Enable parallel execution of TensorFlow Layer 2 python tests

.github/workflows/job_python_unit_tests.yml

@@ -280,7 +280,7 @@ jobs:
         run: |
           # requires 'unit_tests' from 'mo'
           export PYTHONPATH=${INSTALL_TEST_DIR}/mo
-          python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/ -m precommit_tf_fe --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_fe.xml
+          python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/tensorflow2_keras_tests/ -n logical -m precommit_tf_fe --junitxml=${INSTALL_TEST_DIR}/TEST-tf2_fe.xml
         env:
           TEST_DEVICE: CPU
           TEST_PRECISION: FP16

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py

@@ -22,6 +22,15 @@ def _prepare_input(self, inputs_info):
     def create_keras_conv_lstm_2d_net(self, params, input_shapes):
         # create TensorFlow 2 model with Keras ConvLSTM2D operation
         tf.keras.backend.clear_session()
+
+        activation = params.get('activation', None)
+        recurrent_activation = params.get('recurrent_activation', None)
+
+        if activation is not None:
+          params['activation'] = tf.keras.activations.get(activation)
+        if recurrent_activation is not None:
+          params['recurrent_activation'] = tf.keras.activations.get(recurrent_activation)
+
 
         x = tf.keras.Input(shape=input_shapes[0][1:], name="x")
         y = tf.keras.layers.ConvLSTM2D(**params)(x)
@@ -31,21 +40,21 @@ def create_keras_conv_lstm_2d_net(self, params, input_shapes):
 
     test_data_basic = [
         dict(params=dict(filters=4, kernel_size=(3, 3), padding='same', return_sequences=False,
-                         activation=tf.nn.swish),
+                         activation="swish"),
              input_shapes=[[2, 5, 20, 30, 2]]),
         dict(params=dict(filters=6, kernel_size=(2, 3), padding='valid', dilation_rate=3,
-                         recurrent_activation=tf.nn.elu, return_sequences=True, use_bias=True,
+                         recurrent_activation="elu", return_sequences=True, use_bias=True,
                          data_format="channels_first"),
              input_shapes=[[2, 5, 1, 40, 30]]),
         dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', return_sequences=False),
              input_shapes=[[2, 5, 20, 30, 1]]),
-        dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation=tf.nn.swish),
+        dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation="swish"),
              input_shapes=[[2, 5, 25, 15, 3]]),
         dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', strides=(2, 2),
                          return_sequences=True),
              input_shapes=[[2, 5, 10, 15, 2]]),
         dict(params=dict(filters=5, kernel_size=(2, 2), padding='valid', dilation_rate=3,
-                         activation=tf.nn.relu, return_sequences=False, use_bias=True,
+                         activation="relu", return_sequences=False, use_bias=True,
                          data_format="channels_last"),
              input_shapes=[[2, 5, 18, 17, 1]])
     ]

tests/layer_tests/tensorflow2_keras_tests/test_tf2_map_fn.py

@@ -20,6 +20,24 @@ def call(self, x):
                          fn_output_signature=self.fn_output_signature,
                          back_prop=self.back_prop)
 
+def fn_1(x):
+    return (x[0] * x[1] + x[2])
+
+def fn_2(x):
+    return (x[0] + x[1] + x[2], x[0] - x[2] + x[1], 2 + x[2])
+
+def fn_3(x):
+    return (x[0] * x[1], x[0] + x[1])
+
+def fn_4(x):
+    return (x[0] * x[1] + x[2], x[0] + x[2] * x[1], 2 * x[2])
+
+def fn_5(x):
+    return (x[0] * x[1] + x[2])
+
+def fn_6(x):
+    return (x[0] + x[1] + x[2], x[0] - x[2] + x[1], 2 + x[2])
+
 
 class TestMapFN(CommonTF2LayerTest):
     def create_map_fn_net(self, fn, input_type, fn_output_signature, back_prop,
@@ -39,10 +57,10 @@ def create_map_fn_net(self, fn, input_type, fn_output_signature, back_prop,
         return tf2_net, ref_net
 
     test_basic = [
-        dict(fn=lambda x: x[0] * x[1] + x[2], input_type=tf.float32,
+        dict(fn=fn_1, input_type=tf.float32,
              fn_output_signature=tf.float32, back_prop=False,
              input_names=["x1", "x2", "x3"], input_shapes=[[2, 3, 4], [2, 3, 4], [2, 3, 4]]),
-        pytest.param(dict(fn=lambda x: (x[0] + x[1] + x[2], x[0] - x[2] + x[1], 2 + x[2]),
+        pytest.param(dict(fn=fn_2,
                           input_type=tf.float32,
                           fn_output_signature=(tf.float32, tf.float32, tf.float32), back_prop=True,
                           input_names=["x1", "x2", "x3"],
@@ -77,11 +95,11 @@ def test_multiple_inputs(self, params, ie_device, precision, ir_version, temp_di
                    **params)
 
     test_multiple_outputs = [
-        pytest.param(dict(fn=lambda x: (x[0] * x[1], x[0] + x[1]), input_type=tf.float32,
+        pytest.param(dict(fn=fn_3, input_type=tf.float32,
                           fn_output_signature=(tf.float32, tf.float32), back_prop=True,
                           input_names=["x1", "x2"], input_shapes=[[2, 4], [2, 4]]),
                      marks=pytest.mark.xfail(reason="61587")),
-        pytest.param(dict(fn=lambda x: (x[0] * x[1] + x[2], x[0] + x[2] * x[1], 2 * x[2]),
+        pytest.param(dict(fn=fn_4,
                           input_type=tf.float32,
                           fn_output_signature=(tf.float32, tf.float32, tf.float32), back_prop=True,
                           input_names=["x1", "x2", "x3"],
@@ -97,17 +115,17 @@ def test_multiple_outputs(self, params, ie_device, precision, ir_version, temp_d
                    **params)
 
     test_multiple_inputs_outputs_int32 = [
-        dict(fn=lambda x: x[0] * x[1] + x[2],
+        dict(fn=fn_5,
              input_type=tf.int32,
              fn_output_signature=tf.int32, back_prop=True,
              input_names=["x1", "x2", "x3"],
              input_shapes=[[2, 1, 3], [2, 1, 3], [2, 1, 3]]),
-        pytest.param(dict(fn=lambda x: (x[0] + x[1] + x[2], x[0] - x[2] + x[1], 2 + x[2]),
+        pytest.param(dict(fn=fn_6,
                           input_type=tf.int32,
                           fn_output_signature=(tf.int32, tf.int32, tf.int32), back_prop=True,
                           input_names=["x1", "x2", "x3"],
                           input_shapes=[[2, 1, 3, 4], [2, 1, 3, 4], [2, 1, 3, 4]]),
-                     marks=[pytest.mark.xfail(reason="61587"), pytest.mark.precommit_tf_fe])
+                     marks=[pytest.mark.xfail(reason="61587")])
     ]
 
     @pytest.mark.parametrize("params", test_multiple_inputs_outputs_int32)