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tests/models/pp_lcnet_v3/test_modeling_pp_lcnet_v3.py

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+# coding = utf-8
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Testing suite for the PP-LCNetV3 backbone."""
+
+import unittest
+
+from transformers import (
+    PPLCNetV3Backbone,
+    PPLCNetV3Config,
+)
+from transformers.testing_utils import (
+    is_torch_available,
+    require_torch,
+)
+
+from ...test_backbone_common import BackboneTesterMixin
+from ...test_configuration_common import ConfigTester
+from ...test_modeling_common import floats_tensor
+
+
+class PPLCNetV3ModelTester:
+    def __init__(
+        self,
+        parent,
+        batch_size=3,
+        image_size=128,
+        num_channels=3,
+        num_stages=5,
+        is_training=False,
+        scale=1.0,
+        reduction=4,
+        dropout_prob=0.2,
+        class_expand=1280,
+        use_last_convolution=True,
+        hidden_act="hardswish",
+        num_labels=4,
+        out_features=["stage2", "stage3", "stage4"],
+        out_indices=[2, 3, 4],
+        stem_channels=16,
+    ):
+        self.parent = parent
+        self.batch_size = batch_size
+        self.num_channels = num_channels
+        self.image_size = image_size
+        self.is_training = is_training
+        self.num_stages = num_stages
+        self.scale = scale
+        self.reduction = reduction
+        self.dropout_prob = dropout_prob
+        self.class_expand = class_expand
+        self.use_last_convolution = use_last_convolution
+        self.hidden_act = hidden_act
+        self.num_labels = num_labels
+        self.out_features = out_features
+        self.out_indices = out_indices
+        self.stem_channels = stem_channels
+        self.block_configs = [
+            [[3, 16, 32, 1, False]],
+            [[3, 32, 32, 2, False], [3, 32, 32, 1, False]],
+            [[3, 32, 32, 2, False], [3, 32, 32, 1, False]],
+            [
+                [3, 32, 32, 2, False],
+                [5, 32, 32, 1, False],
+                [5, 32, 32, 1, False],
+                [5, 32, 32, 1, False],
+                [5, 32, 32, 1, False],
+            ],
+            [[5, 32, 32, 2, True], [5, 32, 32, 1, True], [5, 32, 32, 1, False], [5, 32, 32, 1, False]],
+        ]
+
+    def prepare_config_and_inputs_for_common(self):
+        config, pixel_values = self.prepare_config_and_inputs()
+        inputs_dict = {"pixel_values": pixel_values}
+        return config, inputs_dict
+
+    def prepare_config_and_inputs(self):
+        pixel_values = floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])
+        config = self.get_config()
+
+        return config, pixel_values
+
+    def get_config(self) -> PPLCNetV3Config:
+        config = PPLCNetV3Config(
+            scale=self.scale,
+            reduction=self.reduction,
+            dropout_prob=self.dropout_prob,
+            class_expand=self.class_expand,
+            use_last_conv=self.use_last_convolution,
+            hidden_act=self.hidden_act,
+            out_features=self.out_features,
+            out_indices=self.out_indices,
+            block_configs=self.block_configs,
+        )
+
+        return config
+
+
+@require_torch
+class PPLCNetBackboneTest(BackboneTesterMixin, unittest.TestCase):
+    all_model_classes = (PPLCNetV3Backbone,) if is_torch_available() else ()
+    has_attentions = False
+    config_class = PPLCNetV3Config
+
+    def setUp(self):
+        self.model_tester = PPLCNetV3ModelTester(self)
+        self.config_tester = ConfigTester(
+            self,
+            config_class=PPLCNetV3Config,
+            has_text_modality=False,
+            common_properties=[],
+        )