[Fix: pixart-alpha] random 512px resolution bug (#5842)

* [Fix: pixart-alpha]
add ASPECT_RATIO_512_BIN in use_resolution_binning for random 512px image generation.

* add slow test file for 512px generation without resolution binning

* fix: slow tests for resolution binning.

---------
Co-authored-by: jschen <chenjunsong4@h-partners.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

src/diffusers/pipelines/pixart_alpha/pipeline_pixart_alpha.py

@@ -97,6 +97,42 @@ ASPECT_RATIO_1024_BIN = {
     "4.0": [2048.0, 512.0],
 }
 
+ASPECT_RATIO_512_BIN = {
+    "0.25": [256.0, 1024.0],
+    "0.28": [256.0, 928.0],
+    "0.32": [288.0, 896.0],
+    "0.33": [288.0, 864.0],
+    "0.35": [288.0, 832.0],
+    "0.4": [320.0, 800.0],
+    "0.42": [320.0, 768.0],
+    "0.48": [352.0, 736.0],
+    "0.5": [352.0, 704.0],
+    "0.52": [352.0, 672.0],
+    "0.57": [384.0, 672.0],
+    "0.6": [384.0, 640.0],
+    "0.68": [416.0, 608.0],
+    "0.72": [416.0, 576.0],
+    "0.78": [448.0, 576.0],
+    "0.82": [448.0, 544.0],
+    "0.88": [480.0, 544.0],
+    "0.94": [480.0, 512.0],
+    "1.0": [512.0, 512.0],
+    "1.07": [512.0, 480.0],
+    "1.13": [544.0, 480.0],
+    "1.21": [544.0, 448.0],
+    "1.29": [576.0, 448.0],
+    "1.38": [576.0, 416.0],
+    "1.46": [608.0, 416.0],
+    "1.67": [640.0, 384.0],
+    "1.75": [672.0, 384.0],
+    "2.0": [704.0, 352.0],
+    "2.09": [736.0, 352.0],
+    "2.4": [768.0, 320.0],
+    "2.5": [800.0, 320.0],
+    "3.0": [864.0, 288.0],
+    "4.0": [1024.0, 256.0],
+}
+
 
 class PixArtAlphaPipeline(DiffusionPipeline):
     r"""
@@ -691,8 +727,11 @@ class PixArtAlphaPipeline(DiffusionPipeline):
         height = height or self.transformer.config.sample_size * self.vae_scale_factor
         width = width or self.transformer.config.sample_size * self.vae_scale_factor
         if use_resolution_binning:
+            aspect_ratio_bin = (
+                ASPECT_RATIO_1024_BIN if self.transformer.config.sample_size == 128 else ASPECT_RATIO_512_BIN
+            )
             orig_height, orig_width = height, width
-            height, width = self.classify_height_width_bin(height, width, ratios=ASPECT_RATIO_1024_BIN)
+            height, width = self.classify_height_width_bin(height, width, ratios=aspect_ratio_bin)
 
         self.check_inputs(
             prompt,

tests/pipelines/pixart/test_pixart.py

@@ -320,6 +320,10 @@ class PixArtAlphaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 @slow
 @require_torch_gpu
 class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
+    ckpt_id_1024 = "PixArt-alpha/PixArt-XL-2-1024-MS"
+    ckpt_id_512 = "PixArt-alpha/PixArt-XL-2-512x512"
+    prompt = "A small cactus with a happy face in the Sahara desert."
+
     def tearDown(self):
         super().tearDown()
         gc.collect()
@@ -328,10 +332,10 @@ class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
     def test_pixart_1024_fast(self):
         generator = torch.manual_seed(0)
 
-        pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", torch_dtype=torch.float16)
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_1024, torch_dtype=torch.float16)
         pipe.enable_model_cpu_offload()
 
-        prompt = "A small cactus with a happy face in the Sahara desert."
+        prompt = self.prompt
 
         image = pipe(prompt, generator=generator, num_inference_steps=2, output_type="np").images
 
@@ -345,10 +349,10 @@ class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
     def test_pixart_512_fast(self):
         generator = torch.manual_seed(0)
 
-        pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-512x512", torch_dtype=torch.float16)
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_512, torch_dtype=torch.float16)
         pipe.enable_model_cpu_offload()
 
-        prompt = "A small cactus with a happy face in the Sahara desert."
+        prompt = self.prompt
 
         image = pipe(prompt, generator=generator, num_inference_steps=2, output_type="np").images
 
@@ -362,9 +366,9 @@ class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
     def test_pixart_1024(self):
         generator = torch.manual_seed(0)
 
-        pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", torch_dtype=torch.float16)
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_1024, torch_dtype=torch.float16)
         pipe.enable_model_cpu_offload()
-        prompt = "A small cactus with a happy face in the Sahara desert."
+        prompt = self.prompt
 
         image = pipe(prompt, generator=generator, output_type="np").images
 
@@ -378,10 +382,10 @@ class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
     def test_pixart_512(self):
         generator = torch.manual_seed(0)
 
-        pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-512x512", torch_dtype=torch.float16)
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_512, torch_dtype=torch.float16)
         pipe.enable_model_cpu_offload()
 
-        prompt = "A small cactus with a happy face in the Sahara desert."
+        prompt = self.prompt
 
         image = pipe(prompt, generator=generator, output_type="np").images
 
@@ -395,17 +399,66 @@ class PixArtAlphaPipelineIntegrationTests(unittest.TestCase):
     def test_pixart_1024_without_resolution_binning(self):
         generator = torch.manual_seed(0)
 
-        pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", torch_dtype=torch.float16)
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_1024, torch_dtype=torch.float16)
         pipe.enable_model_cpu_offload()
 
-        prompt = "A small cactus with a happy face in the Sahara desert."
+        prompt = self.prompt
+        height, width = 1024, 768
+        num_inference_steps = 10
+
+        image = pipe(
+            prompt,
+            height=height,
+            width=width,
+            generator=generator,
+            num_inference_steps=num_inference_steps,
+            output_type="np",
+        ).images
+        image_slice = image[0, -3:, -3:, -1]
 
-        image = pipe(prompt, generator=generator, num_inference_steps=5, output_type="np").images
+        generator = torch.manual_seed(0)
+        no_res_bin_image = pipe(
+            prompt,
+            height=height,
+            width=width,
+            generator=generator,
+            num_inference_steps=num_inference_steps,
+            output_type="np",
+            use_resolution_binning=False,
+        ).images
+        no_res_bin_image_slice = no_res_bin_image[0, -3:, -3:, -1]
+
+        assert not np.allclose(image_slice, no_res_bin_image_slice, atol=1e-4, rtol=1e-4)
+
+    def test_pixart_512_without_resolution_binning(self):
+        generator = torch.manual_seed(0)
+
+        pipe = PixArtAlphaPipeline.from_pretrained(self.ckpt_id_512, torch_dtype=torch.float16)
+        pipe.enable_model_cpu_offload()
+
+        prompt = self.prompt
+        height, width = 512, 768
+        num_inference_steps = 10
+
+        image = pipe(
+            prompt,
+            height=height,
+            width=width,
+            generator=generator,
+            num_inference_steps=num_inference_steps,
+            output_type="np",
+        ).images
         image_slice = image[0, -3:, -3:, -1]
 
         generator = torch.manual_seed(0)
         no_res_bin_image = pipe(
-            prompt, generator=generator, num_inference_steps=5, output_type="np", use_resolution_binning=False
+            prompt,
+            height=height,
+            width=width,
+            generator=generator,
+            num_inference_steps=num_inference_steps,
+            output_type="np",
+            use_resolution_binning=False,
         ).images
         no_res_bin_image_slice = no_res_bin_image[0, -3:, -3:, -1]