bmerry: I wasn't sure if the return value should include the class of the literal object, so that `tokenize(literal(x))` and `tokenize(x)` would be different. I'm assuming that if both are used then they're intended to mean the same thing, so I haven't.
diff --git a/dask/array/blockwise.py b/dask/array/blockwise.py
index 240baa35a..6c30e36e7 100644
--- a/dask/array/blockwise.py
+++ b/dask/array/blockwise.py
@@ -145,11 +145,15 @@ def blockwise(
         chunkss, arrays = unify_chunks(*args)
     else:
         arginds = [(a, i) for (a, i) in toolz.partition(2, args) if i is not None]
-        if arginds:
-            arg, ind = max(arginds, key=lambda ai: len(ai[1]))
-            chunkss = dict(zip(ind, arg.chunks))
-        else:
-            chunkss = {}
+        chunkss = {}
+        # For each dimension, use the input chunking that has the most blocks;
+        # this will ensure that broadcasting works as expected, and in
+        # particular the number of blocks should be correct if the inputs are
+        # consistent.
+        for arg, ind in arginds:
+            for c, i in zip(arg.chunks, ind):
+                if i not in chunkss or len(c) > len(chunkss[i]):
+                    chunkss[i] = c
         arrays = args[::2]
 
     for k, v in new_axes.items():
@@ -220,6 +224,14 @@ def blockwise(
                 elif isinstance(adjust_chunks[ind], numbers.Integral):
                     chunks[i] = tuple(adjust_chunks[ind] for _ in chunks[i])
                 elif isinstance(adjust_chunks[ind], (tuple, list)):
+                    if len(adjust_chunks[ind]) != len(chunks[i]):
+                        raise ValueError(
+                            "Dimension {0} has {1} blocks, "
+                            "adjust_chunks specified with "
+                            "{2} blocks".format(
+                                i, len(chunks[i]), len(adjust_chunks[ind])
+                            )
+                        )
                     chunks[i] = tuple(adjust_chunks[ind])
                 else:
                     raise NotImplementedError(
diff --git a/dask/array/chunk.py b/dask/array/chunk.py
index a34e1b555..d9e182c2b 100644
--- a/dask/array/chunk.py
+++ b/dask/array/chunk.py
@@ -86,7 +86,7 @@ with ignoring(AttributeError):
     nanstd = np.nanstd
 
 
-def coarsen(reduction, x, axes, trim_excess=False):
+def coarsen(reduction, x, axes, trim_excess=False, **kwargs):
     """ Coarsen array by applying reduction to fixed size neighborhoods
 
     Parameters
@@ -140,7 +140,7 @@ def coarsen(reduction, x, axes, trim_excess=False):
     # (10, 10) -> (5, 2, 5, 2)
     newshape = tuple(concat([(x.shape[i] // axes[i], axes[i]) for i in range(x.ndim)]))
 
-    return reduction(x.reshape(newshape), axis=tuple(range(1, x.ndim * 2, 2)))
+    return reduction(x.reshape(newshape), axis=tuple(range(1, x.ndim * 2, 2)), **kwargs)
 
 
 def trim(x, axes=None):
diff --git a/dask/array/core.py b/dask/array/core.py
index 84fcbf620..ff59dedef 100644
--- a/dask/array/core.py
+++ b/dask/array/core.py
@@ -612,6 +612,17 @@ def map_blocks(
         out_ind = tuple(out_ind)
         if max(new_axis) > max(out_ind):
             raise ValueError("New_axis values do not fill in all dimensions")
+
+    if chunks is not None:
+        if len(chunks) != len(out_ind):
+            raise ValueError(
+                "Provided chunks have {0} dims, expected {1} "
+                "dims.".format(len(chunks), len(out_ind))
+            )
+        adjust_chunks = dict(zip(out_ind, chunks))
+    else:
+        adjust_chunks = None
+
     out = blockwise(
         func,
         out_ind,
@@ -621,6 +632,7 @@ def map_blocks(
         dtype=dtype,
         concatenate=True,
         align_arrays=False,
+        adjust_chunks=adjust_chunks,
         meta=meta,
         **kwargs,
     )
@@ -639,30 +651,6 @@ def map_blocks(
             v.dsk[key] = task
             dsk[k] = (v,) + vv[1:]
 
-    if chunks is not None:
-        if len(chunks) != len(out.numblocks):
-            raise ValueError(
-                "Provided chunks have {0} dims, expected {1} "
-                "dims.".format(len(chunks), len(out.numblocks))
-            )
-        chunks2 = []
-        for i, (c, nb) in enumerate(zip(chunks, out.numblocks)):
-            if isinstance(c, tuple):
-                # We only check cases where numblocks > 1. Because of
-                # broadcasting, we can't (easily) validate the chunks
-                # when the number of blocks is 1.
-                # See https://github.com/dask/dask/issues/4299 for more.
-                if nb > 1 and len(c) != nb:
-                    raise ValueError(
-                        "Dimension {0} has {1} blocks, "
-                        "chunks specified with "
-                        "{2} blocks".format(i, nb, len(c))
-                    )
-                chunks2.append(c)
-            else:
-                chunks2.append(nb * (c,))
-        out._chunks = normalize_chunks(chunks2)
-
     # If func has block_info as an argument, add it to the kwargs for each call
     if has_keyword(func, "block_info"):
         starts = {}
diff --git a/dask/array/routines.py b/dask/array/routines.py
index 182322658..03ea568df 100644
--- a/dask/array/routines.py
+++ b/dask/array/routines.py
@@ -9,6 +9,7 @@ from distutils.version import LooseVersion
 import numpy as np
 from toolz import concat, sliding_window, interleave
 
+from ..compatibility import apply
 from ..core import flatten
 from ..base import tokenize
 from ..highlevelgraph import HighLevelGraph
@@ -1292,7 +1293,7 @@ def piecewise(x, condlist, funclist, *args, **kw):
 
 
 @wraps(chunk.coarsen)
-def coarsen(reduction, x, axes, trim_excess=False):
+def coarsen(reduction, x, axes, trim_excess=False, **kwargs):
     if not trim_excess and not all(
         bd % div == 0 for i, div in axes.items() for bd in x.chunks[i]
     ):
@@ -1304,16 +1305,17 @@ def coarsen(reduction, x, axes, trim_excess=False):
 
     name = "coarsen-" + tokenize(reduction, x, axes, trim_excess)
     dsk = {
-        (name,) + key[1:]: (chunk.coarsen, reduction, key, axes, trim_excess)
+        (name,)
+        + key[1:]: (apply, chunk.coarsen, [reduction, key, axes, trim_excess], kwargs)
         for key in flatten(x.__dask_keys__())
     }
     chunks = tuple(
         tuple(int(bd // axes.get(i, 1)) for bd in bds) for i, bds in enumerate(x.chunks)
     )
 
-    dt = reduction(np.empty((1,) * x.ndim, dtype=x.dtype)).dtype
+    meta = reduction(np.empty((1,) * x.ndim, dtype=x.dtype), **kwargs)
     graph = HighLevelGraph.from_collections(name, dsk, dependencies=[x])
-    return Array(graph, name, chunks, dtype=dt)
+    return Array(graph, name, chunks, meta=meta)
 
 
 def split_at_breaks(array, breaks, axis=0):
diff --git a/dask/base.py b/dask/base.py
index b7c96f728..1612b8408 100644
--- a/dask/base.py
+++ b/dask/base.py
@@ -15,7 +15,7 @@ from toolz.functoolz import Compose
 
 from .compatibility import is_dataclass, dataclass_fields
 from .context import thread_state
-from .core import flatten, quote, get as simple_get
+from .core import flatten, quote, get as simple_get, literal
 from .hashing import hash_buffer_hex
 from .utils import Dispatch, ensure_dict, apply
 from . import config, local, threaded
@@ -678,6 +678,11 @@ def normalize_seq(seq):
     return type(seq).__name__, list(map(normalize_token, seq))
 
 
+@normalize_token.register(literal)
+def normalize_literal(lit):
+    return "literal", normalize_token(lit())
+
+
 @normalize_token.register(object)
 def normalize_object(o):
     method = getattr(o, "__dask_tokenize__", None)
diff --git a/dask/blockwise.py b/dask/blockwise.py
index 5fc7cf5d6..28d575a4f 100644
--- a/dask/blockwise.py
+++ b/dask/blockwise.py
@@ -581,6 +581,10 @@ def rewrite_blockwise(inputs):
     --------
     optimize_blockwise
     """
+    if len(inputs) == 1:
+        # Fast path: if there's only one input we can just use it as-is.
+        return inputs[0]
+
     inputs = {inp.output: inp for inp in inputs}
     dependencies = {
         inp.output: {d for d, v in inp.indices if v is not None and d in inputs}
diff --git a/dask/dataframe/core.py b/dask/dataframe/core.py
index 57989c866..53298c698 100644
--- a/dask/dataframe/core.py
+++ b/dask/dataframe/core.py
@@ -1645,7 +1645,7 @@ Dask Name: {name}, {task} tasks"""
             # Need the astype(int) for empty dataframes, which sum to float dtype
             result = self.reduction(
                 M.count,
-                aggregate=lambda x: x.sum().astype("int64"),
+                aggregate=_count_aggregate,
                 meta=meta,
                 token=token,
                 split_every=split_every,
@@ -5928,6 +5928,10 @@ def idxmaxmin_agg(x, fn=None, skipna=True, scalar=False):
     return res
 
 
+def _count_aggregate(x):
+    return x.sum().astype("int64")
+
+
 def safe_head(df, n):
     r = M.head(df, n)
     if len(r) != n:
diff --git a/dask/highlevelgraph.py b/dask/highlevelgraph.py
index 8c16b8326..1a9ce204f 100644
--- a/dask/highlevelgraph.py
+++ b/dask/highlevelgraph.py
@@ -131,7 +131,10 @@ class HighLevelGraph(Mapping):
                     with ignoring(AttributeError):
                         deps[name] |= set(collection.__dask_layers__())
                 else:
-                    key = id(graph)
+                    try:
+                        [key] = collection.__dask_layers__()
+                    except AttributeError:
+                        key = id(graph)
                     layers[key] = graph
                     deps[name].add(key)
                     deps[key] = set()

normalize_token pickles data of literal
While investigating a slow call to `tokenize` I discovered that when a `literal` is passed to a function that tokenizes args, it ends up pickling the quoted data instead of recursively normalising it. This is because there is no normalizer registered for `literal`, so it goes down the generic path for callables, which uses pickle.

Example:
```python
from dask.base import normalize_token
from dask.core import literal

d = {'a': [1, 2], 'b': [3]}
print(normalize_token(d))
print(normalize_token(literal(d)))
```

Output:
```
('list', [('tuple', ['a', ('list', [1, 2])]), ('tuple', ['b', ('list', [3])])])
b'cdask.core\nliteral\np0\n((dp1\nVa\np2\n(lp3\nL1L\naL2L\nasVb\np4\n(lp5\nL3L\nastp6\nRp7\n.'
```

This is on current master.
diff --git a/dask/array/tests/test_array_core.py b/dask/array/tests/test_array_core.py
index 39b2607d1..9b861cd34 100644
--- a/dask/array/tests/test_array_core.py
+++ b/dask/array/tests/test_array_core.py
@@ -1370,6 +1370,14 @@ def test_map_blocks_with_kwargs():
     assert_eq(result, np.array([4, 9]))
 
 
+def test_map_blocks_infer_chunks_broadcast():
+    dx = da.from_array([[1, 2, 3, 4]], chunks=((1,), (2, 2)))
+    dy = da.from_array([[10, 20], [30, 40]], chunks=((1, 1), (2,)))
+    result = da.map_blocks(lambda x, y: x + y, dx, dy)
+    assert result.chunks == ((1, 1), (2, 2),)
+    assert_eq(result, np.array([[11, 22, 13, 24], [31, 42, 33, 44]]))
+
+
 def test_map_blocks_with_chunks():
     dx = da.ones((5, 3), chunks=(2, 2))
     dy = da.ones((5, 3), chunks=(2, 2))
@@ -2873,6 +2881,9 @@ def test_map_blocks_with_changed_dimension():
     with pytest.raises(ValueError):
         d.map_blocks(lambda b: b.sum(axis=0), chunks=((4, 4, 4),), drop_axis=0)
 
+    with pytest.raises(ValueError):
+        d.map_blocks(lambda b: b.sum(axis=1), chunks=((3, 4),), drop_axis=1)
+
     d = da.from_array(x, chunks=(4, 8))
     e = d.map_blocks(lambda b: b.sum(axis=1), drop_axis=1, dtype=d.dtype)
     assert e.chunks == ((4, 3),)
diff --git a/dask/array/tests/test_atop.py b/dask/array/tests/test_atop.py
index 1e22396d9..dbac96c26 100644
--- a/dask/array/tests/test_atop.py
+++ b/dask/array/tests/test_atop.py
@@ -587,3 +587,12 @@ def test_atop_legacy():
     z = da.blockwise(inc, "i", x, "i", dtype=x.dtype)
     assert_eq(y, z)
     assert y.name == z.name
+
+
+def test_non_hlg():
+    # Regression test for https://github.com/dask/dask/issues/5850
+    a = da.from_array(np.ones(1, np.float64), chunks=(1,))
+    a.dask = dict(a.dask)  # Convert from HighLevelGraph to plain dict
+    b = da.from_array(np.zeros(1, np.float64), chunks=(1,))
+    x = a + b
+    assert_eq(x, a)
diff --git a/dask/array/tests/test_routines.py b/dask/array/tests/test_routines.py
index 6e16e9d44..a716fabf2 100644
--- a/dask/array/tests/test_routines.py
+++ b/dask/array/tests/test_routines.py
@@ -1391,6 +1391,10 @@ def test_coarsen():
     assert_eq(
         da.chunk.coarsen(np.sum, x, {0: 2, 1: 4}), da.coarsen(da.sum, d, {0: 2, 1: 4})
     )
+    assert_eq(
+        da.chunk.coarsen(np.mean, x, {0: 2, 1: 4}, dtype="float32"),
+        da.coarsen(da.mean, d, {0: 2, 1: 4}, dtype="float32"),
+    )
 
 
 def test_coarsen_with_excess():
diff --git a/dask/tests/test_base.py b/dask/tests/test_base.py
index 7d06bb4d3..663a77846 100644
--- a/dask/tests/test_base.py
+++ b/dask/tests/test_base.py
@@ -25,6 +25,7 @@ from dask.base import (
     named_schedulers,
     get_scheduler,
 )
+from dask.core import literal
 from dask.delayed import Delayed
 from dask.utils import tmpdir, tmpfile, ignoring
 from dask.utils_test import inc, dec
@@ -406,6 +407,10 @@ def test_tokenize_base_types(x):
     assert tokenize(x) == tokenize(x), x
 
 
+def test_tokenize_literal():
+    assert tokenize(literal(["x", 1])) == tokenize(literal(["x", 1]))
+
+
 @pytest.mark.skipif("not np")
 @pytest.mark.filterwarnings("ignore:the matrix:PendingDeprecationWarning")
 def test_tokenize_numpy_matrix():

pip install -e .[complete]
parse_log_pytest
pytest
pytest
3.7
pytest --no-header -rA --tb=line --color=no -p no:cacheprovider -W ignore::DeprecationWarning
attrs @ file:///croot/attrs_1668696182826/work
bokeh==2.4.3
certifi @ file:///croot/certifi_1671487769961/work/certifi
click==8.1.8
cloudpickle==2.2.1
-e git+https://github.com/dask/dask.git@2fee6bbbc49ef62e563322e7e0de7346d8333875#egg=dask
distributed==2.30.1
flit_core @ file:///opt/conda/conda-bld/flit-core_1644941570762/work/source/flit_core
fsspec==2023.1.0
HeapDict==1.0.1
importlib-metadata @ file:///tmp/build/80754af9/importlib-metadata_1648562407465/work
iniconfig @ file:///home/linux1/recipes/ci/iniconfig_1610983019677/work
Jinja2==3.1.6
locket==1.0.0
MarkupSafe==2.1.5
msgpack==1.0.5
numpy==1.21.6
packaging @ file:///croot/packaging_1671697413597/work
pandas==1.3.5
partd==1.4.1
Pillow==9.5.0
pluggy @ file:///tmp/build/80754af9/pluggy_1648042572264/work
psutil==7.0.0
py @ file:///opt/conda/conda-bld/py_1644396412707/work
pytest==7.1.2
python-dateutil==2.9.0.post0
pytz==2025.2
PyYAML==6.0.1
six==1.17.0
sortedcontainers==2.4.0
tblib==2.0.0
tomli @ file:///opt/conda/conda-bld/tomli_1657175507142/work
toolz==0.12.1
tornado==6.2
typing_extensions @ file:///croot/typing_extensions_1669924550328/work
zict==2.2.0
zipp @ file:///croot/zipp_1672387121353/work

name: dask
channels:
  - defaults
  - https://repo.anaconda.com/pkgs/main
  - https://repo.anaconda.com/pkgs/r
  - conda-forge
dependencies:
  - _libgcc_mutex=0.1=main
  - _openmp_mutex=5.1=1_gnu
  - attrs=22.1.0=py37h06a4308_0
  - ca-certificates=2025.2.25=h06a4308_0
  - certifi=2022.12.7=py37h06a4308_0
  - flit-core=3.6.0=pyhd3eb1b0_0
  - importlib-metadata=4.11.3=py37h06a4308_0
  - importlib_metadata=4.11.3=hd3eb1b0_0
  - iniconfig=1.1.1=pyhd3eb1b0_0
  - ld_impl_linux-64=2.40=h12ee557_0
  - libffi=3.4.4=h6a678d5_1
  - libgcc-ng=11.2.0=h1234567_1
  - libgomp=11.2.0=h1234567_1
  - libstdcxx-ng=11.2.0=h1234567_1
  - ncurses=6.4=h6a678d5_0
  - openssl=1.1.1w=h7f8727e_0
  - packaging=22.0=py37h06a4308_0
  - pip=22.3.1=py37h06a4308_0
  - pluggy=1.0.0=py37h06a4308_1
  - py=1.11.0=pyhd3eb1b0_0
  - pytest=7.1.2=py37h06a4308_0
  - python=3.7.16=h7a1cb2a_0
  - readline=8.2=h5eee18b_0
  - setuptools=65.6.3=py37h06a4308_0
  - sqlite=3.45.3=h5eee18b_0
  - tk=8.6.14=h39e8969_0
  - tomli=2.0.1=py37h06a4308_0
  - typing_extensions=4.4.0=py37h06a4308_0
  - wheel=0.38.4=py37h06a4308_0
  - xz=5.6.4=h5eee18b_1
  - zipp=3.11.0=py37h06a4308_0
  - zlib=1.2.13=h5eee18b_1
  - pip:
      - bokeh==2.4.3
      - click==8.1.8
      - cloudpickle==2.2.1
      - distributed==2.30.1
      - fsspec==2023.1.0
      - heapdict==1.0.1
      - jinja2==3.1.6
      - locket==1.0.0
      - markupsafe==2.1.5
      - msgpack==1.0.5
      - numpy==1.21.6
      - pandas==1.3.5
      - partd==1.4.1
      - pillow==9.5.0
      - psutil==7.0.0
      - python-dateutil==2.9.0.post0
      - pytz==2025.2
      - pyyaml==6.0.1
      - six==1.17.0
      - sortedcontainers==2.4.0
      - tblib==2.0.0
      - toolz==0.12.1
      - tornado==6.2
      - zict==2.2.0
prefix: /opt/conda/envs/dask

dask/array/tests/test_array_core.py::test_map_blocks_infer_chunks_broadcast dask/array/tests/test_array_core.py::test_map_blocks_with_changed_dimension dask/array/tests/test_atop.py::test_non_hlg dask/array/tests/test_routines.py::test_coarsen
dask/array/tests/test_array_core.py::test_Array_numpy_gufunc_call__array_ufunc__01 dask/array/tests/test_array_core.py::test_Array_numpy_gufunc_call__array_ufunc__02 dask/array/tests/test_array_core.py::test_no_warnings_from_blockwise
dask/array/tests/test_array_core.py::test_getem dask/array/tests/test_array_core.py::test_top dask/array/tests/test_array_core.py::test_top_supports_broadcasting_rules dask/array/tests/test_array_core.py::test_top_literals dask/array/tests/test_array_core.py::test_blockwise_literals dask/array/tests/test_array_core.py::test_concatenate3_on_scalars dask/array/tests/test_array_core.py::test_chunked_dot_product dask/array/tests/test_array_core.py::test_chunked_transpose_plus_one dask/array/tests/test_array_core.py::test_broadcast_dimensions_works_with_singleton_dimensions dask/array/tests/test_array_core.py::test_broadcast_dimensions dask/array/tests/test_array_core.py::test_Array dask/array/tests/test_array_core.py::test_uneven_chunks dask/array/tests/test_array_core.py::test_numblocks_suppoorts_singleton_block_dims dask/array/tests/test_array_core.py::test_keys dask/array/tests/test_array_core.py::test_Array_computation dask/array/tests/test_array_core.py::test_stack 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dask/array/tests/test_array_core.py::test_compute_chunk_sizes_2d_array dask/array/tests/test_array_core.py::test_compute_chunk_sizes_3d_array dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_rechunk dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_to_svg dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_concatenate dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_reduction dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_reshape dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_slicing dask/array/tests/test_array_core.py::test_rechunk_auto dask/array/tests/test_atop.py::test_rewrite[inputs0-expected0] dask/array/tests/test_atop.py::test_rewrite[inputs1-expected1] dask/array/tests/test_atop.py::test_rewrite[inputs2-expected2] dask/array/tests/test_atop.py::test_rewrite[inputs3-expected3] dask/array/tests/test_atop.py::test_rewrite[inputs4-expected4] dask/array/tests/test_atop.py::test_rewrite[inputs5-expected5] dask/array/tests/test_atop.py::test_rewrite[inputs6-expected6] dask/array/tests/test_atop.py::test_rewrite[inputs7-expected7] dask/array/tests/test_atop.py::test_rewrite[inputs8-expected8] dask/array/tests/test_atop.py::test_rewrite[inputs9-expected9] dask/array/tests/test_atop.py::test_rewrite[inputs10-expected10] dask/array/tests/test_atop.py::test_rewrite[inputs11-expected11] dask/array/tests/test_atop.py::test_rewrite[inputs12-expected12] dask/array/tests/test_atop.py::test_rewrite[inputs13-expected13] dask/array/tests/test_atop.py::test_rewrite[inputs14-expected14] dask/array/tests/test_atop.py::test_rewrite[inputs15-expected15] dask/array/tests/test_atop.py::test_index_subs dask/array/tests/test_atop.py::test_optimize_blockwise dask/array/tests/test_atop.py::test_blockwise_diamond_fusion dask/array/tests/test_atop.py::test_blockwise_non_blockwise_output 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dask/array/tests/test_atop.py::test_validate_top_inputs dask/array/tests/test_atop.py::test_dont_merge_before_reductions dask/array/tests/test_atop.py::test_atop_legacy dask/array/tests/test_routines.py::test_array dask/array/tests/test_routines.py::test_array_return_type dask/array/tests/test_routines.py::test_derived_docstrings dask/array/tests/test_routines.py::test_atleast_nd_no_args[atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_no_args[atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_no_args[atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape0-chunks0-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape0-chunks0-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape0-chunks0-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape1-chunks1-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape1-chunks1-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape1-chunks1-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape2-chunks2-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape2-chunks2-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape2-chunks2-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape3-chunks3-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape3-chunks3-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape3-chunks3-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape4-chunks4-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape4-chunks4-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_one_arg[shape4-chunks4-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape10-shape20-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape10-shape20-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape10-shape20-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape11-shape21-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape11-shape21-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape11-shape21-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape12-shape22-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape12-shape22-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape12-shape22-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape13-shape23-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape13-shape23-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape13-shape23-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape14-shape24-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape14-shape24-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape14-shape24-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape15-shape25-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape15-shape25-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape15-shape25-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape16-shape26-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape16-shape26-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape16-shape26-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape17-shape27-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape17-shape27-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape17-shape27-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape18-shape28-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape18-shape28-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape18-shape28-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape19-shape29-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape19-shape29-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape19-shape29-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape110-shape210-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape110-shape210-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape110-shape210-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape111-shape211-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape111-shape211-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape111-shape211-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape112-shape212-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape112-shape212-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape112-shape212-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape113-shape213-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape113-shape213-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape113-shape213-atleast_3d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape114-shape214-atleast_1d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape114-shape214-atleast_2d] dask/array/tests/test_routines.py::test_atleast_nd_two_args[shape114-shape214-atleast_3d] 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dask/array/tests/test_routines.py::test_flip[shape2-flip-kwargs5] dask/array/tests/test_routines.py::test_flip[shape3-flipud-kwargs0] dask/array/tests/test_routines.py::test_flip[shape3-fliplr-kwargs1] dask/array/tests/test_routines.py::test_flip[shape3-flip-kwargs2] dask/array/tests/test_routines.py::test_flip[shape3-flip-kwargs3] dask/array/tests/test_routines.py::test_flip[shape3-flip-kwargs4] dask/array/tests/test_routines.py::test_flip[shape3-flip-kwargs5] dask/array/tests/test_routines.py::test_flip[shape4-flipud-kwargs0] dask/array/tests/test_routines.py::test_flip[shape4-fliplr-kwargs1] dask/array/tests/test_routines.py::test_flip[shape4-flip-kwargs2] dask/array/tests/test_routines.py::test_flip[shape4-flip-kwargs3] dask/array/tests/test_routines.py::test_flip[shape4-flip-kwargs4] dask/array/tests/test_routines.py::test_flip[shape4-flip-kwargs5] dask/array/tests/test_routines.py::test_matmul[x_shape0-y_shape0] dask/array/tests/test_routines.py::test_matmul[x_shape1-y_shape1] dask/array/tests/test_routines.py::test_matmul[x_shape2-y_shape2] dask/array/tests/test_routines.py::test_matmul[x_shape3-y_shape3] dask/array/tests/test_routines.py::test_matmul[x_shape4-y_shape4] dask/array/tests/test_routines.py::test_matmul[x_shape5-y_shape5] dask/array/tests/test_routines.py::test_matmul[x_shape6-y_shape6] dask/array/tests/test_routines.py::test_matmul[x_shape7-y_shape7] dask/array/tests/test_routines.py::test_matmul[x_shape8-y_shape8] dask/array/tests/test_routines.py::test_matmul[x_shape9-y_shape9] dask/array/tests/test_routines.py::test_matmul[x_shape10-y_shape10] dask/array/tests/test_routines.py::test_matmul[x_shape11-y_shape11] dask/array/tests/test_routines.py::test_matmul[x_shape12-y_shape12] dask/array/tests/test_routines.py::test_matmul[x_shape13-y_shape13] dask/array/tests/test_routines.py::test_matmul[x_shape14-y_shape14] dask/array/tests/test_routines.py::test_matmul[x_shape15-y_shape15] dask/array/tests/test_routines.py::test_matmul[x_shape16-y_shape16] dask/array/tests/test_routines.py::test_matmul[x_shape17-y_shape17] dask/array/tests/test_routines.py::test_matmul[x_shape18-y_shape18] dask/array/tests/test_routines.py::test_matmul[x_shape19-y_shape19] dask/array/tests/test_routines.py::test_matmul[x_shape20-y_shape20] dask/array/tests/test_routines.py::test_matmul[x_shape21-y_shape21] dask/array/tests/test_routines.py::test_matmul[x_shape22-y_shape22] dask/array/tests/test_routines.py::test_matmul[x_shape23-y_shape23] dask/array/tests/test_routines.py::test_matmul[x_shape24-y_shape24] dask/array/tests/test_routines.py::test_tensordot dask/array/tests/test_routines.py::test_tensordot_2[0] dask/array/tests/test_routines.py::test_tensordot_2[1] dask/array/tests/test_routines.py::test_tensordot_2[axes2] dask/array/tests/test_routines.py::test_tensordot_2[axes3] dask/array/tests/test_routines.py::test_tensordot_2[axes4] dask/array/tests/test_routines.py::test_tensordot_2[axes5] dask/array/tests/test_routines.py::test_tensordot_2[axes6] dask/array/tests/test_routines.py::test_tensordot_more_than_26_dims dask/array/tests/test_routines.py::test_dot_method dask/array/tests/test_routines.py::test_vdot[shape0-chunks0] dask/array/tests/test_routines.py::test_vdot[shape1-chunks1] dask/array/tests/test_routines.py::test_inner[shape10-shape20] dask/array/tests/test_routines.py::test_inner[shape11-shape21] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-ndim-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-sum-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-range-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-range2-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-cumsum-<lambda>-True] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-ndim-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-sum-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-range-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-range2-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-cumsum-<lambda>-True] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-ndim-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-sum-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-range-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-range2-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-cumsum-<lambda>-True] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-ndim-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-sum-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-range-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-range2-<lambda>-False] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-cumsum-<lambda>-True] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-sum0-<lambda>] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-sum1-<lambda>] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-range-<lambda>] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-sum0-<lambda>] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-sum1-<lambda>] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-range-<lambda>] 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dask/array/tests/test_routines.py::test_isin_rand[True-test_shape2-test_chunks2-elements_shape3-elements_chunks3-0-10-796] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape0-elements_chunks0-0-10-23] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape0-elements_chunks0-0-10-796] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape1-elements_chunks1-0-10-23] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape1-elements_chunks1-0-10-796] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape2-elements_chunks2-0-10-23] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape2-elements_chunks2-0-10-796] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape3-elements_chunks3-0-10-23] 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dask/tests/test_base.py::test_num_workers_config[processes]
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