Python tensorflow.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS Examples

The following are 12 code examples of tensorflow.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS(). 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.contrib.tfprof.model_analyzer , or try the search function .
Example #1
Source File: model_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def test_model_size_less_then1_gb(self):
    # NOTE: Actual amount of memory occupied my TF during training will be at
    # least 4X times bigger because of space need to store original weights,
    # updates, gradients and variances. It also depends on the type of used
    # optimizer.
    ocr_model = self.create_model()
    ocr_model.create_base(images=self.fake_images, labels_one_hot=None)
    with self.test_session() as sess:
      tfprof_root = model_analyzer.print_model_analysis(
          sess.graph,
          tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)

      model_size_bytes = 4 * tfprof_root.total_parameters
      self.assertLess(model_size_bytes, 1 * 2**30)
Example #2
Source File: train.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #3
Source File: train.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #4
Source File: train.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #5
Source File: model_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def test_model_size_less_then1_gb(self):
    # NOTE: Actual amount of memory occupied my TF during training will be at
    # least 4X times bigger because of space need to store original weights,
    # updates, gradients and variances. It also depends on the type of used
    # optimizer.
    ocr_model = self.create_model()
    ocr_model.create_base(images=self.fake_images, labels_one_hot=None)
    with self.test_session() as sess:
      tfprof_root = model_analyzer.print_model_analysis(
          sess.graph,
          tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)

      model_size_bytes = 4 * tfprof_root.total_parameters
      self.assertLess(model_size_bytes, 1 * 2**30)
Example #6
Source File: train.py    From hands-detection with MIT License 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #7
Source File: model_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def test_model_size_less_then1_gb(self):
    # NOTE: Actual amount of memory occupied my TF during training will be at
    # least 4X times bigger because of space need to store original weights,
    # updates, gradients and variances. It also depends on the type of used
    # optimizer.
    ocr_model = self.create_model()
    ocr_model.create_base(images=self.fake_images, labels_one_hot=None)
    with self.test_session() as sess:
      tfprof_root = model_analyzer.print_model_analysis(
          sess.graph,
          tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)

      model_size_bytes = 4 * tfprof_root.total_parameters
      self.assertLess(model_size_bytes, 1 * 2**30)
Example #8
Source File: train.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #9
Source File: train.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #10
Source File: train.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #11
Source File: train.py    From models with Apache License 2.0 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters
Example #12
Source File: train.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
def calculate_graph_metrics():
  param_stats = model_analyzer.print_model_analysis(
      tf.get_default_graph(),
      tfprof_options=model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
  return param_stats.total_parameters