seems to be working.

Author: sayakpaul

benchmarks/benchmarking_flux.py

@@ -8,6 +8,7 @@
 
 
 CKPT_ID = "black-forest-labs/FLUX.1-dev"
+RESULT_FILENAME = "flux.csv"
 
 
 def get_input_dict(**device_dtype_kwargs):
@@ -94,4 +95,4 @@ def get_input_dict(**device_dtype_kwargs):
     ]
 
     runner = BenchmarkMixin()
-    runner.run_bencmarks_and_collate(scenarios, filename="flux.csv")
+    runner.run_bencmarks_and_collate(scenarios, filename=RESULT_FILENAME)

benchmarks/benchmarking_ltx.py

@@ -8,6 +8,7 @@
 
 
 CKPT_ID = "Lightricks/LTX-Video-0.9.7-dev"
+RESULT_FILENAME = "ltx.csv"
 
 
 def get_input_dict(**device_dtype_kwargs):
@@ -76,4 +77,4 @@ def get_input_dict(**device_dtype_kwargs):
     ]
 
     runner = BenchmarkMixin()
-    runner.run_bencmarks_and_collate(scenarios, filename="ltx.csv")
+    runner.run_bencmarks_and_collate(scenarios, filename=RESULT_FILENAME)

benchmarks/benchmarking_sdxl.py

@@ -8,6 +8,7 @@
 
 
 CKPT_ID = "stabilityai/stable-diffusion-xl-base-1.0"
+RESULT_FILENAME = "sdxl.csv"
 
 
 def get_input_dict(**device_dtype_kwargs):
@@ -78,4 +79,4 @@ def get_input_dict(**device_dtype_kwargs):
     ]
 
     runner = BenchmarkMixin()
-    runner.run_bencmarks_and_collate(scenarios, filename="sdxl.csv")
+    runner.run_bencmarks_and_collate(scenarios, filename=RESULT_FILENAME)

benchmarks/benchmarking_wan.py

@@ -8,6 +8,7 @@
 
 
 CKPT_ID = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
+RESULT_FILENAME = "wan.csv"
 
 
 def get_input_dict(**device_dtype_kwargs):
@@ -70,4 +71,4 @@ def get_input_dict(**device_dtype_kwargs):
     ]
 
     runner = BenchmarkMixin()
-    runner.run_bencmarks_and_collate(scenarios, filename="wan.csv")
+    runner.run_bencmarks_and_collate(scenarios, filename=RESULT_FILENAME)

benchmarks/push_results.py

@@ -45,11 +45,7 @@ def push_to_hf_dataset():
 
         for column in numeric_columns:
             # get previous values as floats, aligned to current index
-            prev_vals = (
-                previous_results[column]
-                .map(filter_float)
-                .reindex(current_results.index)
-            )
+            prev_vals = previous_results[column].map(filter_float).reindex(current_results.index)
 
             # get current values as floats
             curr_vals = current_results[column].astype(float)
@@ -58,21 +54,16 @@ def push_to_hf_dataset():
             curr_str = curr_vals.map(str)
 
             # build an appendage only when prev exists and differs
-            append_str = prev_vals.where(
-                prev_vals.notnull() & (prev_vals != curr_vals),
-                other=pd.NA
-            ).map(lambda x: f" ({x})" if pd.notnull(x) else "")
+            append_str = prev_vals.where(prev_vals.notnull() & (prev_vals != curr_vals), other=pd.NA).map(
+                lambda x: f" ({x})" if pd.notnull(x) else ""
+            )
 
             # combine
             current_results[column] = curr_str + append_str
 
         current_results.to_csv(FINAL_CSV_FILENAME, index=False)
 
-    commit_message = (
-        f"upload from sha: {GITHUB_SHA}"
-        if GITHUB_SHA is not None else
-        "upload benchmark results"
-    )
+    commit_message = f"upload from sha: {GITHUB_SHA}" if GITHUB_SHA is not None else "upload benchmark results"
     upload_file(
         repo_id=REPO_ID,
         path_in_repo=FINAL_CSV_FILENAME,

benchmarks/run_all.py

@@ -4,12 +4,17 @@
 
 import pandas as pd
 
+from diffusers.utils import logging
+
 
 PATTERN = "benchmarking_*.py"
 FINAL_CSV_FILENAME = "collated_results.csv"
 GITHUB_SHA = os.getenv("GITHUB_SHA", None)
 
 
+logger = logging.get_logger(__name__)
+
+
 class SubprocessCallException(Exception):
     pass
 
@@ -37,7 +42,7 @@ def run_scripts():
 
     for file in python_files:
         if file != "benchmarking_utils.py":
-            print(f"****** Running file: {file} ******")
+            logger.info(f"****** Running file: {file} ******")
             command = f"python {file}"
             run_command(command.split())