Refactor P2P rechunk validation (#7890)

distributed/shuffle/_rechunk.py

@@ -1,8 +1,7 @@
 from __future__ import annotations
 
-import math
 from collections import defaultdict
-from itertools import compress, product
+from itertools import product
 from typing import TYPE_CHECKING, NamedTuple
 
 import dask
@@ -73,34 +72,6 @@ def rechunk_p2p(x: da.Array, chunks: ChunkedAxes) -> da.Array:
         # Special case for empty array, as the algorithm below does not behave correctly
         return da.empty(x.shape, chunks=chunks, dtype=x.dtype)
 
-    old_chunks = x.chunks
-    new_chunks = chunks
-
-    def is_unknown(dim: ChunkedAxis) -> bool:
-        return any(math.isnan(chunk) for chunk in dim)
-
-    old_is_unknown = [is_unknown(dim) for dim in old_chunks]
-    new_is_unknown = [is_unknown(dim) for dim in new_chunks]
-
-    if old_is_unknown != new_is_unknown or any(
-        new != old for new, old in compress(zip(old_chunks, new_chunks), old_is_unknown)
-    ):
-        raise ValueError(
-            "Chunks must be unchanging along dimensions with missing values.\n\n"
-            "A possible solution:\n  x.compute_chunk_sizes()"
-        )
-
-    old_known = [dim for dim, unknown in zip(old_chunks, old_is_unknown) if not unknown]
-    new_known = [dim for dim, unknown in zip(new_chunks, new_is_unknown) if not unknown]
-
-    old_sizes = [sum(o) for o in old_known]
-    new_sizes = [sum(n) for n in new_known]
-
-    if old_sizes != new_sizes:
-        raise ValueError(
-            f"Cannot change dimensions from {old_sizes!r} to {new_sizes!r}"
-        )
-
     dsk: dict = {}
     token = tokenize(x, chunks)
     _barrier_key = barrier_key(ShuffleId(token))

distributed/shuffle/_worker_extension.py

@@ -314,14 +314,6 @@ def __init__(
             memory_limiter_comms=memory_limiter_comms,
             memory_limiter_disk=memory_limiter_disk,
         )
-        from dask.array.core import normalize_chunks
-
-        # We rely on a canonical `np.nan` in `dask.array.rechunk.old_to_new`
-        # that passes an implicit identity check when testing for list equality.
-        # This does not work with (de)serialization, so we have to normalize the chunks
-        # here again to canonicalize `nan`s.
-        old = normalize_chunks(old)
-        new = normalize_chunks(new)
         self.old = old
         self.new = new
         partitions_of = defaultdict(list)