Added temperature in generation

gpt2.py

@@ -83,18 +83,18 @@ def gpt2(inputs, wte, wpe, blocks, ln_f, n_head):  # [n_seq] -> [n_seq, n_vocab]
     return x @ wte.T  # [n_seq, n_embd] -> [n_seq, n_vocab]
 
 
-def generate(inputs, params, n_head, n_tokens_to_generate):
+def generate(inputs, params, n_head, n_tokens_to_generate,temperature):
     from tqdm import tqdm
 
     for _ in tqdm(range(n_tokens_to_generate), "generating"):  # auto-regressive decode loop
         logits = gpt2(inputs, **params, n_head=n_head)  # model forward pass
-        next_id = np.argmax(logits[-1])  # greedy sampling
+        next_id = np.argmax(softmax(logits[-1])/temperature)  # greedy sampling ## Added Temperature
         inputs.append(int(next_id))  # append prediction to input
 
     return inputs[len(inputs) - n_tokens_to_generate :]  # only return generated ids
 
 
-def main(prompt: str, n_tokens_to_generate: int = 40, model_size: str = "124M", models_dir: str = "models"):
+def main(prompt: str, n_tokens_to_generate: int = 40, model_size: str = "124M", models_dir: str = "models",temperature = 1.0):
     from utils import load_encoder_hparams_and_params
 
     # load encoder, hparams, and params from the released open-ai gpt-2 files
@@ -107,7 +107,7 @@ def main(prompt: str, n_tokens_to_generate: int = 40, model_size: str = "124M",
     assert len(input_ids) + n_tokens_to_generate < hparams["n_ctx"]
 
     # generate output ids
-    output_ids = generate(input_ids, params, hparams["n_head"], n_tokens_to_generate)
+    output_ids = generate(input_ids, params, hparams["n_head"], n_tokens_to_generate,temperature)
 
     # decode the ids back into a string
     output_text = encoder.decode(output_ids)