add lora tests

Author: sayakpaul

tests/lora/test_lora_layers_qwenimage.py

@@ -0,0 +1,134 @@
+# coding=utf-8
+# Copyright 2025 HuggingFace Inc.
+#
+# 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.
+import sys
+import unittest
+
+import torch
+from transformers import Qwen2_5_VLForConditionalGeneration, Qwen2Tokenizer
+
+from diffusers import (
+    AutoencoderKLQwenImage,
+    FlowMatchEulerDiscreteScheduler,
+    QwenImagePipeline,
+    QwenImageTransformer2DModel,
+)
+from diffusers.utils.testing_utils import floats_tensor, is_peft_available, require_peft_backend
+
+
+if is_peft_available():
+    pass
+
+sys.path.append(".")
+
+from utils import PeftLoraLoaderMixinTests  # noqa: E402
+
+
+@require_peft_backend
+class QwenImageLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
+    pipeline_class = QwenImagePipeline
+    scheduler_cls = FlowMatchEulerDiscreteScheduler
+    scheduler_classes = [FlowMatchEulerDiscreteScheduler]
+    scheduler_kwargs = {}
+
+    transformer_kwargs = {
+        "patch_size": 2,
+        "in_channels": 16,
+        "out_channels": 4,
+        "num_layers": 2,
+        "attention_head_dim": 16,
+        "num_attention_heads": 3,
+        "joint_attention_dim": 16,
+        "guidance_embeds": False,
+        "axes_dims_rope": (8, 4, 4),
+    }
+    transformer_cls = QwenImageTransformer2DModel
+    z_dim = 4
+    vae_kwargs = {
+        "base_dim": z_dim * 6,
+        "z_dim": z_dim,
+        "dim_mult": [1, 2, 4],
+        "num_res_blocks": 1,
+        "temperal_downsample": [False, True],
+        # fmt: off
+        "latents_mean": [0.0] * 4,
+        "latents_std": [1.0] * 4,
+        # fmt: on
+    }
+    vae_cls = AutoencoderKLQwenImage
+    tokenizer_cls, tokenizer_id = Qwen2Tokenizer, "hf-internal-testing/tiny-random-Qwen25VLForCondGen"
+    text_encoder_cls, text_encoder_id = (
+        Qwen2_5_VLForConditionalGeneration,
+        "hf-internal-testing/tiny-random-Qwen25VLForCondGen",
+    )
+    denoiser_target_modules = ["to_q", "to_k", "to_v", "to_out.0"]
+
+    @property
+    def output_shape(self):
+        return (1, 8, 8, 3)
+
+    def get_dummy_inputs(self, with_generator=True):
+        batch_size = 1
+        sequence_length = 10
+        num_channels = 4
+        sizes = (32, 32)
+
+        generator = torch.manual_seed(0)
+        noise = floats_tensor((batch_size, num_channels) + sizes)
+        input_ids = torch.randint(1, sequence_length, size=(batch_size, sequence_length), generator=generator)
+
+        pipeline_inputs = {
+            "prompt": "A painting of a squirrel eating a burger",
+            "num_inference_steps": 4,
+            "guidance_scale": 0.0,
+            "height": 8,
+            "width": 8,
+            "output_type": "np",
+        }
+        if with_generator:
+            pipeline_inputs.update({"generator": generator})
+
+        return noise, input_ids, pipeline_inputs
+
+    @unittest.skip("Not supported in Qwen Image.")
+    def test_simple_inference_with_text_denoiser_block_scale(self):
+        pass
+
+    @unittest.skip("Not supported in Qwen Image.")
+    def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(self):
+        pass
+
+    @unittest.skip("Not supported in Qwen Image.")
+    def test_modify_padding_mode(self):
+        pass
+
+    @unittest.skip("Text encoder LoRA is not supported in Qwen Image.")
+    def test_simple_inference_with_partial_text_lora(self):
+        pass
+
+    @unittest.skip("Text encoder LoRA is not supported in Qwen Image.")
+    def test_simple_inference_with_text_lora(self):
+        pass
+
+    @unittest.skip("Text encoder LoRA is not supported in Qwen Image.")
+    def test_simple_inference_with_text_lora_and_scale(self):
+        pass
+
+    @unittest.skip("Text encoder LoRA is not supported in Qwen Image.")
+    def test_simple_inference_with_text_lora_fused(self):
+        pass
+
+    @unittest.skip("Text encoder LoRA is not supported in Qwen Image.")
+    def test_simple_inference_with_text_lora_save_load(self):
+        pass