jax.Array: support fast path for lax.transpose & lax.squeeze

As part of this change, I created a helper function so that the logic of type checking is
in a single location. Eventually we can replace this helper function with appropriate
isinstance() checks using the APIs described in jax-ml#11859.

jax/_src/lax/lax.py

@@ -85,6 +85,14 @@
 map, unsafe_map = safe_map, map
 zip, unsafe_zip = safe_zip, zip
 
+# TODO(jakevdp): replace this with an isinstance() check when JEP 12049 is complete.
+def _is_array_or_tracer(operand: Any) -> bool:
+  if config.jax_array:
+    from jax.experimental import array  # pylint: disable=g-import-not-at-top
+    return isinstance(operand, (core.Tracer, array.Array))
+  else:
+    return isinstance(operand, (core.Tracer, device_array.DeviceArray))
+
 def _validate_shapes(shapes: Sequence[Shape]):
   def _check_static_shape(shape: Shape):
     checked = canonicalize_shape(shape)
@@ -548,8 +556,6 @@ def convert_element_type(operand: Array, new_dtype: DType) -> Array:
 
 def _convert_element_type(operand: Array, new_dtype: Optional[DType] = None,
                           weak_type: bool = False):
-  from jax.experimental import array
-
   # Don't canonicalize old_dtype because x64 context might cause
   # un-canonicalized operands to be passed in.
   old_dtype = dtypes.dtype(operand, canonicalize=False)
@@ -576,8 +582,7 @@ def _convert_element_type(operand: Array, new_dtype: Optional[DType] = None,
     operand = np.asarray(operand, new_dtype)
     old_weak_type = False
 
-  if ((old_dtype, old_weak_type) == (new_dtype, new_weak_type)
-      and isinstance(operand, (core.Tracer, device_array.DeviceArray, array.Array))):
+  if (old_dtype, old_weak_type) == (new_dtype, new_weak_type) and _is_array_or_tracer(operand):
     return operand
   else:
     return convert_element_type_p.bind(operand, new_dtype=new_dtype,
@@ -628,13 +633,11 @@ def concatenate(operands: Sequence[Array], dimension: int) -> Array:
   Returns:
     An array containing the concatenation.
   """
-  from jax.experimental import array
-
   if len(operands) == 0:
     raise ValueError("concatenate requires a non-empty sequences of arrays")
   if len(operands) == 1:
     op, = operands
-    if isinstance(op, (core.Tracer, device_array.DeviceArray, array.Array)):
+    if _is_array_or_tracer(op):
       return op
   return concatenate_p.bind(*operands, dimension=dimension)
 
@@ -802,10 +805,7 @@ def broadcast_in_dim(operand: Array, shape: Shape,
   See Also:
     jax.lax.broadcast : simpler interface to add new leading dimensions.
   """
-  from jax.experimental import array
-
-  if (np.ndim(operand) == len(shape) and not len(broadcast_dimensions)
-      and isinstance(operand, (device_array.DeviceArray, core.Tracer, array.Array))):
+  if np.ndim(operand) == len(shape) and not len(broadcast_dimensions) and _is_array_or_tracer(operand):
     return operand
   if config.jax_dynamic_shapes:
     # We must gate this behavior under a flag because otherwise the errors
@@ -860,8 +860,6 @@ def reshape(operand: Array, new_sizes: Shape,
     >>> reshape(y, (6,), (1, 0))
     DeviceArray([0, 3, 1, 4, 2, 5], dtype=int32)
   """
-  from jax.experimental import array
-
   new_sizes = canonicalize_shape(new_sizes)  # TODO
   new_sizes = tuple(new_sizes)
   same_shape = core.symbolic_equal_shape(np.shape(operand), new_sizes)
@@ -871,8 +869,7 @@ def reshape(operand: Array, new_sizes: Shape,
   else:
     dims = api_util._ensure_index_tuple(dimensions)
     same_dims = tuple(dims) == tuple(range(np.ndim(operand)))
-  if (np.shape(operand) and same_shape and same_dims
-      and isinstance(operand, (core.Tracer, device_array.DeviceArray, array.Array))):
+  if np.shape(operand) and same_shape and same_dims and _is_array_or_tracer(operand):
     return operand
   else:
     dyn_shape, static_new_sizes = _extract_tracers_dyn_shape(new_sizes)
@@ -951,8 +948,7 @@ def transpose(operand: Array, permutation: Sequence[int]) -> Array:
   operator.
   """
   permutation = tuple(operator.index(d) for d in permutation)
-  if (permutation == tuple(range(np.ndim(operand)))
-      and isinstance(operand, (core.Tracer, device_array.DeviceArray))):
+  if permutation == tuple(range(np.ndim(operand))) and _is_array_or_tracer(operand):
     return operand
   else:
     return transpose_p.bind(operand, permutation=permutation)
@@ -1282,7 +1278,7 @@ def squeeze(array: Array, dimensions: Sequence[int]) -> Array:
   """Squeeze any number of size 1 dimensions from an array."""
   ndim = np.ndim(array)
   dimensions = tuple(sorted(canonicalize_axis(i, ndim) for i in dimensions))
-  if not dimensions and isinstance(array, (core.Tracer, device_array.DeviceArray)):
+  if not dimensions and _is_array_or_tracer(array):
     return array
   return squeeze_p.bind(array, dimensions=dimensions)