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tests/models/solar_open/test_modeling_solar_open.py

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+# Copyright 2025 Upstage and 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 PyTorch SolarOpen model."""
+
+import unittest
+
+import torch
+
+from transformers import is_torch_available
+from transformers.testing_utils import (
+    Expectations,
+    cleanup,
+    require_torch,
+    require_torch_accelerator,
+    slow,
+    torch_device,
+)
+
+from ...causal_lm_tester import CausalLMModelTest, CausalLMModelTester
+
+
+if is_torch_available():
+    from transformers import AutoTokenizer, SolarOpenConfig, SolarOpenForCausalLM, SolarOpenModel
+
+
+class SolarOpenModelTester(CausalLMModelTester):
+    if is_torch_available():
+        base_model_class = SolarOpenModel
+
+    def __init__(
+        self,
+        parent,
+        n_routed_experts=8,
+        n_shared_experts=1,
+        n_group=1,
+        topk_group=1,
+        num_experts_per_tok=2,
+        moe_intermediate_size=16,
+        routed_scaling_factor=1.0,
+        norm_topk_prob=True,
+        use_qk_norm=False,
+    ):
+        super().__init__(parent=parent, num_experts_per_tok=num_experts_per_tok)
+        self.n_routed_experts = n_routed_experts
+        self.n_shared_experts = n_shared_experts
+        self.n_group = n_group
+        self.topk_group = topk_group
+        self.moe_intermediate_size = moe_intermediate_size
+        self.routed_scaling_factor = routed_scaling_factor
+        self.norm_topk_prob = norm_topk_prob
+        self.use_qk_norm = use_qk_norm
+
+
+@require_torch
+class SolarOpenModelTest(CausalLMModelTest, unittest.TestCase):
+    model_tester_class = SolarOpenModelTester
+    model_split_percents = [0.5, 0.85, 0.9]  # it tries to offload everything with the default value
+
+    def test_rope_parameters_partially_initialized(self):
+        """
+        Test for SolarOpenConfig when rope_parameters is partially initialized
+        """
+        config = SolarOpenConfig(
+            rope_parameters={
+                "rope_type": "yarn",
+                "factor": 2.0,
+                "original_max_position_embeddings": 65536,
+            }
+        )
+
+        # ensure SolarOpenConfig overrides the parent's default partial_rotary_factor to 1.0
+        self.assertEqual(config.rope_parameters["partial_rotary_factor"], 1.0)
+        self.assertEqual(config.rope_parameters["rope_theta"], 1_000_000)
+
+
+@require_torch_accelerator
+@slow
+class SolarOpenIntegrationTest(unittest.TestCase):
+    def setup(self):
+        cleanup(torch_device, gc_collect=True)
+
+    def tearDown(self):
+        cleanup(torch_device, gc_collect=True)
+
+    def test_batch_generation_dummy_bf16(self):
+        """Original model is 100B, hence using a dummy model on our CI to sanity check against"""
+        model_id = "SSON9/solar-open-tiny-dummy"
+        prompts = [
+            "Orange is the new black",
+            "Lorem ipsum dolor sit amet",
+        ]
+        # expected random outputs from the tiny dummy model
+        EXPECTED_DECODED_TEXT = Expectations(
+            {
+                ("cuda", None): [
+                    "Orange is the new blackRIB yshift yshift catheter merits catheterCCTV meritsCCTVCCTVCCTVCCTVCCTVCCTV SyllabusCCTVCCTVCCTVCCTV Syllabus",
+                    "Lorem ipsum dolor sit amet=√=√=√ 치수 치수 치수 치수 치수 치수 치수 Shelley Shelley Shelley Shelley Shelley Shelley Shelley Shelley площа площа",
+                ],
+                ("xpu", 3): [
+                    "Orange is the new blackRIB yshift yshift merits catheter merits yshiftCCTVCCTVCCTVCCTVCCTVCCTVCCTVCCTVCCTVCCTV SyllabusCCTVCCTV",
+                    "Lorem ipsum dolor sit amet=√=√ 치수=√ 치수 치수 치수 치수 치수 Shelley Shelley Shelley Shelley Shelley Shelley Shelley Shelley Shelley площа площа",
+                ],
+            }
+        ).get_expectation()
+
+        tokenizer = AutoTokenizer.from_pretrained(model_id)
+        model = SolarOpenForCausalLM.from_pretrained(
+            model_id, experts_implementation="eager", device_map=torch_device, torch_dtype=torch.bfloat16
+        )
+        inputs = tokenizer(prompts, return_tensors="pt", padding=True).to(model.device)
+
+        generated_ids = model.generate(**inputs, max_new_tokens=20, do_sample=False)
+        generated_texts = tokenizer.batch_decode(generated_ids, skip_special_tokens=False)
+
+        for text, expected_text in zip(generated_texts, EXPECTED_DECODED_TEXT):
+            self.assertEqual(text, expected_text)