misc improvements

RWKV-v4neo/run.py

@@ -22,7 +22,7 @@ args = types.SimpleNamespace()
 ########################################################################################################
 
 args.RUN_DEVICE = "cpu"  # 'cpu' (already very fast) // 'cuda'
-args.FLOAT_MODE = "fp32" # fp32 (good for cpu) // fp16 (might overflow) // bf16 (less accurate)
+args.FLOAT_MODE = "fp32" # fp32 (good for CPU) // fp16 (recommended for GPU) // bf16 (less accurate)
 # if args.RUN_DEVICE == "cuda":
 #     os.environ["RWKV_RUN_BACKEND"] = 'nvfuser' # !!!BUGGY!!! wrong output
 
@@ -87,25 +87,25 @@ context = "\nIn a shocking finding, scientist discovered a herd of dragons livin
 
 ###### A good prompt for chatbot ######
 # context = '''
-# The following is a conversation between a highly knowledgeable and intelligent AI assistant, called RWKV, and a human user, called User. In the following interactions, User and RWKV will converse in natural language, and RWKV will do its best to answer User’s questions. RWKV was built to be respectful, polite and inclusive. It knows a lot, and always tells the truth. The conversation begins.
+# The following is a conversation between a highly knowledgeable and intelligent AI assistant called Bot, and a human user called User. In the following interactions, User and Bot converse in natural language, and Bot always answer User's questions. Bot is very smart, polite and humorous. Bot knows a lot, and always tells the truth. The conversation begins.
 
-# User: OK RWKV, I’m going to start by quizzing you with a few warm-up questions. Who is currently the president of the USA?
+# User: who is president of usa?
 
-# RWKV: It’s Joe Biden; he was sworn in earlier this year.
+# Bot: It’s Joe Biden; he was sworn in earlier this year.
 
-# User: What year was the French Revolution?
+# User: french revolution what year
 
-# RWKV: It started in 1789, but it lasted 10 years until 1799.
+# Bot: It started in 1789, but it lasted 10 years until 1799.
 
-# User: Can you guess who I might want to marry?
+# User: guess i marry who ?
 
-# RWKV: Only if you tell me more about yourself - what are your interests?
+# Bot: Only if you tell me more about yourself - what are your interests?
 
-# User: Aha, I’m going to refrain from that for now. Now for a science question. What can you tell me about the Large Hadron Collider (LHC)?
+# User: wat is lhc
 
-# RWKV: It’s a large and very expensive piece of science equipment. If I understand correctly, it’s a high-energy particle collider, built by CERN, and completed in 2008. They used it to confirm the existence of the Higgs boson in 2012.
+# Bot: It’s a large and very expensive piece of science equipment. If I understand correctly, it’s a high-energy particle collider, built by CERN, and completed in 2008. They used it to confirm the existence of the Higgs boson in 2012.
 
-# User:'''
+# User:''' # type your question here
 
 NUM_TRIALS = 999
 LENGTH_PER_TRIAL = 333

RWKV-v4neo/src/trainer.py

@@ -124,8 +124,8 @@ class train_callback(pl.Callback):
                         to_save_dict,
                         f"{args.proj_dir}/rwkv-{args.epoch_begin + trainer.current_epoch}.pth",
                     )
-                except:
-                    pass
+                except Exception as e:
+                    print('Error\n\n', e, '\n\n')
             trainer.my_log.write(f"{args.epoch_begin + trainer.current_epoch} {trainer.my_epoch_loss:.6f} {math.exp(trainer.my_epoch_loss):.4f} {trainer.my_lr:.8f} {datetime.datetime.now()} {trainer.current_epoch}\n")
             trainer.my_log.flush()
 

RWKV-v4neo/verify.py

@@ -0,0 +1,104 @@
+########################################################################################################
+# The RWKV Language Model - https://github.com/BlinkDL/RWKV-LM
+########################################################################################################
+
+# this is for verifying the results of different models and make sure they agree with each other
+
+import os, sys, types
+import numpy as np
+import torch
+np.set_printoptions(precision=4, suppress=True, linewidth=200)
+try:
+    os.environ["CUDA_VISIBLE_DEVICES"] = sys.argv[1]
+except:
+    pass
+torch.backends.cudnn.benchmark = True
+torch.backends.cudnn.allow_tf32 = False
+torch.backends.cuda.matmul.allow_tf32 = False
+
+os.environ['RWKV_FLOAT_MODE'] = 'bf16' # bf16 or fp32
+os.environ['RWKV_RUN_DEVICE'] = 'cuda' # currently model_train requires CUDA
+RUN_DEVICE = os.environ['RWKV_RUN_DEVICE']
+
+TOKEN_MODE = 'pile'
+
+if TOKEN_MODE == 'pile':
+    WORD_NAME = ['20B_tokenizer.json', '20B_tokenizer.json']
+    MODEL_NAME = '/fsx/BlinkDL/HF-MODEL/rwkv-4-pile-3b/RWKV-4-Pile-3B-20221003-6783'
+    n_layer = 32
+    n_embd = 2560
+    ctx_len = 1024
+    UNKNOWN_CHAR = None
+
+from src.utils import TOKENIZER
+tokenizer = TOKENIZER(WORD_NAME, UNKNOWN_CHAR=UNKNOWN_CHAR)
+if TOKEN_MODE == 'pile':
+    tokenizer.vocab_size = 50277
+
+########################################################################################################
+
+os.environ["RWKV_JIT_ON"] = "1"
+os.environ["RWKV_T_MAX"] = str(ctx_len)
+
+from src.model_run import RWKV_RNN
+from src.model import RWKV
+
+args = types.SimpleNamespace()
+args.vocab_size = tokenizer.vocab_size
+args.ctx_len = ctx_len
+args.n_embd = n_embd
+args.n_layer = n_layer
+args.head_qk = 0
+args.pre_ffn = 0
+args.grad_cp = 0
+args.my_pos_emb = 0
+model_train = RWKV(args).to(RUN_DEVICE)
+
+if os.environ['RWKV_FLOAT_MODE'] == 'fp16':
+    model_train = model_train.half()
+elif os.environ['RWKV_FLOAT_MODE'] == 'bf16':
+    model_train = model_train.bfloat16()
+
+print('loading ' + MODEL_NAME)
+m2 = torch.load(MODEL_NAME + '.pth', map_location='cpu')
+model_train.load_state_dict(m2)
+
+if os.environ['RWKV_FLOAT_MODE'] == 'fp16':
+    model_train = model_train.half()
+elif os.environ['RWKV_FLOAT_MODE'] == 'bf16':
+    model_train = model_train.bfloat16()
+
+args.MODEL_NAME = MODEL_NAME
+args.RUN_DEVICE = RUN_DEVICE
+args.FLOAT_MODE = os.environ['RWKV_FLOAT_MODE']
+model_rnn = RWKV_RNN(args)
+
+########################################################################################################
+
+print(f"\nVerifying {os.environ['RWKV_RUN_DEVICE']} {os.environ['RWKV_FLOAT_MODE']}")
+
+# context = '\nIn a'
+context = '\nIn a shocking finding, scientist discovered a herd of dragons living in a remote, previously unexplored valley, in Tibet. Even more surprising to the researchers was the fact that the dragons spoke perfect Chinese.'
+
+if TOKEN_MODE == 'pile':
+    ctx = tokenizer.tokenizer.encode(context)
+print(f'input len {len(ctx)} data {ctx}')
+
+########################################################################################################
+
+with torch.no_grad():
+    print('\nRWKV-train output')
+    out = model_train.forward(torch.tensor([ctx]).to(RUN_DEVICE))[0].detach().cpu().float().numpy()
+    print(out, '\n')
+
+    print('\nRWKV-RNN output')
+    state = None
+    out = None
+    src_len = len(ctx)
+    for i in range(src_len):
+        x = ctx[:i+1]
+        out, state = model_rnn.forward(x, state)
+        if i < 3 or i >= src_len - 3:
+            print(out.detach().cpu().numpy())
+        if i == 2:
+            print('...')