[TF FE] Xfail Mod and FloorDiv tests and correct Conv3D test (#24126)

**Details:** Xfail Mod and FloorDiv tests due to sporadic inference
mismatch results. Correct Conv3D test to decrease workload to pass
timeout.

**Tickets:** 138904, 138713

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_3d.py

@@ -34,25 +34,25 @@ def create_keras_conv3d_net(self, conv_params, input_names, input_shapes, input_
         return tf2_net, ref_net
 
     test_data_float32 = [
-        dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", strides=(2, 2, 2)),
+        dict(conv_params=dict(filters=7, kernel_size=3, padding="valid", strides=(2, 2, 2)),
              input_names=["x"], input_shapes=[[5, 3, 5, 7, 6]], input_type=tf.float32),
-        dict(conv_params=dict(filters=10, kernel_size=5, padding="same", strides=(3, 3, 3),
+        dict(conv_params=dict(filters=5, kernel_size=5, padding="same", strides=(3, 3, 3),
                               activation="relu", use_bias=True), input_names=["x"],
              input_shapes=[[5, 3, 5, 7, 8]], input_type=tf.float32),
-        dict(conv_params=dict(filters=10, kernel_size=5, padding="same", strides=(3, 3, 3)),
+        dict(conv_params=dict(filters=5, kernel_size=5, padding="same", strides=(3, 3, 3)),
              input_names=["x"],
              input_shapes=[[5, 3, 5, 7, 8]], input_type=tf.float32),
-        dict(conv_params=dict(filters=27, kernel_size=3, padding="valid", dilation_rate=3),
+        dict(conv_params=dict(filters=7, kernel_size=3, padding="valid", dilation_rate=3),
              input_names=["x"],
              input_shapes=[[5, 8, 9, 7, 6]], input_type=tf.float32),
-        dict(conv_params=dict(filters=10, kernel_size=5, padding="same", dilation_rate=4),
+        dict(conv_params=dict(filters=5, kernel_size=5, padding="same", dilation_rate=4),
              input_names=["x"],
              input_shapes=[[5, 3, 9, 7, 8]], input_type=tf.float32),
-        dict(conv_params=dict(filters=27, kernel_size=3, padding="valid",
+        dict(conv_params=dict(filters=7, kernel_size=3, padding="valid",
                               dilation_rate=3, activation="sigmoid", use_bias=False),
              input_names=["x"],
              input_shapes=[[5, 8, 9, 7, 6]], input_type=tf.float32),
-        dict(conv_params=dict(filters=10, kernel_size=5, padding="same", dilation_rate=4,
+        dict(conv_params=dict(filters=5, kernel_size=5, padding="same", dilation_rate=4,
                               use_bias=True),
              input_names=["x"], input_shapes=[[5, 3, 9, 7, 8]], input_type=tf.float32)
     ]

tests/layer_tests/tensorflow_tests/test_tf_BinaryOps.py

@@ -112,7 +112,7 @@ def test_binary_op(self, x_shape, y_shape, ie_device, precision, ir_version, tem
             pytest.skip("Bitwise and Xdivy ops are supported only by new TF FE.")
         if op_type in ['BitwiseAnd', 'BitwiseOr', 'BitwiseXor', 'Pow', 'Mod'] and ie_device == 'GPU':
             pytest.skip("GPU does not support Bitwise ops. For Mod and Pow it has inference mismatch")
-        if op_type in ['Mod', 'FloorDiv'] and platform.machine() == 'arm64':
-            pytest.skip("Arm64 has inference mismatch for Mod and FloorDiv")
+        if op_type in ['Mod', 'FloorDiv']:
+            pytest.skip("Inference mismatch for Mod and FloorDiv")
         self._test(*self.create_add_placeholder_const_net(x_shape=x_shape, y_shape=y_shape, op_type=op_type), ie_device,
                    precision, ir_version, temp_dir=temp_dir, use_legacy_frontend=use_legacy_frontend)