Python tensorflow.python.ops.standard_ops.reduce_mean() Examples

The following are 6 code examples of tensorflow.python.ops.standard_ops.reduce_mean(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.python.ops.standard_ops , or try the search function .
Example #1
Source File: summaries.py    From deep_image_model with Apache License 2.0 6 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(standard_ops.to_float(standard_ops.less(
            op.op.inputs[0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(standard_ops.to_float(standard_ops.greater(
            op.op.inputs[0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)
Example #2
Source File: summaries.py    From tensornets with MIT License 5 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.less(op.op.inputs[
                    0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.greater(op.op.inputs[
                    0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)
Example #3
Source File: summaries.py    From lambda-packs with MIT License 5 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.less(op.op.inputs[
                    0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.greater(op.op.inputs[
                    0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)
Example #4
Source File: summaries.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.less(op.op.inputs[
                    0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.greater(op.op.inputs[
                    0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)
Example #5
Source File: summaries.py    From tf-slim with Apache License 2.0 5 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.less(op.op.inputs[
                    0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.greater(op.op.inputs[
                    0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)
Example #6
Source File: summaries.py    From keras-lambda with MIT License 5 votes vote down vote up 
def summarize_activation(op):
  """Summarize an activation.

  This applies the given activation and adds useful summaries specific to the
  activation.

  Args:
    op: The tensor to summarize (assumed to be a layer activation).
  Returns:
    The summary op created to summarize `op`.
  """
  if op.op.type in ('Relu', 'Softplus', 'Relu6'):
    # Using inputs to avoid floating point equality and/or epsilons.
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.less(op.op.inputs[
                    0], standard_ops.cast(0.0, op.op.inputs[0].dtype)))),
        '%s/zeros' % op.op.name)
  if op.op.type == 'Relu6':
    _add_scalar_summary(
        standard_ops.reduce_mean(
            standard_ops.to_float(
                standard_ops.greater(op.op.inputs[
                    0], standard_ops.cast(6.0, op.op.inputs[0].dtype)))),
        '%s/sixes' % op.op.name)
  return _add_histogram_summary(op, '%s/activation' % op.op.name)