Change timestamp column from ISO string to Unix float64

Enables numeric sorting on the HF dataset viewer. Dataset repo has
been reset so there are no legacy string-typed rows to conflict.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

logging_utils.py

@@ -37,7 +37,7 @@ def log_inference(pil_inputs, output_pil, prompt, seed, steps, guidance_scale,
         # a 'huggingface' schema metadata key for the HF viewer to render them.
         img_struct = pa.struct([("bytes", pa.binary()), ("path", pa.string())])
         hf_meta = _json.dumps({"info": {"features": {
-            "timestamp":        {"dtype": "string",  "_type": "Value"},
+            "timestamp":        {"dtype": "float64", "_type": "Value"},
             "prompt":           {"dtype": "string",  "_type": "Value"},
             "seed":             {"dtype": "int32",   "_type": "Value"},
             "steps":            {"dtype": "int32",   "_type": "Value"},
@@ -51,7 +51,7 @@ def log_inference(pil_inputs, output_pil, prompt, seed, steps, guidance_scale,
             "error_message":    {"dtype": "string",  "_type": "Value"},
         }}}).encode()
         schema = pa.schema([
-            ("timestamp",        pa.string()),
+            ("timestamp",        pa.float64()),
             ("prompt",           pa.string()),
             ("seed",             pa.int32()),
             ("steps",            pa.int32()),
@@ -79,7 +79,7 @@ def log_inference(pil_inputs, output_pil, prompt, seed, steps, guidance_scale,
         output_jpeg = _to_jpeg(output_pil)
 
         new_table = pa.table({
-            "timestamp":        pa.array([datetime.now(timezone.utc).isoformat()], type=pa.string()),
+            "timestamp":        pa.array([datetime.now(timezone.utc).timestamp()], type=pa.float64()),
             "prompt":           pa.array([prompt],              type=pa.string()),
             "seed":             pa.array([int(seed)],           type=pa.int32()),
             "steps":            pa.array([int(steps)],          type=pa.int32()),