@@ -155,7 +155,7 @@ def test_flux_different_prompts(self):
155155
156156        # Outputs should be different here 
157157        # For some reasons, they don't show large differences 
158-         assert   max_diff   >   1e-6 
158+         self . assertGreater ( max_diff ,  1e-6 ,  "Outputs should be different for different prompts." ) 
159159
160160    def  test_fused_qkv_projections (self ):
161161        device  =  "cpu"   # ensure determinism for the device-dependent torch.Generator 
@@ -187,14 +187,17 @@ def test_fused_qkv_projections(self):
187187        image  =  pipe (** inputs ).images 
188188        image_slice_disabled  =  image [0 , - 3 :, - 3 :, - 1 ]
189189
190-         assert  np .allclose (original_image_slice , image_slice_fused , atol = 1e-3 , rtol = 1e-3 ), (
191-             "Fusion of QKV projections shouldn't affect the outputs." 
190+         self .assertTrue (
191+             np .allclose (original_image_slice , image_slice_fused , atol = 1e-3 , rtol = 1e-3 ),
192+             ("Fusion of QKV projections shouldn't affect the outputs." ),
192193        )
193-         assert  np .allclose (image_slice_fused , image_slice_disabled , atol = 1e-3 , rtol = 1e-3 ), (
194-             "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled." 
194+         self .assertTrue (
195+             np .allclose (image_slice_fused , image_slice_disabled , atol = 1e-3 , rtol = 1e-3 ),
196+             ("Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled." ),
195197        )
196-         assert  np .allclose (original_image_slice , image_slice_disabled , atol = 1e-2 , rtol = 1e-2 ), (
197-             "Original outputs should match when fused QKV projections are disabled." 
198+         self .assertTrue (
199+             np .allclose (original_image_slice , image_slice_disabled , atol = 1e-2 , rtol = 1e-2 ),
200+             ("Original outputs should match when fused QKV projections are disabled." ),
198201        )
199202
200203    def  test_flux_image_output_shape (self ):
@@ -209,7 +212,11 @@ def test_flux_image_output_shape(self):
209212            inputs .update ({"height" : height , "width" : width })
210213            image  =  pipe (** inputs ).images [0 ]
211214            output_height , output_width , _  =  image .shape 
212-             assert  (output_height , output_width ) ==  (expected_height , expected_width )
215+             self .assertEqual (
216+                 (output_height , output_width ),
217+                 (expected_height , expected_width ),
218+                 f"Output shape { image .shape } { (expected_height , expected_width )}  ,
219+             )
213220
214221    def  test_flux_true_cfg (self ):
215222        pipe  =  self .pipeline_class (** self .get_dummy_components ()).to (torch_device )
@@ -220,7 +227,9 @@ def test_flux_true_cfg(self):
220227        inputs ["negative_prompt" ] =  "bad quality" 
221228        inputs ["true_cfg_scale" ] =  2.0 
222229        true_cfg_out  =  pipe (** inputs , generator = torch .manual_seed (0 )).images [0 ]
223-         assert  not  np .allclose (no_true_cfg_out , true_cfg_out )
230+         self .assertFalse (
231+             np .allclose (no_true_cfg_out , true_cfg_out ), "Outputs should be different when true_cfg_scale is set." 
232+         )
224233
225234
226235@nightly  
@@ -269,45 +278,17 @@ def test_flux_inference(self):
269278
270279        image  =  pipe (** inputs ).images [0 ]
271280        image_slice  =  image [0 , :10 , :10 ]
281+         # fmt: off 
272282        expected_slice  =  np .array (
273-             [
274-                 0.3242 ,
275-                 0.3203 ,
276-                 0.3164 ,
277-                 0.3164 ,
278-                 0.3125 ,
279-                 0.3125 ,
280-                 0.3281 ,
281-                 0.3242 ,
282-                 0.3203 ,
283-                 0.3301 ,
284-                 0.3262 ,
285-                 0.3242 ,
286-                 0.3281 ,
287-                 0.3242 ,
288-                 0.3203 ,
289-                 0.3262 ,
290-                 0.3262 ,
291-                 0.3164 ,
292-                 0.3262 ,
293-                 0.3281 ,
294-                 0.3184 ,
295-                 0.3281 ,
296-                 0.3281 ,
297-                 0.3203 ,
298-                 0.3281 ,
299-                 0.3281 ,
300-                 0.3164 ,
301-                 0.3320 ,
302-                 0.3320 ,
303-                 0.3203 ,
304-             ],
283+             [0.3242 , 0.3203 , 0.3164 , 0.3164 , 0.3125 , 0.3125 , 0.3281 , 0.3242 , 0.3203 , 0.3301 , 0.3262 , 0.3242 , 0.3281 , 0.3242 , 0.3203 , 0.3262 , 0.3262 , 0.3164 , 0.3262 , 0.3281 , 0.3184 , 0.3281 , 0.3281 , 0.3203 , 0.3281 , 0.3281 , 0.3164 , 0.3320 , 0.3320 , 0.3203 ],
305284            dtype = np .float32 ,
306285        )
286+         # fmt: on 
307287
308288        max_diff  =  numpy_cosine_similarity_distance (expected_slice .flatten (), image_slice .flatten ())
309- 
310-         assert  max_diff  <  1e-4 
289+         self .assertLess (
290+             max_diff , 1e-4 , f"Image slice is different from expected slice: { image_slice } { expected_slice }  
291+         )
311292
312293
313294@slow  
@@ -377,42 +358,14 @@ def test_flux_ip_adapter_inference(self):
377358        image  =  pipe (** inputs ).images [0 ]
378359        image_slice  =  image [0 , :10 , :10 ]
379360
361+         # fmt: off 
380362        expected_slice  =  np .array (
381-             [
382-                 0.1855 ,
383-                 0.1680 ,
384-                 0.1406 ,
385-                 0.1953 ,
386-                 0.1699 ,
387-                 0.1465 ,
388-                 0.2012 ,
389-                 0.1738 ,
390-                 0.1484 ,
391-                 0.2051 ,
392-                 0.1797 ,
393-                 0.1523 ,
394-                 0.2012 ,
395-                 0.1719 ,
396-                 0.1445 ,
397-                 0.2070 ,
398-                 0.1777 ,
399-                 0.1465 ,
400-                 0.2090 ,
401-                 0.1836 ,
402-                 0.1484 ,
403-                 0.2129 ,
404-                 0.1875 ,
405-                 0.1523 ,
406-                 0.2090 ,
407-                 0.1816 ,
408-                 0.1484 ,
409-                 0.2110 ,
410-                 0.1836 ,
411-                 0.1543 ,
412-             ],
363+             [0.1855 , 0.1680 , 0.1406 , 0.1953 , 0.1699 , 0.1465 , 0.2012 , 0.1738 , 0.1484 , 0.2051 , 0.1797 , 0.1523 , 0.2012 , 0.1719 , 0.1445 , 0.2070 , 0.1777 , 0.1465 , 0.2090 , 0.1836 , 0.1484 , 0.2129 , 0.1875 , 0.1523 , 0.2090 , 0.1816 , 0.1484 , 0.2110 , 0.1836 , 0.1543 ],
413364            dtype = np .float32 ,
414365        )
366+         # fmt: on 
415367
416368        max_diff  =  numpy_cosine_similarity_distance (expected_slice .flatten (), image_slice .flatten ())
417- 
418-         assert  max_diff  <  1e-4 , f"{ image_slice } { expected_slice }  
369+         self .assertLess (
370+             max_diff , 1e-4 , f"Image slice is different from expected slice: { image_slice } { expected_slice }  
371+         )
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