Python tensorflow.compat.v1.disable_eager_execution() Examples

def test_parse_events_files(self):
    tb_summary_dir = self.create_tempdir()
    tf.disable_eager_execution()  # Needed in pytest.
    summary_writer = tf.summary.FileWriter(tb_summary_dir.full_path)
    tags = [
        "eval/foo_task/accuracy",
        "eval/foo_task/accuracy",
        "loss",
    ]
    values = [1., 2., 3.]
    steps = [20, 30, 40]
    for tag, value, step in zip(tags, values, steps):
      summary = tf.Summary()
      summary.value.add(tag=tag, simple_value=value)
      summary_writer.add_summary(summary, step)
    summary_writer.flush()
    events = eval_utils.parse_events_files(tb_summary_dir.full_path)
    self.assertDictEqual(
        events,
        {
            "eval/foo_task/accuracy": [(20, 1.), (30, 2.)],
            "loss": [(40, 3.)],
        },
    ) 

def parse(self, onnx_file, output_nodes=None, model_name=None):
    tf.disable_eager_execution()
    if model_name:
      graph_name = model_name
    else:
      graph_name, _ = os.path.splitext(
        os.path.basename(onnx_file)
      )
    tf.reset_default_graph()
    model = onnx.load(onnx_file)
    onnx_graph = model.graph
    ugraph = uTensorGraph(
      name=graph_name,
      output_nodes=[],
      lib_name='onnx',
      ops_info={},
    )
    self._build_graph(onnx_graph, ugraph)
    ugraph = Legalizer.legalize(ugraph)
    tf.reset_default_graph()
    return ugraph 

def setUpModule():
  tf.disable_eager_execution() 

def test_forward_atan2():
    """test operator tan """
    tf.disable_eager_execution()
    np_data_1 = np.random.uniform(1, 100, size=(2, 3, 5)).astype(np.float32)
    np_data_2 = np.random.uniform(1, 100, size=(2, 3, 5)).astype(np.float32)
    tf.reset_default_graph()
    in_data_1 = tf.placeholder(tf.float32, (2, 3, 5), name="in_data_1")
    in_data_2 = tf.placeholder(tf.float32, (2, 3, 5), name="in_data_2")
    tf.atan2(in_data_1, in_data_2, name="atan2")
    compare_tf_with_tvm([np_data_1, np_data_2], ['in_data_1:0', 'in_data_2:0'], 'atan2:0') 

def testPCgradNetworkTPU(self):
    tf.reset_default_graph()
    tf.disable_eager_execution()
    learning_rate = lambda: 0.001
    def pcgrad_computation():
      x = tf.constant(1., shape=[64, 472, 472, 3])
      layers = [
          tf.keras.layers.Conv2D(filters=64, kernel_size=3),
          tf.keras.layers.Conv2D(filters=32, kernel_size=3, strides=(2, 2)),
          tf.keras.layers.Conv2D(filters=32, kernel_size=3, strides=(2, 2)),
          tf.keras.layers.Conv2D(filters=32, kernel_size=3, strides=(2, 2)),
          tf.keras.layers.Conv2D(filters=32, kernel_size=3, strides=(2, 2)),
      ]
      y = x
      for layer in layers:
        y = layer(y)
      n_tasks = 10
      task_loss_0 = tf.reduce_sum(y)
      task_losses = [task_loss_0 * (1. + (n / 10.)) for n in range(n_tasks)]

      pcgrad_opt = pcgrad.PCGrad(
          tf.train.GradientDescentOptimizer(learning_rate))
      pcgrad_grads_and_vars = pcgrad_opt.compute_gradients(
          task_losses, var_list=tf.trainable_variables())
      return pcgrad_opt.apply_gradients(pcgrad_grads_and_vars)

    tpu_computation = tf.compat.v1.tpu.batch_parallel(pcgrad_computation,
                                                      num_shards=2)
    self.evaluate(tf.compat.v1.tpu.initialize_system())
    self.evaluate(tf.compat.v1.global_variables_initializer())
    self.evaluate(tpu_computation)
    self.evaluate(tf.compat.v1.tpu.shutdown_system()) 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution() 

def setUpModule():
  tf.disable_eager_execution()