Python LayerNetworkDescription.num_inputs_outputs_from_config Exemples

Exemple #1

Fichier : Network.py Projet : atuxhe/returnn

 def init_args_from_config(cls, config):
   """
   :rtype: dict[str]
   :returns the kwarg for cls.from_json()
   """
   num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
   return {
     "n_in": num_inputs, "n_out": num_outputs,
     "sparse_input": config.bool("sparse_input", False),
     "target": config.value('target', 'classes')
   }

Exemple #2

Fichier : test_NetworkDescription.py Projet : atuxhe/returnn

def test_num_inputs_outputs_special_dataset():
  config = Config()
  config.update({
    "train": {"class": "CopyTaskDataset", "num_seqs": 1000, "nsymbols": 80, "minlen": 100, "maxlen": 100},
    "num_outputs": {"data": [80, 1], "classes": [80, 1]}})
  num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
  assert_equal(num_inputs, 80)
  assert_in("data", num_outputs)
  assert_in("classes", num_outputs)
  assert_equal(num_outputs["classes"], [80, 1])
  assert_equal(num_outputs["data"], [80, 1])

Exemple #3

Fichier : test_NetworkDescription.py Projet : atuxhe/returnn

def test_num_inputs_outputs_old():
  n_in = 5
  n_out = 10
  config = Config()
  config.update({"num_inputs": n_in, "num_outputs": n_out})
  num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
  assert_equal(num_inputs, n_in)
  assert_is_instance(num_outputs, dict)
  assert_equal(len(num_outputs), 1)
  assert_in("classes", num_outputs)
  assert_equal(num_outputs["classes"], [n_out, 1])

Exemple #4

def test_num_inputs_outputs_special_dataset():
  config = Config()
  config.update({
    "train": {"class": "CopyTaskDataset", "num_seqs": 1000, "nsymbols": 80, "minlen": 100, "maxlen": 100},
    "num_outputs": {"data": [80, 1], "classes": [80, 1]}})
  num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
  assert_equal(num_inputs, 80)
  assert_in("data", num_outputs)
  assert_in("classes", num_outputs)
  assert_equal(num_outputs["classes"], [80, 1])
  assert_equal(num_outputs["data"], [80, 1])

Exemple #5

def test_num_inputs_outputs_old():
  n_in = 5
  n_out = 10
  config = Config()
  config.update({"num_inputs": n_in, "num_outputs": n_out})
  num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
  assert_equal(num_inputs, n_in)
  assert_is_instance(num_outputs, dict)
  assert_equal(len(num_outputs), 1)
  assert_in("classes", num_outputs)
  assert_equal(num_outputs["classes"], [n_out, 1])

Exemple #6

Fichier : Network.py Projet : wj199031738/returnn

 def init_args_from_config(cls, config):
   """
   :rtype: dict[str]
   :returns the kwarg for cls.from_json()
   """
   num_inputs, num_outputs = LayerNetworkDescription.num_inputs_outputs_from_config(config)
   return {
     "n_in": num_inputs, "n_out": num_outputs,
     "sparse_input": config.bool("sparse_input", False),
     "target": config.value('target', 'classes')
   }