From 256c3468f40f56eef2e71aa69edc27d3bba40c1a Mon Sep 17 00:00:00 2001
From: Shephin philip <shephinphilipj404@gmail.com>
Date: Mon, 18 Mar 2024 11:46:13 +0530
Subject: [PATCH] Added error handling on run.py

---
 run.py | 95 ++++++++++++++++++++++++++++++++--------------------------
 1 file changed, 53 insertions(+), 42 deletions(-)

diff --git a/run.py b/run.py
index f1e157a..5a64819 100644
--- a/run.py
+++ b/run.py
@@ -22,49 +22,60 @@ CKPT_PATH = "./checkpoints/"
 
 
 def main():
-    grok_1_model = LanguageModelConfig(
-        vocab_size=128 * 1024,
-        pad_token=0,
-        eos_token=2,
-        sequence_len=8192,
-        embedding_init_scale=1.0,
-        output_multiplier_scale=0.5773502691896257,
-        embedding_multiplier_scale=78.38367176906169,
-        model=TransformerConfig(
-            emb_size=48 * 128,
-            widening_factor=8,
-            key_size=128,
-            num_q_heads=48,
-            num_kv_heads=8,
-            num_layers=64,
-            attn_output_multiplier=0.08838834764831845,
-            shard_activations=True,
-            # MoE.
-            num_experts=8,
-            num_selected_experts=2,
-            # Activation sharding.
-            data_axis="data",
-            model_axis="model",
-        ),
-    )
-    inference_runner = InferenceRunner(
-        pad_sizes=(1024,),
-        runner=ModelRunner(
-            model=grok_1_model,
-            bs_per_device=0.125,
-            checkpoint_path=CKPT_PATH,
-        ),
-        name="local",
-        load=CKPT_PATH,
-        tokenizer_path="./tokenizer.model",
-        local_mesh_config=(1, 8),
-        between_hosts_config=(1, 1),
-    )
-    inference_runner.initialize()
-    gen = inference_runner.run()
+    try:
+        grok_1_model = LanguageModelConfig(
+            vocab_size=128 * 1024,
+            pad_token=0,
+            eos_token=2,
+            sequence_len=8192,
+            embedding_init_scale=1.0,
+            output_multiplier_scale=0.5773502691896257,
+            embedding_multiplier_scale=78.38367176906169,
+            model=TransformerConfig(
+                emb_size=48 * 128,
+                widening_factor=8,
+                key_size=128,
+                num_q_heads=48,
+                num_kv_heads=8,
+                num_layers=64,
+                attn_output_multiplier=0.08838834764831845,
+                shard_activations=True,
+                # MoE.
+                num_experts=8,
+                num_selected_experts=2,
+                # Activation sharding.
+                data_axis="data",
+                model_axis="model",
+            ),
+        )
+
+        inference_runner = InferenceRunner(
+            pad_sizes=(1024,),
+            runner=ModelRunner(
+                model=grok_1_model,
+                bs_per_device=0.125,
+                checkpoint_path=CKPT_PATH,
+            ),
+            name="local",
+            load=CKPT_PATH,
+            tokenizer_path="./tokenizer.model",
+            local_mesh_config=(1, 8),
+            between_hosts_config=(1, 1),
+        )
+
+        inference_runner.initialize()
+        gen = inference_runner.run()
+
+        inp = "The answer to life the universe and everything is of course"
+        print(f"Output for prompt: {inp}", sample_from_model(gen, inp, max_len=100, temperature=0.01))
+
+    except FileNotFoundError as e:
+        logging.error(f"File not found: {e}")
+    except ValueError as e:
+        logging.error(f"Value error: {e}")
+    except Exception as e:
+        logging.error(f"An unexpected error occurred: {e}")
 
-    inp = "The answer to life the universe and everything is of course"
-    print(f"Output for prompt: {inp}", sample_from_model(gen, inp, max_len=100, temperature=0.01))
 
 
 if __name__ == "__main__":