Copy the generate_combinations_with_testcase_name to keras testing_utils

PiperOrigin-RevId: 331229096 Change-Id: Ie4a0bc8eacea7e7d04dee669de18b17ab1b0ecc1
2020-09-11 14:57:55 -07:00 · 2020-09-11 14:57:55 -07:00 · be60cfe80f
commit be60cfe80f
parent e92d25ebd0
7 changed files with 57 additions and 18 deletions
--- a/tensorflow/python/keras/layers/convolutional_recurrent_test.py
+++ b/tensorflow/python/keras/layers/convolutional_recurrent_test.py
@ -22,7 +22,6 @@ from absl.testing import parameterized
 import numpy as np

 from tensorflow.python import keras
-from tensorflow.python.framework import test_util
 from tensorflow.python.keras import keras_parameterized
 from tensorflow.python.keras import testing_utils
 from tensorflow.python.platform import test
@ -32,7 +31,7 @@ from tensorflow.python.platform import test
 class ConvLSTMTest(keras_parameterized.TestCase):

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          data_format=['channels_first', 'channels_last'],
          return_sequences=[True, False]))
  def test_conv_lstm(self, data_format, return_sequences):
--- a/tensorflow/python/keras/layers/cudnn_recurrent_test.py
+++ b/tensorflow/python/keras/layers/cudnn_recurrent_test.py
@ -40,7 +40,7 @@ from tensorflow.python.training import gradient_descent
 class CuDNNTest(keras_parameterized.TestCase):

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer_class=[keras.layers.CuDNNGRU, keras.layers.CuDNNLSTM],
          return_sequences=[True, False]))
  @test_util.run_gpu_only
@ -56,7 +56,7 @@ class CuDNNTest(keras_parameterized.TestCase):
        input_shape=(num_samples, timesteps, input_size))

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer_class=[keras.layers.CuDNNGRU, keras.layers.CuDNNLSTM],
          go_backwards=[True, False]))
  @test_util.run_gpu_only
@ -269,7 +269,7 @@ class CuDNNV1OnlyTest(keras_parameterized.TestCase):

  # TODO(b/156439419): Reenable after the bug is fixed.
  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          rnn_type=['LSTM', 'GRU'], to_cudnn=[True, False],
          bidirectional=[True, False], implementation=[1, 2],
          model_nest_level=[1, 2], model_type=['seq', 'func']))
@ -352,7 +352,7 @@ class CuDNNV1OnlyTest(keras_parameterized.TestCase):
    os.remove(fname)

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          rnn_type=['LSTM', 'GRU'], to_cudnn=[True, False]))
  @test_util.run_v1_only('b/120911602')
  @test_util.run_gpu_only
--- a/tensorflow/python/keras/layers/merge_test.py
+++ b/tensorflow/python/keras/layers/merge_test.py
@ -22,7 +22,6 @@ from absl.testing import parameterized
 import numpy as np

 from tensorflow.python import keras
-from tensorflow.python.framework import test_util as tf_test_util
 from tensorflow.python.keras import backend as K
 from tensorflow.python.keras import combinations
 from tensorflow.python.keras import keras_parameterized
@ -225,7 +224,7 @@ class MergeLayersTest(keras_parameterized.TestCase):
    self.assertEqual(layer.compute_output_shape([(4, 5), (4, 5)]), (4, 1))

  @parameterized.named_parameters(
-      *tf_test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer=[keras.layers.Add, keras.layers.Subtract,
                 keras.layers.Multiply, keras.layers.Minimum,
                 keras.layers.Maximum, keras.layers.Average,
@ -251,7 +250,7 @@ class MergeLayersTest(keras_parameterized.TestCase):
    self.assertAllEqual(out_dense, out_ragged)

  @parameterized.named_parameters(
-      *tf_test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer=[keras.layers.Add, keras.layers.Subtract,
                 keras.layers.Multiply, keras.layers.Minimum,
                 keras.layers.Maximum, keras.layers.Average]))
--- a/tensorflow/python/keras/layers/recurrent_test.py
+++ b/tensorflow/python/keras/layers/recurrent_test.py
@ -33,7 +33,6 @@ from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import random_seed
 from tensorflow.python.framework import tensor_shape
-from tensorflow.python.framework import test_util
 from tensorflow.python.keras import keras_parameterized
 from tensorflow.python.keras import testing_utils
 from tensorflow.python.keras.engine import base_layer_utils
@ -722,7 +721,7 @@ class RNNTest(keras_parameterized.TestCase):
      self.assertAllClose(y_np, y_np_2, atol=1e-4)

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer=[rnn_v1.SimpleRNN, rnn_v1.GRU, rnn_v1.LSTM,
                 rnn_v2.GRU, rnn_v2.LSTM],
          unroll=[True, False]))
@ -743,7 +742,7 @@ class RNNTest(keras_parameterized.TestCase):
    model.train_on_batch(x_np, y_np)

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          cell=[keras.layers.SimpleRNNCell, keras.layers.GRUCell,
                keras.layers.LSTMCell],
          unroll=[True, False]))
@ -1551,7 +1550,7 @@ class RNNTest(keras_parameterized.TestCase):
    model.predict(np.ones((batch, timesteps, input_dim)))

  @parameterized.named_parameters(
-      *test_util.generate_combinations_with_testcase_name(layer=[
+      *testing_utils.generate_combinations_with_testcase_name(layer=[
          rnn_v1.SimpleRNN, rnn_v1.GRU, rnn_v1.LSTM, rnn_v2.GRU, rnn_v2.LSTM
      ]))
  def test_rnn_with_ragged_input(self, layer):
--- a/tensorflow/python/keras/layers/wrappers_test.py
+++ b/tensorflow/python/keras/layers/wrappers_test.py
@ -28,7 +28,6 @@ from tensorflow.python.eager import context
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import tensor_shape
-from tensorflow.python.framework import test_util as tf_test_util
 from tensorflow.python.keras import combinations
 from tensorflow.python.keras import keras_parameterized
 from tensorflow.python.keras import testing_utils
@ -405,7 +404,7 @@ class TimeDistributedTest(keras_parameterized.TestCase):

  @keras_parameterized.run_all_keras_modes
  @parameterized.named_parameters(
-      *tf_test_util.generate_combinations_with_testcase_name(
+      *testing_utils.generate_combinations_with_testcase_name(
          layer=[keras.layers.LSTM,
                 keras.layers.Dense]))
  def test_TimeDistributed_with_ragged_input(self, layer):
--- a/tensorflow/python/keras/testing_utils.py
+++ b/tensorflow/python/keras/testing_utils.py
@ -18,8 +18,10 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function

+import collections
 import contextlib
 import functools
+import itertools
 import threading

 import numpy as np
@ -1040,3 +1042,44 @@ def run_v2_only(func=None):
    return decorator(func)

  return decorator
+
+
+def generate_combinations_with_testcase_name(**kwargs):
+  """Generate combinations based on its keyword arguments using combine().
+
+  This function calls combine() and appends a testcase name to the list of
+  dictionaries returned. The 'testcase_name' key is a required for named
+  parameterized tests.
+
+  Args:
+    **kwargs: keyword arguments of form `option=[possibilities, ...]` or
+      `option=the_only_possibility`.
+
+  Returns:
+    a list of dictionaries for each combination. Keys in the dictionaries are
+    the keyword argument names.  Each key has one value - one of the
+    corresponding keyword argument values.
+  """
+  sort_by_key = lambda k: k[0]
+  combinations = []
+  for key, values in sorted(kwargs.items(), key=sort_by_key):
+    if not isinstance(values, list):
+      values = [values]
+    combinations.append([(key, value) for value in values])
+
+  combinations = [collections.OrderedDict(result)
+                  for result in itertools.product(*combinations)]
+  named_combinations = []
+  for combination in combinations:
+    assert isinstance(combination, collections.OrderedDict)
+    name = ''.join([
+        '_{}_{}'.format(''.join(filter(str.isalnum, key)),
+                        ''.join(filter(str.isalnum, str(value))))
+        for key, value in combination.items()
+    ])
+    named_combinations.append(
+        collections.OrderedDict(
+            list(combination.items()) +
+            [('testcase_name', '_test{}'.format(name))]))
+
+  return named_combinations
--- a/tensorflow/python/keras/utils/composite_tensor_support_test.py
+++ b/tensorflow/python/keras/utils/composite_tensor_support_test.py
@ -325,7 +325,7 @@ def prepare_inputs(data, use_dict, use_dataset, action, input_name):
@keras_parameterized.run_with_all_model_types
@keras_parameterized.run_all_keras_modes
@parameterized.named_parameters(
-    *test_util.generate_combinations_with_testcase_name(
+    *testing_utils.generate_combinations_with_testcase_name(
        use_dict=[True, False],
        use_dataset=[True, False],
        action=["predict", "evaluate", "fit"]))
@ -490,7 +490,7 @@ class ScipySparseTensorInputTest(keras_parameterized.TestCase,
@keras_parameterized.run_with_all_model_types
@keras_parameterized.run_all_keras_modes
@parameterized.named_parameters(
-    *test_util.generate_combinations_with_testcase_name(
+    *testing_utils.generate_combinations_with_testcase_name(
        use_dict=[True, False],
        use_dataset=[True, False],
        action=["predict", "evaluate", "fit"]))
@ -537,7 +537,7 @@ class RaggedTensorInputTest(keras_parameterized.TestCase,
@keras_parameterized.run_with_all_model_types
@keras_parameterized.run_all_keras_modes
@parameterized.named_parameters(
-    *test_util.generate_combinations_with_testcase_name(
+    *testing_utils.generate_combinations_with_testcase_name(
        use_dict=[True, False], use_dataset=[True, False]))
 class RaggedTensorInputValidationTest(keras_parameterized.TestCase,
                                      test_util.TensorFlowTestCase):