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Python training_ops.sparse_apply_ftrl方法代码示例

本文整理汇总了Python中tensorflow.python.training.training_ops.sparse_apply_ftrl方法的典型用法代码示例。如果您正苦于以下问题:Python training_ops.sparse_apply_ftrl方法的具体用法?Python training_ops.sparse_apply_ftrl怎么用?Python training_ops.sparse_apply_ftrl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tensorflow.python.training.training_ops的用法示例。


在下文中一共展示了training_ops.sparse_apply_ftrl方法的4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: _apply_sparse

# 需要导入模块: from tensorflow.python.training import training_ops [as 别名]
# 或者: from tensorflow.python.training.training_ops import sparse_apply_ftrl [as 别名]
def _apply_sparse(self, grad, var):
    accum = self.get_slot(var, "accum")
    linear = self.get_slot(var, "linear")
    return training_ops.sparse_apply_ftrl(
        var,
        accum,
        linear,
        grad.values,
        grad.indices,
        math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
        math_ops.cast(self._l1_regularization_strength_tensor,
                      var.dtype.base_dtype),
        math_ops.cast(self._l2_regularization_strength_tensor,
                      var.dtype.base_dtype),
        math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
        use_locking=self._use_locking) 
开发者ID:ryfeus,项目名称:lambda-packs,代码行数:18,代码来源:ftrl.py

示例2: _testTypesForSparseFtrl

# 需要导入模块: from tensorflow.python.training import training_ops [as 别名]
# 或者: from tensorflow.python.training.training_ops import sparse_apply_ftrl [as 别名]
def _testTypesForSparseFtrl(self, x, y, z, lr, grad, indices, l1=0.0, l2=0.0,
                              lr_power=-0.5):
    self.setUp()
    with self.test_session(use_gpu=False):
      var = variables.Variable(x)
      accum = variables.Variable(y)
      linear = variables.Variable(z)
      variables.global_variables_initializer().run()

      self.assertAllCloseAccordingToType(x, var.eval())
      sparse_apply_ftrl = training_ops.sparse_apply_ftrl(
          var, accum, linear, grad,
          constant_op.constant(indices, self._toType(indices.dtype)),
          lr, l1, l2, lr_power=lr_power)
      out = sparse_apply_ftrl.eval()
      self.assertShapeEqual(out, sparse_apply_ftrl)

      for (i, index) in enumerate(indices):
        self.assertAllCloseAccordingToType(
            x[index] - lr * grad[i] * (y[index] + grad[i] * grad[i]) ** (
                lr_power),
            var.eval()[index])
        self.assertAllCloseAccordingToType(y[index] + grad[i] * grad[i],
                                           accum.eval()[index]) 
开发者ID:tobegit3hub,项目名称:deep_image_model,代码行数:26,代码来源:training_ops_test.py

示例3: _apply_sparse

# 需要导入模块: from tensorflow.python.training import training_ops [as 别名]
# 或者: from tensorflow.python.training.training_ops import sparse_apply_ftrl [as 别名]
def _apply_sparse(self, grad, var):
    accum = self.get_slot(var, "accum")
    linear = self.get_slot(var, "linear")
    return training_ops.sparse_apply_ftrl(
        var, accum, linear, grad.values, grad.indices,
        math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
        math_ops.cast(self._l1_regularization_strength_tensor,
                      var.dtype.base_dtype),
        math_ops.cast(self._l2_regularization_strength_tensor,
                      var.dtype.base_dtype),
        math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
        use_locking=self._use_locking) 
开发者ID:abhisuri97,项目名称:auto-alt-text-lambda-api,代码行数:14,代码来源:ftrl.py

示例4: _apply_sparse

# 需要导入模块: from tensorflow.python.training import training_ops [as 别名]
# 或者: from tensorflow.python.training.training_ops import sparse_apply_ftrl [as 别名]
def _apply_sparse(self, grad, var):
    accum = self.get_slot(var, "accum")
    linear = self.get_slot(var, "linear")
    if self._l2_shrinkage_regularization_strength <= 0.0:
      return training_ops.sparse_apply_ftrl(
          var,
          accum,
          linear,
          grad.values,
          grad.indices,
          math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
          math_ops.cast(self._l1_regularization_strength_tensor,
                        var.dtype.base_dtype),
          math_ops.cast(self._l2_regularization_strength_tensor,
                        var.dtype.base_dtype),
          math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
          use_locking=self._use_locking)
    else:
      return training_ops.sparse_apply_ftrl_v2(
          var,
          accum,
          linear,
          grad.values,
          grad.indices,
          math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
          math_ops.cast(self._l1_regularization_strength_tensor,
                        var.dtype.base_dtype),
          math_ops.cast(self._l2_regularization_strength_tensor,
                        var.dtype.base_dtype),
          math_ops.cast(self._l2_shrinkage_regularization_strength_tensor,
                        grad.dtype.base_dtype),
          math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
          use_locking=self._use_locking) 
开发者ID:PacktPublishing,项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda,代码行数:35,代码来源:ftrl.py


注:本文中的tensorflow.python.training.training_ops.sparse_apply_ftrl方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。