[TF FE] Refactor ExtractImagePatches and add tests (#15456)

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

src/frontends/tensorflow_common/src/op/extract_image_patches.cpp

@@ -16,41 +16,36 @@ namespace tensorflow {
 namespace op {
 
 OutputVector translate_extract_image_patches_op(const NodeContext& node) {
-    TENSORFLOW_OP_VALIDATION(node, node.get_input_size() >= 0, "ExtractImagePatches must have at least one input.");
+    default_op_checks(node, 1, {"ExtractImagePatches"});
     auto images = node.get_input(0);
 
     // retrieve attributes for ExtractImagePatches
     auto tf_ksizes = node.get_attribute<std::vector<int64_t>>("ksizes");
     auto tf_strides = node.get_attribute<std::vector<int64_t>>("strides");
     auto tf_rates = node.get_attribute<std::vector<int64_t>>("rates");
-    auto tf_padding_type = node.get_attribute<std::string>("padding");
+    auto padding = node.get_attribute<std::string>("padding");
-    ov::op::PadType auto_pad = convert_tf_padding(node, tf_padding_type);
+    ov::op::PadType auto_pad = convert_tf_padding(node, padding);
     TENSORFLOW_OP_VALIDATION(node,
                              auto_pad == ov::op::PadType::SAME_UPPER || auto_pad == ov::op::PadType::VALID,
-                             "Only SAME_UPPER and VALID padding modes are supported for ExtractImagePatches.");
+                             "[TensorFlow Frontend] Inconsistent model: only SAME and VALID padding modes are "
+                             "supported for ExtractImagePatches.");
 
-    // prepare attributes for OpenVINO ExtractImagePatches
+    // prepare attributes for opset ExtractImagePatches
     Shape sizes(2);
     Shape rates(2);
     Strides strides(2);
-
+    convert_nhwc_to_hw(true, tf_ksizes, sizes);
-    // layout for this operation is always NHWC
+    convert_nhwc_to_hw(true, tf_strides, strides);
-    bool is_nhwc = true;
+    convert_nhwc_to_hw(true, tf_rates, rates);
-    convert_nhwc_to_hw(is_nhwc, tf_ksizes, sizes);
-    convert_nhwc_to_hw(is_nhwc, tf_strides, strides);
-    convert_nhwc_to_hw(is_nhwc, tf_rates, rates);
 
     // prepare input to ExtractImagePatches
-    convert_nhwc_to_nchw(is_nhwc, images);
+    convert_nhwc_to_nchw(true, images);
 
-    auto extract_image_patches = make_shared<ExtractImagePatches>(images, sizes, strides, rates, auto_pad);
+    Output<Node> extract_image_patches = make_shared<ExtractImagePatches>(images, sizes, strides, rates, auto_pad);
+    convert_nchw_to_nhwc(true, extract_image_patches);
 
-    // prepare output to return the original layout NHWC
+    set_node_name(node.get_name(), extract_image_patches.get_node_shared_ptr());
-    auto extract_image_patches_output = extract_image_patches->output(0);
+    return {extract_image_patches};
-    convert_nchw_to_nhwc(is_nhwc, extract_image_patches_output);
-
-    set_node_name(node.get_name(), extract_image_patches_output.get_node_shared_ptr());
-    return {extract_image_patches_output};
 }
 }  // namespace op
 }  // namespace tensorflow

tests/layer_tests/tensorflow_tests/test_tf_ExtractImagePatches.py

@@ -0,0 +1,44 @@
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+
+class TestExtractImagePatches(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        # generate elements so that the input tensor may contain repeating elements
+        assert 'images' in inputs_info, "Test error: inputs_info must contain `images`"
+        images_shape = inputs_info['images']
+        inputs_data = {}
+        inputs_data['images'] = np.random.randint(-10, 10, images_shape).astype(np.float32)
+        return inputs_data
+
+    def create_extract_image_patches_net(self, images_shape, ksizes, strides, rates, padding):
+        tf.compat.v1.reset_default_graph()
+        with tf.compat.v1.Session() as sess:
+            images = tf.compat.v1.placeholder(tf.float32, images_shape, 'images')
+            tf.raw_ops.ExtractImagePatches(images=images, ksizes=ksizes, strides=strides, rates=rates, padding=padding)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    test_basic = [
+        # TensorFlow supports patching only across spatial dimensions
+        dict(images_shape=[2, 110, 50, 4], ksizes=[1, 20, 30, 1], strides=[1, 5, 5, 1], rates=[1, 1, 1, 1]),
+        dict(images_shape=[3, 30, 40, 3], ksizes=[1, 5, 10, 1], strides=[1, 3, 1, 1], rates=[1, 4, 3, 1]),
+    ]
+
+    @pytest.mark.parametrize("params", test_basic)
+    @pytest.mark.parametrize("padding", ["SAME", "VALID"])
+    @pytest.mark.nightly
+    @pytest.mark.precommit_tf_fe
+    def test_extract_image_patches_basic(self, params, padding, ie_device, precision, ir_version, temp_dir,
+                                         use_new_frontend,
+                                         use_old_api):
+        self._test(*self.create_extract_image_patches_net(**params, padding=padding),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)