simplify slicing jaxprs a little

Co-authored-by: Sharad Vikram <sharad.vikram@gmail.com>

benchmarks/api_benchmark.py

@@ -539,5 +539,13 @@ def bench_remat_eager_retracing_overheads_static_argnums(state):
   y.block_until_ready()
 
 
+@google_benchmark.register
+@google_benchmark.option.unit(google_benchmark.kMillisecond)
+def bench_slicing_compilation(state):
+  x = jnp.arange(3)
+  while state:
+    jax.jit(lambda x: (x[0], x[1], x[2])).lower(x).compile()
+
+
 if __name__ == "__main__":
   google_benchmark.main()

jax/_src/lax/slicing.py

@@ -50,6 +50,8 @@ Shape = core.Shape
 map, unsafe_map = safe_map, map
 zip, unsafe_zip = safe_zip, zip
 
+_dtype = partial(dtypes.dtype, canonicalize=True)
+
 
 def slice(operand: Array, start_indices: Sequence[int],
           limit_indices: Sequence[int],
@@ -263,7 +265,7 @@ def gather(operand: Array, start_indices: Array,
   parsed_mode = GatherScatterMode.from_any(mode)
   if parsed_mode == GatherScatterMode.FILL_OR_DROP:
     if fill_value is None:
-      dtype = lax._dtype(operand)
+      dtype = _dtype(operand)
       if dtypes.issubdtype(dtype, np.inexact):
         fill_value = np.nan
       elif dtypes.issubdtype(dtype, np.signedinteger):
@@ -2042,14 +2044,15 @@ def _dynamic_slice_indices(operand, start_indices: Any):
     if start_indices.ndim != 1:
       raise ValueError("Slice indices must be a 1D sequence, got {}"
                        .format(start_indices.shape))
-    start_indices = [i for i in start_indices]
-  return [np.asarray(i + d if i < 0 else i, lax._dtype(i))
-          if isinstance(i, (int, np.integer)) and core.is_constant_dim(d)
-          else lax.select(
-              lax.lt(i, lax._const(i, 0)),
-              lax.add(i, lax.convert_element_type(core.dimension_as_value(d), lax._dtype(i))),
-              i)
-          for i, d in zip(start_indices, operand.shape)]
+    start_indices = list(start_indices)
+  result = []
+  for i, d in zip(start_indices, operand.shape):
+    if isinstance(i, (int, np.integer)) and core.is_constant_dim(d):
+      result.append(lax.convert_element_type(i + d, _dtype(i)) if i < 0 else i)
+    else:
+      d = lax.convert_element_type(core.dimension_as_value(d), _dtype(i))
+      result.append(lax.select(i < 0, i + d, i))
+  return result
 
 
 # TODO(mattjj): getslice is a prototype for dynamic shapes, revise or remove it

jax/_src/numpy/lax_numpy.py

@@ -3485,10 +3485,10 @@ def _normalize_index(index, axis_size):
   else:
     axis_size_val = lax.convert_element_type(core.dimension_as_value(axis_size),
                                              _dtype(index))
-  return lax.select(
-    lax.lt(index, _lax_const(index, 0)),
-    lax.add(index, axis_size_val),
-    index)
+  if isinstance(index, (int, np.integer)):
+    return lax.add(index, axis_size_val) if index < 0 else index
+  else:
+    return lax.select(index < 0, lax.add(index, axis_size_val), index)
 
 
 TAKE_ALONG_AXIS_DOC = """