lowerer is kernel [run_process_replay] (#5437)

extra/optimization/extract_policynet.py

@@ -7,7 +7,7 @@ from tinygrad.nn.optim import Adam
 from tinygrad.nn.state import get_parameters, get_state_dict, safe_save, safe_load, load_state_dict
 from tinygrad.engine.search import actions
 from extra.optimization.helpers import load_worlds, ast_str_to_lin, lin_to_feats, assert_same_lin
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tinygrad.helpers import getenv
 
 # stuff needed to unpack a kernel
@@ -38,7 +38,7 @@ def dataset_from_cache(fn):
   for f in tqdm(cur.fetchall()):
     Xs,As = [], []
     try:
-      lin = Lowerer(eval(f[0]))
+      lin = Kernel(eval(f[0]))
       opts = pickle.loads(f[-1])
       for o in opts:
         Xs.append(lin_to_feats(lin, use_sts=True))

extra/optimization/extract_sa_pairs.py

@@ -13,7 +13,7 @@ inf, nan = float('inf'), float('nan')
 from tinygrad.codegen.kernel import Opt, OptOps
 
 # more stuff
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tinygrad.engine.search import actions
 from extra.optimization.helpers import lin_to_feats
 from extra.optimization.pretrain_valuenet import ValueNet
@@ -48,7 +48,7 @@ def dataset_from_cache(fn):
     new_tm = min(opts_to_outcome[(ast,k)])
     if math.isinf(old_tm) or math.isinf(new_tm) or old_tm < 1e-9 or new_tm < 1e-9: continue
     try:
-      lin = Lowerer(eval(ast))
+      lin = Kernel(eval(ast))
     except Exception:
       continue
     for opt in k[:-1]: lin.apply_opt(opt)

extra/optimization/get_action_space.py

@@ -1,12 +1,12 @@
 import random
 from extra.optimization.helpers import load_worlds, ast_str_to_lin
 from tinygrad.engine.search import actions
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tinygrad.helpers import tqdm
 
 tactions = set()
 def test_rebuild(lin):
-  linr = Lowerer(lin.ast)
+  linr = Kernel(lin.ast)
   for o in lin.applied_opts:
     assert o in actions, f"{o} is not in actions"
     tactions.add(o)

extra/optimization/helpers.py

@@ -9,12 +9,12 @@ from tinygrad.shape.symbolic import Variable, NumNode
 inf, nan = float('inf'), float('nan')
 
 # kernel unpacker
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 def ast_str_to_ast(ast_str:str) -> Tuple[LazyOp,...]: return LazyOp(MetaOps.SINK, val) if isinstance(val:=eval(ast_str), tuple) else val
-def ast_str_to_lin(ast_str:str, opts=None): return Lowerer(ast_str_to_ast(ast_str), opts=opts)
+def ast_str_to_lin(ast_str:str, opts=None): return Kernel(ast_str_to_ast(ast_str), opts=opts)
 def kern_str_to_lin(kern_str:str, opts=None):
   (ast, applied_opts,) = eval(kern_str)
-  k = Lowerer(ast, opts=opts)
+  k = Kernel(ast, opts=opts)
   for opt in applied_opts:
     k.apply_opt(opt)
   return k
@@ -44,7 +44,7 @@ from tinygrad.shape.symbolic import Node
 
 MAX_DIMS = 16
 MAX_BUFS = 9
-def lin_to_feats(lin:Lowerer, use_sts=True):
+def lin_to_feats(lin:Kernel, use_sts=True):
   assert lin.shape_len < MAX_DIMS, "too many dims"
 
   all_colors = ["blue", "cyan", "white", "green", "red", "magenta", "yellow"]

extra/optimization/pretrain_valuenet.py

@@ -1,4 +1,4 @@
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tqdm import tqdm, trange
 import math
 import random
@@ -45,7 +45,7 @@ if __name__ == "__main__":
   X,Y = [], []
   for i,x in enumerate(tqdm(dset)):
     ast, opts, tms = eval(x)
-    lin = Lowerer(ast)
+    lin = Kernel(ast)
     for o in opts: lin.apply_opt(o)
     if lin.shape_len >= MAX_DIMS: continue
     if min(tms) == float('inf'): continue

extra/optimization/run_qnet.py

@@ -1,9 +1,9 @@
 from typing import List, Tuple
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tinygrad.engine.search import get_linearizer_actions, actions
 
 _net = None
-def beam_q_estimate(beam:List[Tuple[Lowerer, float]]) -> List[Tuple[Lowerer, float]]:
+def beam_q_estimate(beam:List[Tuple[Kernel, float]]) -> List[Tuple[Kernel, float]]:
   global _net
   if _net is None:
     from tinygrad.nn.state import load_state_dict, safe_load

extra/optimization/search.py

@@ -4,7 +4,7 @@ from extra.optimization.helpers import ast_str_to_lin
 from tinygrad import dtypes
 from tinygrad.helpers import BEAM, getenv
 from tinygrad.device import Device, Compiled
-from tinygrad.codegen.lowerer import Lowerer
+from tinygrad.codegen.kernel import Kernel
 from tinygrad.engine.search import time_linearizer, beam_search, bufs_from_lin