prepare mypy==1.13.0: legacy cast (#7866)

* use helper to narrow literal type

* narrow with asserts instead of cast

* remove parantheses

* tensor.item() calls tensor.data()

* no copy

* proper indexing

tinygrad/dtype.py

@@ -1,11 +1,13 @@
 from __future__ import annotations
-from typing import Final, Optional, ClassVar, Set, Tuple, Dict, Union, Callable
+from typing import Final, Optional, ClassVar, Set, Tuple, Dict, Union, Callable, Literal
 import math, struct, ctypes, functools
 from dataclasses import dataclass, fields
 from tinygrad.helpers import getenv
 
 ConstType = Union[float, int, bool]
 
+FmtStr = Literal['?', 'b', 'B', 'h', 'H', 'i', 'I', 'q', 'Q', 'e', 'f', 'd']
+
 # all DTypes should only be created once
 class DTypeMetaClass(type):
   dcache: Dict[Tuple, DType] = {}
@@ -19,11 +21,11 @@ class DType(metaclass=DTypeMetaClass):
   priority: int  # this determines when things get upcasted
   itemsize: int
   name: str
-  fmt: Optional[str]
+  fmt: Optional[FmtStr]
   count: int
   _scalar: Optional[DType]
   @staticmethod
-  def new(priority:int, itemsize:int, name:str, fmt:Optional[str]): return DType(priority, itemsize, name, fmt, 1, None)
+  def new(priority:int, itemsize:int, name:str, fmt:Optional[FmtStr]): return DType(priority, itemsize, name, fmt, 1, None)
   def __reduce__(self): return type(self), tuple(getattr(self, f.name) for f in fields(self))
   def __repr__(self): return f"dtypes.{INVERSE_DTYPES_DICT[self.scalar().name]}"+(f".vec({self.count})" if self.count > 1 else "")
   def __lt__(self, o:DType): return (self.priority, self.itemsize, self.name, self.fmt, self.count) < (o.priority, o.itemsize, o.name, o.fmt, o.count)

tinygrad/runtime/ops_python.py

@@ -2,7 +2,8 @@
 # a python uops emulator
 # works to test the tensor cores, and all the uops in general
 # this is the (living) definition of uops
-from typing import Tuple, List, Optional, Any, Dict
+import sys
+from typing import Tuple, List, Optional, Any, Dict, TYPE_CHECKING
 import pickle, base64, itertools, time, struct
 from tinygrad.dtype import DType, dtypes, ImageDType, PtrDType, truncate
 from tinygrad.helpers import all_same, getenv, flatten
@@ -66,13 +67,11 @@ class PythonProgram:
           continue
         assert dtype is not None, f"{uop} is missing a dtype"
         dl[i] = dtype
-        if uop is Ops.DEFINE_GLOBAL:
+        if uop in {Ops.DEFINE_GLOBAL, Ops.DEFINE_LOCAL}:
           assert dtype.fmt is not None
-          ul[i] = [pbufs.pop(0).cast(dtype.fmt)] * warp_size
-        elif uop is Ops.DEFINE_LOCAL:
-          assert dtype.fmt is not None
-          lbuf = memoryview(bytearray(arg[1]*dtype.itemsize))
-          ul[i] = [lbuf.cast(dtype.fmt)] * warp_size
+          if TYPE_CHECKING or sys.version_info < (3, 12): assert dtype.fmt != "e"
+          buf = memoryview(bytearray(arg[1]*dtype.itemsize)) if uop is Ops.DEFINE_LOCAL else pbufs.pop(0)
+          ul[i] = [buf.cast(dtype.fmt)] * warp_size
         elif uop is Ops.DEFINE_VAR:
           ul[i] = [pvals.pop(0)] * warp_size
         elif uop is Ops.SPECIAL:

tinygrad/tensor.py

@@ -2,7 +2,7 @@
 from __future__ import annotations
 import time, math, itertools, functools, struct, sys, inspect, pathlib, string, dataclasses, hashlib
 from contextlib import ContextDecorator
-from typing import List, Tuple, Callable, Optional, ClassVar, Type, Union, Sequence, Dict, DefaultDict, cast, get_args, Literal
+from typing import List, Tuple, Callable, Optional, ClassVar, Type, Union, Sequence, Dict, DefaultDict, cast, get_args, Literal, TYPE_CHECKING
 from collections import defaultdict
 
 from tinygrad.dtype import DType, DTypeLike, dtypes, ImageDType, ConstType, least_upper_float, least_upper_dtype, sum_acc_dtype, to_dtype, truncate
@@ -273,6 +273,7 @@ class Tensor(SimpleMathTrait):
     """
     assert self.dtype.fmt is not None, f"no fmt dtype for {self.dtype}"
     assert all_int(self.shape), f"no data if shape is symbolic, {self.shape=}"
+    if TYPE_CHECKING or sys.version_info < (3, 12): assert self.dtype.fmt != "e"
     return self._data().cast(self.dtype.fmt) if 0 in self.shape else self._data().cast(self.dtype.fmt, self.shape)
 
   def item(self) -> ConstType:
@@ -284,9 +285,8 @@ class Tensor(SimpleMathTrait):
     print(t.item())
     ```
     """
-    assert self.dtype.fmt is not None, f"no fmt dtype for {self.dtype}"
     assert self.numel() == 1, "must have one element for item"
-    return self._data().cast(self.dtype.fmt)[0]
+    return self.data()[(0,) * len(self.shape)]
 
   # TODO: should be Tensor.tolist() -> Union[List[ConstType], ConstType]. The List is Sequence because mypy expects memoryview.tolist() -> list[int]
   # src: https://github.com/python/mypy/blob/release-1.6/mypy/typeshed/stdlib/builtins.pyi#L803