d" % task] = np.squeeze(to_one_hot(
            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)
开发者ID:apappu97,项目名称:deepchem,代码行数:29,代码来源:fcnet.py

示例3: construct_feed_dict

# 需要导入模块: from deepchem.models.tensorflow_models import TensorflowGraph [as 别名]
# 或者: from deepchem.models.tensorflow_models.TensorflowGraph import get_feed_dict [as 别名]
  def construct_feed_dict(self, X_b, y_b=None, w_b=None, ids_b=None):

    orig_dict = {}
    orig_dict["mol_features"] = X_b
    for task in range(self.n_tasks):
      if y_b is not None:
        y_2column = to_one_hot(y_b[:, task])
        # fix the size to be [?,1]
        orig_dict["labels_%d" % task] = y_2column[:, 1:2]
      else:
        # Dummy placeholders
        orig_dict["labels_%d" % task] = np.zeros((self.batch_size, 1))
      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)
开发者ID:joegomes,项目名称:deepchem,代码行数:20,代码来源:lr.py


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