[TF FE] Enable parallel execution of TensorFlow Layer 2 python tests (#…

…23344)

Addresses issue: #20919 

### Details:
- Enables parallel execution of TensorFlow Layer 2 python tests
- Fixes test_tf2_keras_conv_lstm_2d.py and test_tf2_map_fn.py to not
fail during parallel execution
- Appends args in github workflow to enable parallel execution

Errors fixed:
- Due to varying Kera activation function addresses causing the workers
to get different parameter inputs and thus failing. See [known
issue](https://pytest-xdist.readthedocs.io/en/stable/known-limitations.html#order-and-amount-of-test-must-be-consistent)
```
-tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py::TestKerasConvLSTM2D::test_keras_conv_lstm_2d_basic[ ie_device:CPU - precision:FP32 - params:{'params': {'filters': 4, 'kernel_size': (3, 3), 'padding': 'same', 'return_sequences': False, 'activation': <function swish at 0x7f1fadf364d0>}, 'input_shapes': [[2, 5, 20, 30, 2]]} ]
-tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py::TestKerasConvLSTM2D::test_keras_conv_lstm_2d_basic[ ie_device:CPU - precision:FP32 - params:{'params': {'filters': 6, 'kernel_size': (2, 3), 'padding': 'valid', 'dilation_rate': 3, 'recurrent_activation': <function elu at 0x7f1fe6a1a830>, 'return_sequences': True, 'use_bias': True, 'data_format': 'channels_first'}, 'input_shapes': [[2, 5, 1, 40, 30]]} ]
+tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py::TestKerasConvLSTM2D::test_keras_conv_lstm_2d_basic[ ie_device:CPU - precision:FP32 - params:{'params': {'filters': 4, 'kernel_size': (3, 3), 'padding': 'same', 'return_sequences': False, 'activation': <function swish at 0x7f635e4d24d0>}, 'input_shapes': [[2, 5, 20, 30, 2]]} ]
+tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py::TestKerasConvLSTM2D::test_keras_conv_lstm_2d_basic[ ie_device:CPU - precision:FP32 - params:{'params': {'filters': 6, 'kernel_size': (2, 3), 'padding': 'valid', 'dilation_rate': 3, 'recurrent_activation': <function elu at 0x7f6396fa2830>, 'return_sequences': True, 'use_bias': True, 'data_format': 'channels_first'}, 'input_shapes': [[2, 5, 1, 40, 30]]} ]
```

- Due to lambda function definitions giving varying addresses as inputs
```
-tensorflow2_keras_tests/test_tf2_map_fn.py::TestMapFN::test_multiple_inputs_outputs_int32[ ie_device:CPU - precision:FP32 - params:{'fn': <function TestMapFN.<lambda> at 0x7f66c2c63c70>, '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]]} ]
-tensorflow2_keras_tests/test_tf2_map_fn.py::TestMapFN::test_multiple_inputs_outputs_int32[ ie_device:CPU - precision:FP16 - params:{'fn': <function TestMapFN.<lambda> at 0x7f66c2c63c70>, '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]]} ]
+tensorflow2_keras_tests/test_tf2_map_fn.py::TestMapFN::test_multiple_inputs_outputs_int32[ ie_device:CPU - precision:FP32 - params:{'fn': <function TestMapFN.<lambda> at 0x7f211b56fd00>, '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]]} ]
+tensorflow2_keras_tests/test_tf2_map_fn.py::TestMapFN::test_multiple_inputs_outputs_int32[ ie_device:CPU - precision:FP16 - params:{'fn': <function TestMapFN.<lambda> at 0x7f211b56fd00>, '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]]} ]
```

---------

Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>

.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

@@ -6,11 +6,36 @@
 
 from common.tf2_layer_test_class import CommonTF2LayerTest
 
+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])
+
+def fn_4(x):
+    return (x[0] * x[1] + 2 * x[2])
+
+def fn_5(x):
+    return (x[0] * x[1], x[0] + x[1])
+
+def fn_6(x):
+    return (x[0] * x[1] + x[2], x[0] + x[2] * x[1], 2 * x[2])
+
+def fn_7(x):
+    return (x[0] * x[1] + x[2])
+
+def fn_8(x):
+    return (x[0] + x[1] + x[2], x[0] - x[2] + x[1], 2 + x[2])
+
+list_fns = [fn_1, fn_2, fn_3, fn_4, fn_5, fn_6, fn_7, fn_8]
 
 class MapFNLayer(tf.keras.layers.Layer):
     def __init__(self, fn, input_type, fn_output_signature, back_prop):
         super(MapFNLayer, self).__init__()
-        self.fn = fn
+        self.fn = list_fns[fn-1]
         self.input_type = input_type
         self.fn_output_signature = fn_output_signature
         self.back_prop = back_prop
@@ -20,7 +45,6 @@ def call(self, x):
                          fn_output_signature=self.fn_output_signature,
                          back_prop=self.back_prop)
 
-
 class TestMapFN(CommonTF2LayerTest):
     def create_map_fn_net(self, fn, input_type, fn_output_signature, back_prop,
                           input_names, input_shapes, ir_version):
@@ -39,10 +63,10 @@ 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=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=2,
                           input_type=tf.float32,
                           fn_output_signature=(tf.float32, tf.float32, tf.float32), back_prop=True,
                           input_names=["x1", "x2", "x3"],
@@ -59,10 +83,10 @@ def test_basic(self, params, ie_device, precision, ir_version, temp_dir, use_leg
                    **params)
 
     test_multiple_inputs = [
-        dict(fn=lambda x: x[0] * x[1], input_type=tf.float32,
+        dict(fn=3, input_type=tf.float32,
              fn_output_signature=tf.float32, back_prop=True,
              input_names=["x1", "x2"], input_shapes=[[2, 4], [2, 4]]),
-        dict(fn=lambda x: x[0] * x[1] + 2 * x[2], input_type=tf.float32,
+        dict(fn=4, input_type=tf.float32,
              fn_output_signature=tf.float32, back_prop=False,
              input_names=["x1", "x2", "x3"], input_shapes=[[2, 1, 3, 4],
                                                            [2, 1, 3, 4],
@@ -77,11 +101,11 @@ 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=5, 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=6,
                           input_type=tf.float32,
                           fn_output_signature=(tf.float32, tf.float32, tf.float32), back_prop=True,
                           input_names=["x1", "x2", "x3"],
@@ -97,12 +121,12 @@ 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=7,
              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=8,
                           input_type=tf.int32,
                           fn_output_signature=(tf.int32, tf.int32, tf.int32), back_prop=True,
                           input_names=["x1", "x2", "x3"],