Delete requests

app.py

@@ -383,7 +383,7 @@ with demo:
                     choices=[t.to_str() for t in GPUType],
                     label="GPU type",
                     multiselect=False,
-                    value=None,
+                    value="NVIDIA-A100-PCIe-80GB",
                     interactive=True,
                 )
                 
@@ -422,7 +422,7 @@ with demo:
 
             submit_button = gr.Button("Submit Eval")
             submission_result = gr.Markdown()
-            debug = gr.Textbox(label=args.debug, placeholder="main", visible=False)
+            debug = gr.Checkbox(value=args.debug, label="Debug", visible=False)
             submit_button.click(
                 add_new_eval,
                 [
@@ -434,6 +434,8 @@ with demo:
                     weight_type,
                     model_type,
                     inference_framework,
+                    debug,
+                    gpu_type
                 ],
                 submission_result,
             )

src/display/utils.py

@@ -191,9 +191,9 @@ class InferenceFramework(Enum):
         return InferenceFramework.Unknown
 
 class GPUType(Enum):
-    H100_pcie = ModelDetails("NVIDIA H100 PCIe")
-    A100_pcie = ModelDetails("NVIDIA A100 PCIe")
-    A5000 = ModelDetails("NVIDIA A5000")
+    H100_pcie = ModelDetails("NVIDIA-H100-PCIe-80GB")
+    A100_pcie = ModelDetails("NVIDIA-A100-PCIe-80GB")
+    A5000 = ModelDetails("NVIDIA-A5000-24GB")
     Unknown = ModelDetails("?")
 
     def to_str(self):
@@ -201,11 +201,11 @@ class GPUType(Enum):
 
     @staticmethod
     def from_str(gpu_type: str):
-        if gpu_type in ["NVIDIA A100 PCIe"]:
+        if gpu_type in ["NVIDIA-H100-PCIe-80GB"]:
             return GPUType.A100_pcie
-        if gpu_type in ["NVIDIA H100 PCIe"]:
+        if gpu_type in ["NVIDIA-A100-PCIe-80GB"]:
             return GPUType.H100_pcie
-        if gpu_type in ["NVIDIA A5000"]:
+        if gpu_type in ["NVIDIA-A5000-24GB"]:
             return GPUType.A5000
         return GPUType.Unknown
     

src/submission/check_validity.py

@@ -130,7 +130,7 @@ def already_submitted_models(requested_models_dir: str) -> set[str]:
                     continue
                 with open(os.path.join(root, file), "r") as f:
                     info = json.load(f)
-                    file_names.append(f"{info['model']}_{info['revision']}_{info['precision']}_{info['inference_framework']}")
+                    file_names.append(f"{info['model']}_{info['revision']}_{info['precision']}_{info['inference_framework']}_{info['gpu_type']}")
 
                     # Select organisation
                     if info["model"].count("/") == 0 or "submitted_time" not in info:

src/submission/submit.py

@@ -26,7 +26,8 @@ def add_new_eval(
     weight_type: str,
     model_type: str,
     inference_framework: str,
-    debug: bool = False
+    debug: bool = False,
+    gpu_type: str = "NVIDIA-A100-PCIe-80GB",
 ):
     global REQUESTED_MODELS
     global USERS_TO_SUBMISSION_DATES
@@ -114,17 +115,18 @@ def add_new_eval(
         "params": model_size,
         "license": license,
         "inference_framework": inference_framework,
+        "GPU_type": gpu_type
     }
 
     # Check for duplicate submission
-    if f"{model}_{revision}_{precision}_{inference_framework}" in REQUESTED_MODELS:
+    if f"{model}_{revision}_{precision}_{inference_framework}_{gpu_type}" in REQUESTED_MODELS:
         return styled_warning("This model has been already submitted.")
 
     print("Creating eval file")
     OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}"
     os.makedirs(OUT_DIR, exist_ok=True)
     # out_path = f"{OUT_DIR}/{model_path}_eval_request_{private}_{precision}_{weight_type}.json"
-    out_path = f"{OUT_DIR}/{model_path}_eval_request_{private}_{precision}_{weight_type}_{inference_framework}.json"
+    out_path = f"{OUT_DIR}/{model_path}_eval_request_{private}_{precision}_{weight_type}_{inference_framework}_{gpu_type}.json"
 
     with open(out_path, "w") as f:
         f.write(json.dumps(eval_entry))