Adds TF2 layer tests witn new FE in precommit (#13311)

* marks tf2 keras tests as precommit for new FE

* adds tf2 layers tests for new FE in precommit

* removes redundant tabulations

* review changes

* fix field name

* fix syntax error

* removes failing tests

* removes failed test

* removes failed test

.ci/azure/linux.yml

@@ -458,6 +458,15 @@ jobs:
     displayName: 'TensorFlow 1 Layer Tests - TF FE'
     continueOnError: false
 
+  - script: |
+      python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt
+      export PYTHONPATH=$(REPO_DIR)/tools/mo/:$(LAYER_TESTS_DIR):$PYTHONPATH
+      export OV_FRONTEND_PATH=$(INSTALL_DIR)/runtime/lib/intel64
+      export TEST_DEVICE=CPU
+      $(RUN_PREFIX) python3 -m pytest $(LAYER_TESTS_DIR)/tensorflow2_keras_tests/ --use_new_frontend -m precommit_tf_fe --junitxml=$(INSTALL_TEST_DIR)/TEST-tf2_fe.xmlTEST
+    displayName: 'TensorFlow 2 Layer Tests - TF FE'
+    continueOnError: false
+
   - script: |
       python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt
       export PYTHONPATH=$(LAYER_TESTS_DIR):$PYTHONPATH

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_activation.py

@@ -44,8 +44,8 @@ class TestKerasActivation(CommonTF2LayerTest):
              input_type=tf.float32),
         dict(activation_func="sigmoid", input_names=["x1"], input_shapes=[[5, 4, 8, 3]],
              input_type=tf.float32),
-        dict(activation_func="softmax", input_names=["x1"], input_shapes=[[5, 4, 8]],
-             input_type=tf.float32),
+        pytest.param(dict(activation_func="softmax", input_names=["x1"], input_shapes=[[5, 4, 8]],
+                          input_type=tf.float32), marks=pytest.mark.precommit_tf_fe),
         dict(activation_func="softsign", input_names=["x1"], input_shapes=[[5, 4]],
              input_type=tf.float32),
         dict(activation_func="swish", input_names=["x1"], input_shapes=[[5, 4, 8]],

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_avg_pool_2D.py

@@ -46,9 +46,9 @@ class TestKerasAvgPool2D(CommonTF2LayerTest):
         dict(pool_size=(5, 5), strides=None, padding='same', data_format='channels_last',
              input_names=["x1"],
              input_shapes=[[3, 4, 5, 6]], input_type=tf.float32),
-        dict(pool_size=(5, 5), strides=(3, 3), padding='valid', data_format='channels_last',
-             input_names=["x1"],
-             input_shapes=[[3, 7, 6, 5]], input_type=tf.float32)]
+        pytest.param(dict(pool_size=(5, 5), strides=(3, 3), padding='valid', data_format='channels_last',
+                          input_names=["x1"],
+                          input_shapes=[[3, 7, 6, 5]], input_type=tf.float32), marks=pytest.mark.precommit_tf_fe)]
 
     @pytest.mark.parametrize("params", test_data_extended_float32)
     @pytest.mark.nightly

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_batch_normalization.py

@@ -46,9 +46,9 @@ class TestKerasBatchNormalization(CommonTF2LayerTest):
                                        scale=False,
                                        input_names=["x1"], input_shapes=[[3, 4, 5]],
                                        input_type=tf.float32),
-                                  dict(axis=-1, momentum=0.0, epsilon=1e-5, center=True, scale=True,
-                                       input_names=["x1"], input_shapes=[[3, 4, 5, 6]],
-                                       input_type=tf.float32),
+                                  pytest.param(dict(axis=-1, momentum=0.0, epsilon=1e-5, center=True, scale=True,
+                                                    input_names=["x1"], input_shapes=[[3, 4, 5, 6]],
+                                                    input_type=tf.float32), marks=pytest.mark.precommit_tf_fe),
                                   dict(axis=[2, 1, 4], momentum=0.99, epsilon=1e-2, center=False,
                                        scale=True,
                                        input_names=["x1"], input_shapes=[[3, 4, 5, 6, 7]],

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_1d.py

@@ -47,10 +47,10 @@ class TestKerasConv1D(CommonTF2LayerTest):
         dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3),
              input_names=["x"],
              input_shapes=[[5, 7, 6]], input_type=tf.float32),
-        dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3,
-                              activation="swish",
-                              use_bias=True), input_names=["x"], input_shapes=[[5, 7, 6]],
-             input_type=tf.float32),
+        pytest.param(dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3,
+                                           activation="swish",
+                                           use_bias=True), input_names=["x"], input_shapes=[[5, 7, 6]],
+                          input_type=tf.float32), marks=pytest.mark.precommit_tf_fe),
         dict(conv_params=dict(filters=10, kernel_size=5, padding="same", dilation_rate=4,
                               activation="softmax",
                               use_bias=False), input_names=["x"], input_shapes=[[5, 7, 8]],

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_1d_transpose.py

@@ -48,15 +48,15 @@ class TestKerasConv1DTranspose(CommonTF2LayerTest):
         pytest.param(dict(
             params=dict(filters=20, kernel_size=7, padding="valid", data_format="channels_first"),
             input_names=["x"], input_shapes=[[5, 7, 8]], input_type=tf.float32),
-                     marks=pytest.mark.xfail(reason="49505")),
+            marks=pytest.mark.xfail(reason="49505")),
 
         dict(params=dict(filters=10, kernel_size=5, padding="same", strides=3), input_names=["x"],
              input_shapes=[[5, 7, 8]], input_type=tf.float32),
         dict(params=dict(filters=20, kernel_size=7, padding="valid", strides=4), input_names=["x"],
              input_shapes=[[5, 7, 8]], input_type=tf.float32),
-        dict(params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3),
-             input_names=["x"],
-             input_shapes=[[5, 7, 6]], input_type=tf.float32),
+        pytest.param(dict(params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3),
+                          input_names=["x"],
+                          input_shapes=[[5, 7, 6]], input_type=tf.float32), marks=pytest.mark.precommit_tf_fe),
         dict(params=dict(filters=20, kernel_size=7, padding="valid", data_format="channels_first"),
              input_names=["x"],
              input_shapes=[[5, 7, 8]], input_type=tf.float32),

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_2d_transpose.py

@@ -52,10 +52,10 @@ class TestKerasConv2DTranspose(CommonTF2LayerTest):
         dict(conv_params=dict(filters=10, kernel_size=5, padding="same", dilation_rate=4),
              input_names=["x"],
              input_shapes=[[3, 9, 7, 8]], input_type=tf.float32),
-        dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3,
-                              activation="sigmoid",
-                              use_bias=False), input_names=["x"], input_shapes=[[3, 9, 7, 6]],
-             input_type=tf.float32),
+        pytest.param(dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3,
+                                           activation="sigmoid",
+                                           use_bias=False), input_names=["x"], input_shapes=[[3, 9, 7, 6]],
+                          input_type=tf.float32), marks=pytest.mark.precommit_tf_fe),
         dict(conv_params=dict(filters=10, kernel_size=5, padding="same", dilation_rate=4,
                               use_bias=True),
              input_names=["x"], input_shapes=[[3, 9, 7, 8]], input_type=tf.float32)

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_cropping_2d.py

@@ -30,8 +30,8 @@ class TestKerasCropping2D(CommonTF2LayerTest):
 
         dict(cropping=(1, 2), input_names=["x"], input_shapes=[[2, 3, 7, 5]],
              input_type=tf.float32),
-        dict(cropping=((2, 1), (3, 2)), input_names=["x"], input_shapes=[[5, 7, 9, 7]],
-             input_type=tf.float32)]
+        pytest.param(dict(cropping=((2, 1), (3, 2)), input_names=["x"], input_shapes=[[5, 7, 9, 7]],
+                          input_type=tf.float32), marks=pytest.mark.precommit_tf_fe)]
 
     @pytest.mark.parametrize("params", test_data_float32)
     @pytest.mark.nightly

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_dense.py

@@ -55,8 +55,8 @@ class TestKerasDense(CommonTF2LayerTest):
              activation='elu', use_bias=False),
         dict(input_names=["x"], input_shapes=[[5, 4]], input_type=tf.float32, units=1,
              activation='sigmoid', use_bias=True),
-        dict(input_names=["x"], input_shapes=[[5, 4, 8]], input_type=tf.float32, units=4,
-             activation='tanh', use_bias=True),
+        pytest.param(dict(input_names=["x"], input_shapes=[[5, 4, 8]], input_type=tf.float32, units=4,
+                          activation='tanh', use_bias=True), marks=pytest.mark.precommit_tf_fe),
         dict(input_names=["x"], input_shapes=[[5, 4, 8, 8]], input_type=tf.float32, units=5,
              activation='linear', use_bias=True),
         dict(input_names=["x"], input_shapes=[[5, 4, 8, 6, 4]], input_type=tf.float32, units=4,

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_depthwiseconv2D.py

@@ -90,10 +90,10 @@ class TestKerasDepthwiseConv2D(CommonTF2LayerTest):
         dict(input_names=["x"], input_shapes=[[5, 16, 16, 4]], input_type=tf.float32,
              kernel_size=(3, 3), strides=(4, 4), padding='valid', depth_multiplier=2,
              data_format='channels_first', dilation_rate=1, activation='elu', use_bias=True),
-        dict(input_names=["x"], input_shapes=[[5, 8, 16, 4]], input_type=tf.float32,
-             kernel_size=(2, 2), strides=1, padding='same', depth_multiplier=2,
-             data_format='channels_last',
-             dilation_rate=(2, 2), activation='linear', use_bias=True),
+        pytest.param(dict(input_names=["x"], input_shapes=[[5, 8, 16, 4]], input_type=tf.float32,
+                          kernel_size=(2, 2), strides=1, padding='same', depth_multiplier=2,
+                          data_format='channels_last',
+                          dilation_rate=(2, 2), activation='linear', use_bias=True), marks=pytest.mark.precommit_tf_fe),
         dict(input_names=["x"], input_shapes=[[5, 16, 8, 4]], input_type=tf.float32,
              kernel_size=(2, 2), strides=(3, 3), padding='same', depth_multiplier=54,
              data_format='channels_first',

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_embedding.py

@@ -27,8 +27,8 @@ class TestKerasEmbedding(CommonTF2LayerTest):
         return tf2_net, ref_net
 
     test_data_float32 = [
-        dict(input_names=["x"], input_shapes=[[5, 16]], input_type=tf.float32, input_dim=256,
-             output_dim=8, mask_zero=True, input_length=4),
+        pytest.param(dict(input_names=["x"], input_shapes=[[5, 16]], input_type=tf.float32, input_dim=256,
+                          output_dim=8, mask_zero=True, input_length=4), marks=pytest.mark.precommit_tf_fe),
         dict(input_names=["x"], input_shapes=[[5, 16]], input_type=tf.float32, input_dim=256,
              output_dim=324, mask_zero=True, input_length=16),
         dict(input_names=["x"], input_shapes=[[5, 16]], input_type=tf.float32, input_dim=256,

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_layer_normalization.py

@@ -47,9 +47,9 @@ class TestKerasLayerNormalization(CommonTF2LayerTest):
         dict(input_names=["x"], input_shapes=[[2, 3, 8]], input_type=tf.float32, axis=2,
              epsilon=1e-6,
              center=False, scale=True),
-        dict(input_names=["x"], input_shapes=[[2, 2, 3, 5]], input_type=tf.float32, axis=(1, 2, 3),
-             epsilon=1e-5,
-             center=True, scale=True)]
+        pytest.param(dict(input_names=["x"], input_shapes=[[2, 2, 3, 5]], input_type=tf.float32, axis=(1, 2, 3),
+                          epsilon=1e-5,
+                          center=True, scale=True), marks=pytest.mark.precommit_tf_fe)]
 
     @pytest.mark.parametrize("params", test_data_float32)
     @pytest.mark.nightly

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_lstm.py

@@ -48,7 +48,7 @@ class TestKerasLSTM(CommonTF2LayerTest):
              flags=(False, False)),
         dict(input_names=["x"], input_shapes=[[1, 3, 4]], input_type=tf.float32, units=3,
              activation='linear', recurrent_activation='sigmoid', dropouts=(.4, .6),
-             flags=(False, False), use_bias=True)
+             flags=(False, False), use_bias=True),
     ]
 
     @pytest.mark.parametrize("params", test_data_simple)

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_maxpool2D.py

@@ -37,9 +37,10 @@ class TestKerasMaxPool2D(CommonTF2LayerTest):
              strides=None, padding='valid', dataformat='channels_last'),
         dict(input_names=["x"], input_shapes=[[5, 4, 5, 12]], input_type=tf.float32, pool_size=1,
              strides=4, padding='valid', dataformat='channels_last'),
-        dict(input_names=["x"], input_shapes=[[5, 4, 6, 6]], input_type=tf.float32,
-             pool_size=(2, 3),
-             strides=(3, 3), padding='valid', dataformat='channels_last'),
+        pytest.param(dict(input_names=["x"], input_shapes=[[5, 4, 6, 6]], input_type=tf.float32,
+                          pool_size=(2, 3),
+                          strides=(3, 3), padding='valid', dataformat='channels_last'),
+                     marks=pytest.mark.precommit_tf_fe),
         dict(input_names=["x"], input_shapes=[[5, 4, 4, 8]], input_type=tf.float32, pool_size=2,
              strides=2, padding='valid', dataformat='channels_last'),
     ]

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_multiheadattention.py

@@ -73,7 +73,7 @@ class TestKerasMultiHeadAttention(CommonTF2LayerTest):
                  num_heads=1, key_dim=3, value_dim=4, dropout=0.0, use_bias=True,
                  output_shape=None, attention_axes=None,
                  return_attention_scores=True, training=False),
-            marks=pytest.mark.xfail(reason="45432"))
+            marks=[pytest.mark.xfail(reason="45432"), pytest.mark.precommit_tf_fe])
     ]
 
     @pytest.mark.skip(reason='Einsum is unsupported in MO')

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_rnn.py

@@ -97,7 +97,7 @@ class TestKerasRNN(CommonTF2LayerTest):
              cell="SimpleRNNCell", return_sequences=False,
              return_state=False, go_backwards=False,
              stateful=False, unroll=False, time_major=True,
-             )
+             ),
     ]
 
     @pytest.mark.parametrize("params", test_data_others)

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_roll.py

@@ -31,8 +31,8 @@ class TestKerasRoll(CommonTF2LayerTest):
              input_type=tf.float16),
         dict(shift=[11, -8], axis=[-1, -2], input_names=["x1"], input_shapes=[[3, 4, 3, 1]],
              input_type=tf.int32),
-        dict(shift=[7, -2, 5], axis=[0, -1, -1], input_names=["x1"], input_shapes=[[5, 2, 3, 7]],
-             input_type=tf.int64),
+        pytest.param(dict(shift=[7, -2, 5], axis=[0, -1, -1], input_names=["x1"], input_shapes=[[5, 2, 3, 7]],
+                          input_type=tf.int64), marks=pytest.mark.precommit_tf_fe),
         pytest.param(
             dict(shift=[1, -2], axis=[0, 1], input_names=["x1"], input_shapes=[[2, 4, 3, 5]],
                  input_type=tf.float32),

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_separableconv2d.py

@@ -114,9 +114,10 @@ class TestKerasSeparableConv2D(CommonTF2LayerTest):
         dict(input_names=["x1"], input_shapes=[[5, 17, 14, 3]], input_type=tf.float32,
              filters=3, kernel_size=(2, 1), strides=1, padding='valid', data_format='channels_last',
              dilation_rate=1, depth_multiplier=1, activation='relu', use_bias=True),
-        dict(input_names=["x1"], input_shapes=[[1, 14, 12, 2]], input_type=tf.float32,
-             filters=4, kernel_size=(2, 2), strides=1, padding='valid', data_format='channels_last',
-             dilation_rate=2, depth_multiplier=3, activation='relu', use_bias=False),
+        pytest.param(dict(input_names=["x1"], input_shapes=[[1, 14, 12, 2]], input_type=tf.float32,
+                          filters=4, kernel_size=(2, 2), strides=1, padding='valid', data_format='channels_last',
+                          dilation_rate=2, depth_multiplier=3, activation='relu', use_bias=False),
+                     marks=pytest.mark.precommit_tf_fe),
     ]
 
     @pytest.mark.parametrize("params", test_data_different_bias)

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_upsampling2d.py

@@ -44,8 +44,9 @@ class TestKerasUpSampling2D(CommonTF2LayerTest):
 
     # Tests for bilinear interpolation
     test_data_bilinear = [
-        dict(input_names=["x1"], input_shapes=[[1, 6, 2, 1]], input_type=tf.float32,
-             size=(3, 1), data_format='channels_last', interpolation='bilinear'),
+        pytest.param(dict(input_names=["x1"], input_shapes=[[1, 6, 2, 1]], input_type=tf.float32,
+                          size=(3, 1), data_format='channels_last', interpolation='bilinear'),
+                     marks=pytest.mark.precommit_tf_fe),
         dict(input_names=["x1"], input_shapes=[[1, 3, 1, 6]], input_type=tf.float32,
              size=(5, 2), data_format='channels_last', interpolation='bilinear'),
     ]

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_zeropadding2d.py

@@ -26,8 +26,8 @@ class TestKerasZeroPadding2D(CommonTF2LayerTest):
              padding=2, data_format='channels_last'),
         dict(input_names=["x1"], input_shapes=[[3, 2, 4, 6]], input_type=tf.float32,
              padding=(3, 0), data_format='channels_last'),
-        dict(input_names=["x1"], input_shapes=[[1, 3, 8, 7]], input_type=tf.float32,
-             padding=((5, 1), (3, 4)), data_format='channels_last'),
+        pytest.param(dict(input_names=["x1"], input_shapes=[[1, 3, 8, 7]], input_type=tf.float32,
+                          padding=((5, 1), (3, 4)), data_format='channels_last'), marks=pytest.mark.precommit_tf_fe),
     ]
 
     @pytest.mark.parametrize("params", test_data_channels_last)

tests/layer_tests/tensorflow2_keras_tests/test_tf2_map_fn.py

@@ -107,7 +107,7 @@ class TestMapFN(CommonTF2LayerTest):
                           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"))
+                     marks=[pytest.mark.xfail(reason="61587"), pytest.mark.precommit_tf_fe])
     ]
 
     @pytest.mark.parametrize("params", test_multiple_inputs_outputs_int32)