add tinygrad, or at least the straightforward part

einops/_backends.py

@@ -660,3 +660,55 @@ def einsum(self, pattern, *x):
 
     def shape(self, x):
         return tuple(x.shape)
+
+class TinygradBackend(AbstractBackend):
+    framework_name = "tinygrad"
+
+    def __init__(self):
+        import tinygrad
+
+        self.tinygrad = tinygrad
+
+    def is_appropriate_type(self, tensor):
+        return isinstance(tensor, self.tinygrad.Tensor)
+
+    def from_numpy(self, x):
+        return self.tinygrad.Tensor(x)
+
+    def to_numpy(self, x):
+        return x.numpy()
+
+    def arange(self, start, stop):
+        return self.tinygrad.Tensor.arange(start, stop)
+
+    def shape(self, x):
+        return x.shape
+
+    def reshape(self, x, shape):
+        return x.reshape(shape)
+
+    def transpose(self, x, axes):
+        return x.permute(axes)
+
+    def reduce(self, x, operation, axes):
+        for axis in sorted(axes, reverse=True):
+            x = getattr(x, operation)(axis=axis)
+        return x
+
+    def stack_on_zeroth_dimension(self, tensors: list):
+        return self.tinygrad.stack(tensors)
+
+    def add_axis(self, x, new_position):
+        return x.unsqueeze(new_position)
+
+    def tile(self, x, repeats):
+        return x.repeat(repeats)
+
+    def concat(self, tensors, axis: int):
+        return tensors[0].cat(tensors[1:], axis) if len(tensors) > 1 else tensors[0]
+
+    def is_float_type(self, x):
+        return self.dtypes.is_float(x.dtype)
+
+    def __repr__(self):
+        return "<einops backend for {}>".format(self.framework_name)