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Python dragnn_ops.get_component_trace方法代码示例

本文整理汇总了Python中dragnn.python.dragnn_ops.get_component_trace方法的典型用法代码示例。如果您正苦于以下问题:Python dragnn_ops.get_component_trace方法的具体用法?Python dragnn_ops.get_component_trace怎么用?Python dragnn_ops.get_component_trace使用的例子?那么恭喜您, 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dragnn.python.dragnn_ops的用法示例。


在下文中一共展示了dragnn_ops.get_component_trace方法的2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: add_annotation

# 需要导入模块: from dragnn.python import dragnn_ops [as 别名]
# 或者: from dragnn.python.dragnn_ops import get_component_trace [as 别名]
def add_annotation(self, name_scope='annotation', enable_tracing=False):
    """Adds an annotation pipeline to the graph.

    This will create the following additional named targets by default, for use
    in C++ annotation code (as well as regular ComputeSession targets):
      annotation/ComputeSession/session_id (placeholder for giving unique id)
      annotation/EmitAnnotations (get annotated data)
      annotation/GetComponentTrace (get trace data)
      annotation/SetTracing (sets tracing based on annotation/tracing_on)

    Args:
      name_scope: Scope for the annotation pipeline.
      enable_tracing: Enabling this will result in two things:
          1. Tracing will be enabled during inference.
          2. A 'traces' node will be added to the outputs.

    Returns:
      A dictionary of input and output nodes.
    """
    with tf.name_scope(name_scope):
      handle, input_batch = self._get_session_with_reader(enable_tracing)
      handle = self.build_inference(handle, use_moving_average=True)

      annotations = dragnn_ops.emit_annotations(
          handle, component=self.spec.component[-1].name)
      outputs = {'annotations': annotations}

      if enable_tracing:
        outputs['traces'] = dragnn_ops.get_component_trace(
            handle, component=self.spec.component[-1].name)

      return self._outputs_with_release(handle, {'input_batch': input_batch},
                                        outputs) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:35,代码来源:graph_builder.py

示例2: add_annotation

# 需要导入模块: from dragnn.python import dragnn_ops [as 别名]
# 或者: from dragnn.python.dragnn_ops import get_component_trace [as 别名]
def add_annotation(self,
                     name_scope='annotation',
                     enable_tracing=False,
                     build_runtime_graph=False):
    """Adds an annotation pipeline to the graph.

    This will create the following additional named targets by default, for use
    in C++ annotation code (as well as regular ComputeSession targets):
      annotation/ComputeSession/session_id (placeholder for giving unique id)
      annotation/EmitAnnotations (get annotated data)
      annotation/GetComponentTrace (get trace data)
      annotation/SetTracing (sets tracing based on annotation/tracing_on)

    Args:
      name_scope: Scope for the annotation pipeline.
      enable_tracing: Enabling this will result in two things:
          1. Tracing will be enabled during inference.
          2. A 'traces' node will be added to the outputs.
      build_runtime_graph: Whether to build a graph for use by the runtime.

    Returns:
      A dictionary of input and output nodes.
    """
    with tf.name_scope(name_scope):
      handle, input_batch = self._get_session_with_reader(enable_tracing)
      handle = self.build_inference(
          handle,
          use_moving_average=True,
          build_runtime_graph=build_runtime_graph)

      annotations = dragnn_ops.emit_annotations(
          handle, component=self.spec.component[-1].name)
      outputs = {'annotations': annotations}

      if enable_tracing:
        outputs['traces'] = dragnn_ops.get_component_trace(
            handle, component=self.spec.component[-1].name)

      return self._outputs_with_release(handle, {'input_batch': input_batch},
                                        outputs) 
开发者ID:generalized-iou,项目名称:g-tensorflow-models,代码行数:42,代码来源:graph_builder.py


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