array-api-compat
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data-apis
TST: Redesign `test_all`
#288 introduced __dir__, which completely neutered test_all.
Instead of reverting the change, this PR attempts to reinvent the test to be more useful.
CC @jorenham @ev-br
I've heavily reworked the PR and fixed many issues where array-api-compat was hiding objects declared in the wrapped module. Output of the new test vs. the old array_api_compat is as follows:
FAILED tests/test_all.py::test_array_api_names[numpy-] - AssertionError: Missing exports: {'__array_api_version__', '__array_namespace_info__'}
FAILED tests/test_all.py::test_array_api_names[cupy-] - AssertionError: Missing exports: {'__array_api_version__', '__array_namespace_info__'}
FAILED tests/test_all.py::test_array_api_names[torch-] - AssertionError: Missing exports: {'__array_api_version__', '__array_namespace_info__'}
FAILED tests/test_all.py::test_array_api_names[dask.array-] - AssertionError: Missing exports: {'__array_api_version__', '__array_namespace_info__'}
FAILED tests/test_all.py::test_compat_doesnt_hide_names[numpy-] - AssertionError: Non-Array API names have been hidden: {'test', 'kernel_version', 'numarray', 'polynomial', 'compat', 'typing', 'testing', 'version', 'dtypes', 'l...
FAILED tests/test_all.py::test_compat_doesnt_hide_names[numpy-fft] - AssertionError: Non-Array API names have been hidden: {'test', 'helper'}
FAILED tests/test_all.py::test_compat_doesnt_hide_names[numpy-linalg] - AssertionError: Non-Array API names have been hidden: {'test', 'linalg'}
FAILED tests/test_all.py::test_compat_doesnt_hide_names[torch-] - AssertionError: Non-Array API names have been hidden: {'cpu', 'cuda'}
FAILED tests/test_all.py::test_compat_doesnt_hide_names[torch-fft] - AssertionError: Non-Array API names have been hidden: {'ihfftn', 'common_args', 'hfft2', 'factory_common_args', 'ihfft2', 'sys', 'hfftn'}
FAILED tests/test_all.py::test_compat_doesnt_hide_names[dask.array-] - AssertionError: Non-Array API names have been hidden: {'einsumfuncs', 'annotations', 'utils', 'optimization', 'chunk_types', 'warnings', 'wrap', 'reductions', 'r...
FAILED tests/test_all.py::test_compat_doesnt_add_names[numpy-] - AssertionError: array-api-compat is adding non-Array API names: {'is_pydata_sparse_namespace', 'is_numpy_array', 'is_ndonnx_namespace', 'is_cupy_namespace', 'is_...
FAILED tests/test_all.py::test_compat_doesnt_add_names[torch-fft] - AssertionError: array-api-compat is adding non-Array API names: {'annotations', 'Sequence', 'Union', 'Literal', 'Array'}
FAILED tests/test_all.py::test_compat_doesnt_add_names[dask.array-] - AssertionError: array-api-compat is adding non-Array API names: {'Final'}
FAILED tests/test_all.py::test_compat_doesnt_add_names[dask.array-fft] - AssertionError: array-api-compat is adding non-Array API names: {'get_xp', 'fft_all', 'da'}
FAILED tests/test_all.py::test_compat_doesnt_add_names[dask.array-linalg] - AssertionError: array-api-compat is adding non-Array API names: {'Literal', 'linalg_all', 'get_xp', 'da'}
Yes, thanks for the ping. My plan is to look at this and gh-321 right after 1.12 is out of the door (so that pytorch==2.7 is usable).
Sorry for the delay.
This PR seems to have some visible effects on which names are available from the wrapped namespaces. Are these intended?
On main
-------
In [13]: for bare_ns in [np, cp, da, torch]:
...: xp = array_namespace(bare_ns.arange(3))
...: bare_names = set(dir(bare_ns))
...: xp_names = set(dir(xp))
...: print(f"{xp.__name__}, {len(bare_names - xp_names)} {len(xp_names - bare_names)}")
...:
array_api_compat.numpy, 24 7
array_api_compat.cupy, 28 33
array_api_compat.dask.array, 2 37
array_api_compat.torch, 441 25
In [16]: for bare_ns in [np, cp, da, torch]:
...: xp = array_namespace(bare_ns.arange(3))
...: bare_names = set([x for x in dir(bare_ns) if not x.startswith("_")])
...: xp_names = set([x for x in dir(xp) if not x.startswith("_")])
...: print(f"{xp.__name__}, {len(bare_names - xp_names)} {len(xp_names - bare_names)}")
...:
array_api_compat.numpy, 0 4
array_api_compat.cupy, 0 28
array_api_compat.dask.array, 0 33
array_api_compat.torch, 2 20
On branch
---------
In [1]: import numpy as np
In [2]: import torch
import
In [3]: import cupy as cp
In [4]: import dask.array as da
In [5]: from array_api_compat import array_namespace
In [7]: for bare_ns in [np, cp, da, torch]:
...: xp = array_namespace(bare_ns.arange(3))
...: bare_names = set([x for x in dir(bare_ns) ])
...: xp_names = set([x for x in dir(xp) ])
...: print(f"{xp.__name__}, {len(bare_names - xp_names)} {len(xp_names - bare_names)}")
...:
array_api_compat.numpy, 33 3
array_api_compat.cupy, 37 30
array_api_compat.dask.array, 11 34
array_api_compat.torch, 447 22
In [6]: for bare_ns in [np, cp, da, torch]:
...: xp = array_namespace(bare_ns.arange(3))
...: bare_names = set([x for x in dir(bare_ns) if not x.startswith("_")])
...: xp_names = set([x for x in dir(xp) if not x.startswith("_")])
...: print(f"{xp.__name__}, {len(bare_names - xp_names)} {len(xp_names - bare_names)}")
...:
array_api_compat.numpy, 0 3
array_api_compat.cupy, 0 28
array_api_compat.dask.array, 0 32
array_api_compat.torch, 0 20
@ev-br this may be clearer. It shows that all changes in visibility are desirable:
import yaml
from array_api_compat import array_namespace
import numpy as np
import cupy as cp
import dask.array as da
import torch
out = {}
for bare_ns in [np, cp, da, torch]:
xp = array_namespace(bare_ns.arange(3))
bare_names = set(dir(bare_ns))
xp_names = set(dir(xp))
hides = sorted(bare_names - xp_names)
adds = sorted(xp_names - bare_names)
out[f"array-api-compat hides from {bare_ns.__name__}"] = sorted(bare_names - xp_names)
out[f"array-api-compat adds to {bare_ns.__name__}"] = sorted(xp_names - bare_names)
print(yaml.dump(out))
git checkout main
python dump.py > main.txt
git checkout test_all
python dump.py > test_all.txt
diff -c99999 main.txt test_all.txt
*** main.txt 2025-06-04 12:35:57.385160311 +0100
--- test_all.txt 2025-06-04 12:35:48.335020354 +0100
***************
*** 1,628 ****
array-api-compat adds to cupy:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- - _aliases
- - _info
- - _typing
- acos
- acosh
- asin
- asinh
- astype
- atan
- atan2
- atanh
- bitwise_invert
- bitwise_left_shift
- bitwise_right_shift
- bool
- concat
- cumulative_prod
- cumulative_sum
- isdtype
- matrix_transpose
- permute_dims
- pow
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat adds to dask.array:
- - Final
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- - _aliases
- - _info
- acos
- acosh
- argsort
- asin
- asinh
- astype
- atan
- atan2
- atanh
- bitwise_invert
- bitwise_left_shift
- bitwise_right_shift
- can_cast
- concat
- cumulative_prod
- cumulative_sum
- finfo
- iinfo
- isdtype
- matrix_transpose
- permute_dims
- pow
- sort
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat adds to numpy:
- - Final
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- - __annotations__
- - _aliases
- - _info
array-api-compat adds to torch:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- - _aliases
- - _info
- - _typing
- astype
- bitwise_invert
- broadcast_arrays
- cumulative_prod
- cumulative_sum
- expand_dims
- isdtype
- matrix_transpose
- permute_dims
- repeat
- take_along_axis
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat hides from cupy:
- __getattr__
- __version__
- _binary
- _core
- _creation
- _cupy
- _cupyx
- _default_memory_pool
- _default_pinned_memory_pool
- _deprecated_apis
- _embed_signatures
- _environment
- _functional
- _functools
- _indexing
- _io
- _logic
- _manipulation
- _math
- _misc
- _numpy
- _padding
- _sorting
- _statistics
- _sys
- _template
- _util
- _version
array-api-compat hides from dask.array:
- - ARRAY_EXPR_ENABLED
- __all__
- _array_expr_enabled
- _reductions_generic
- _shuffle
- - annotations
- - chunk
- - chunk_types
- - core
- - creation
- - dispatch
- - einsumfuncs
- - importlib
- - numpy_compat
- - optimization
- - reductions
- - routines
- - slicing
- - tiledb_io
- - ufunc
- - utils
- - warnings
- - wrap
array-api-compat hides from numpy:
- _CopyMode
- _NoValue
- __NUMPY_SETUP__
- __all__
- __config__
- __dir__
- __expired_attributes__
- __former_attrs__
- __future_scalars__
- __getattr__
- __numpy_submodules__
- _array_api_info
- _core
- _distributor_init
- _expired_attrs_2_0
- _globals
- _int_extended_msg
- _mat
- _msg
- _pyinstaller_hooks_dir
- _pytesttester
- _specific_msg
- _type_info
- _utils
array-api-compat hides from torch:
- _Any
- _C
- _Callable
- _GLOBAL_DEVICE_CONTEXT
- _InputT
- _Optional
- _ParamSpec
- _RetT
- _TorchCompileInductorWrapper
- _TorchCompileWrapper
- _TritonLibrary
- _TypeIs
- _TypeVar
- _Union
- _VF
- __all__
- __all_and_float_types
- __annotations__
- __config__
- __future__
- __getattr__
- __version__
- _adaptive_avg_pool2d
- _adaptive_avg_pool3d
- _add_batch_dim
- _add_relu
- _add_relu_
- _addmm_activation
- _aminmax
- _amp_foreach_non_finite_check_and_unscale_
- _amp_update_scale_
- _as_tensor_fullprec
- _assert
- _assert_async
- _assert_scalar
- _assert_tensor_metadata
- _awaits
- _batch_norm_impl_index
- _cast_Byte
- _cast_Char
- _cast_Double
- _cast_Float
- _cast_Half
- _cast_Int
- _cast_Long
- _cast_Short
- _check
- _check_index
- _check_is_size
- _check_not_implemented
- _check_tensor_all
- _check_tensor_all_with
- _check_type
- _check_value
- _check_with
- _choose_qparams_per_tensor
- _chunk_cat
- _classes
- _coalesce
- _compile
- _compute_linear_combination
- _conj
- _conj_copy
- _conj_physical
- _constrain_as_size
- _convert_indices_from_coo_to_csr
- _convert_indices_from_csr_to_coo
- _convert_weight_to_int4pack
- _convert_weight_to_int4pack_for_cpu
- _convolution
- _convolution_mode
- _copy_from
- _copy_from_and_resize
- _cslt_compress
- _cslt_sparse_mm
- _cslt_sparse_mm_search
- _ctc_loss
- _cudnn_ctc_loss
- _cudnn_init_dropout_state
- _cudnn_rnn
- _cudnn_rnn_flatten_weight
- _cufft_clear_plan_cache
- _cufft_get_plan_cache_max_size
- _cufft_get_plan_cache_size
- _cufft_set_plan_cache_max_size
- _cummax_helper
- _cummin_helper
- _custom_op
- _custom_ops
- _debug_has_internal_overlap
- _decomp
- _deprecated_attrs
- _dim_arange
- _dirichlet_grad
- _disable_dynamo
- _disable_functionalization
- _dispatch
- _dyn_quant_matmul_4bit
- _dyn_quant_pack_4bit_weight
- _efficientzerotensor
- _embedding_bag
- _embedding_bag_forward_only
- _empty_affine_quantized
- _empty_per_channel_affine_quantized
- _enable_functionalization
- _environment
- _euclidean_dist
- _export
- _fake_quantize_learnable_per_channel_affine
- _fake_quantize_learnable_per_tensor_affine
- _fake_quantize_per_tensor_affine_cachemask_tensor_qparams
- _fft_c2c
- _fft_c2r
- _fft_r2c
- _fill_mem_eff_dropout_mask_
- _foobar
- _foreach_abs
- _foreach_abs_
- _foreach_acos
- _foreach_acos_
- _foreach_add
- _foreach_add_
- _foreach_addcdiv
- _foreach_addcdiv_
- _foreach_addcmul
- _foreach_addcmul_
- _foreach_asin
- _foreach_asin_
- _foreach_atan
- _foreach_atan_
- _foreach_ceil
- _foreach_ceil_
- _foreach_clamp_max
- _foreach_clamp_max_
- _foreach_clamp_min
- _foreach_clamp_min_
- _foreach_copy_
- _foreach_cos
- _foreach_cos_
- _foreach_cosh
- _foreach_cosh_
- _foreach_div
- _foreach_div_
- _foreach_erf
- _foreach_erf_
- _foreach_erfc
- _foreach_erfc_
- _foreach_exp
- _foreach_exp_
- _foreach_expm1
- _foreach_expm1_
- _foreach_floor
- _foreach_floor_
- _foreach_frac
- _foreach_frac_
- _foreach_lerp
- _foreach_lerp_
- _foreach_lgamma
- _foreach_lgamma_
- _foreach_log
- _foreach_log10
- _foreach_log10_
- _foreach_log1p
- _foreach_log1p_
- _foreach_log2
- _foreach_log2_
- _foreach_log_
- _foreach_max
- _foreach_maximum
- _foreach_maximum_
- _foreach_minimum
- _foreach_minimum_
- _foreach_mul
- _foreach_mul_
- _foreach_neg
- _foreach_neg_
- _foreach_norm
- _foreach_pow
- _foreach_pow_
- _foreach_reciprocal
- _foreach_reciprocal_
- _foreach_round
- _foreach_round_
- _foreach_rsqrt
- _foreach_rsqrt_
- _foreach_sigmoid
- _foreach_sigmoid_
- _foreach_sign
- _foreach_sign_
- _foreach_sin
- _foreach_sin_
- _foreach_sinh
- _foreach_sinh_
- _foreach_sqrt
- _foreach_sqrt_
- _foreach_sub
- _foreach_sub_
- _foreach_tan
- _foreach_tan_
- _foreach_tanh
- _foreach_tanh_
- _foreach_trunc
- _foreach_trunc_
- _foreach_zero_
- _freeze_functional_tensor
- _from_functional_tensor
- _functional_assert_async
- _functional_assert_scalar
- _functional_sym_constrain_range
- _functional_sym_constrain_range_for_size
- _functionalize_apply_view_metas
- _functionalize_are_all_mutations_hidden_from_autograd
- _functionalize_are_all_mutations_under_no_grad_or_inference_mode
- _functionalize_commit_update
- _functionalize_enable_reapply_views
- _functionalize_get_storage_size
- _functionalize_has_data_mutation
- _functionalize_has_metadata_mutation
- _functionalize_is_multi_output_view
- _functionalize_is_symbolic
- _functionalize_mark_mutation_hidden_from_autograd
- _functionalize_replace
- _functionalize_set_storage_changed
- _functionalize_sync
- _functionalize_unsafe_set
- _functionalize_was_inductor_storage_resized
- _functionalize_was_storage_changed
- _functorch
- _fused_adagrad_
- _fused_adam_
- _fused_adamw_
- _fused_dropout
- _fused_moving_avg_obs_fq_helper
- _fused_sdp_choice
- _fused_sgd_
- _fw_primal_copy
- _get_cuda_dep_paths
- _get_origin
- _grid_sampler_2d_cpu_fallback
- _guards
- _has_compatible_shallow_copy_type
- _higher_order_ops
- _histogramdd_bin_edges
- _histogramdd_from_bin_cts
- _histogramdd_from_bin_tensors
- _import_device_backends
- _import_dotted_name
- _index_put_impl_
- _indices_copy
- _initExtension
- _int_mm
- _is_all_true
- _is_any_true
- _is_device_backend_autoload_enabled
- _is_functional_tensor
- _is_functional_tensor_base
- _is_zerotensor
- _jit_internal
- _lazy_clone
- _lazy_modules
- _library
- _linalg_check_errors
- _linalg_det
- _linalg_eigh
- _linalg_slogdet
- _linalg_solve_ex
- _linalg_svd
- _linalg_utils
- _load_global_deps
- _lobpcg
- _log_softmax
- _log_softmax_backward_data
- _logcumsumexp
- _logging
- _lowrank
- _lstm_mps
- _lu_with_info
- _make_dep_token
- _make_dual
- _make_dual_copy
- _make_per_channel_quantized_tensor
- _make_per_tensor_quantized_tensor
- _masked_scale
- _masked_softmax
- _meta_registrations
- _mirror_autograd_meta_to
- _mixed_dtypes_linear
- _mkldnn
- _mkldnn_reshape
- _mkldnn_transpose
- _mkldnn_transpose_
- _mps_convolution
- _mps_convolution_transpose
- _namedtensor_internals
- _native_batch_norm_legit
- _native_batch_norm_legit_no_training
- _native_multi_head_attention
- _neg_view
- _neg_view_copy
- _nested_compute_contiguous_strides_offsets
- _nested_from_padded
- _nested_from_padded_and_nested_example
- _nested_from_padded_tensor
- _nested_get_jagged_dummy
- _nested_get_lengths
- _nested_get_max_seqlen
- _nested_get_min_seqlen
- _nested_get_offsets
- _nested_get_ragged_idx
- _nested_get_values
- _nested_get_values_copy
- _nested_tensor_from_mask
- _nested_tensor_from_mask_left_aligned
- _nested_tensor_from_tensor_list
- _nested_tensor_softmax_with_shape
- _nested_view_from_buffer
- _nested_view_from_buffer_copy
- _nested_view_from_jagged
- _nested_view_from_jagged_copy
- _nnpack_available
- _nnpack_spatial_convolution
- _ops
- _overload
- _pack_padded_sequence
- _pad_packed_sequence
- _pin_memory
- _preload_cuda_deps
- _prelu_kernel
- _prims
- _prims_common
- _print
- _propagate_xla_data
- _refs
- _register_device_module
- _remove_batch_dim
- _reshape_alias_copy
- _reshape_from_tensor
- _resize_output_
- _rowwise_prune
- _running_with_deploy
- _safe_softmax
- _sample_dirichlet
- _saturate_weight_to_fp16
- _scaled_dot_product_attention_math
- _scaled_dot_product_attention_math_for_mps
- _scaled_dot_product_cudnn_attention
- _scaled_dot_product_efficient_attention
- _scaled_dot_product_flash_attention
- _scaled_dot_product_flash_attention_for_cpu
- _scaled_grouped_mm
- _scaled_mm
- _segment_reduce
- _shape_as_tensor
- _sobol_engine_draw
- _sobol_engine_ff_
- _sobol_engine_initialize_state_
- _sobol_engine_scramble_
- _softmax
- _softmax_backward_data
- _sources
- _sparse_broadcast_to
- _sparse_broadcast_to_copy
- _sparse_csr_prod
- _sparse_csr_sum
- _sparse_log_softmax_backward_data
- _sparse_semi_structured_addmm
- _sparse_semi_structured_apply
- _sparse_semi_structured_apply_dense
- _sparse_semi_structured_linear
- _sparse_semi_structured_mm
- _sparse_semi_structured_tile
- _sparse_softmax_backward_data
- _sparse_sparse_matmul
- _sparse_sum
- _stack
- _standard_gamma
- _standard_gamma_grad
- _storage_classes
- _strobelight
- _subclasses
- _sym_acos
- _sym_asin
- _sym_atan
- _sym_cos
- _sym_cosh
- _sym_log2
- _sym_sin
- _sym_sinh
- _sym_sqrt
- _sym_tan
- _sym_tanh
- _sync
- _tensor
- _tensor_classes
- _tensor_str
- _test_autograd_multiple_dispatch
- _test_autograd_multiple_dispatch_view
- _test_autograd_multiple_dispatch_view_copy
- _test_check_tensor
- _test_functorch_fallback
- _test_parallel_materialize
- _test_serialization_subcmul
- _to_cpu
- _to_functional_tensor
- _to_sparse_semi_structured
- _transform_bias_rescale_qkv
- _transformer_encoder_layer_fwd
- _trilinear
- _triton_multi_head_attention
- _triton_scaled_dot_attention
- _unique
- _unique2
- _unpack_dual
- _unsafe_index
- _unsafe_index_put
- _unsafe_masked_index
- _unsafe_masked_index_put_accumulate
- _use_cudnn_ctc_loss
- _use_cudnn_rnn_flatten_weight
- _utils
- _utils_internal
- _validate_compressed_sparse_indices
- _validate_sparse_bsc_tensor_args
- _validate_sparse_bsr_tensor_args
- _validate_sparse_compressed_tensor_args
- _validate_sparse_coo_tensor_args
- _validate_sparse_csc_tensor_args
- _validate_sparse_csr_tensor_args
- _values_copy
- _vendor
- _vmap_internals
- _warn_typed_storage_removal
- _weight_int4pack_mm
- _weight_int4pack_mm_for_cpu
- _weight_int8pack_mm
- _weight_norm
- _weight_norm_interface
- _weights_only_unpickler
- _wrapped_linear_prepack
- _wrapped_quantized_linear_prepacked
- - cpu
- - cuda
array-api-compat adds to cupy:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- acos
- acosh
- asin
- asinh
- astype
- atan
- atan2
- atanh
- bitwise_invert
- bitwise_left_shift
- bitwise_right_shift
- bool
- concat
- cumulative_prod
- cumulative_sum
- isdtype
- matrix_transpose
- permute_dims
- pow
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat adds to dask.array:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- acos
- acosh
- argsort
- asin
- asinh
- astype
- atan
- atan2
- atanh
- bitwise_invert
- bitwise_left_shift
- bitwise_right_shift
- can_cast
- concat
- cumulative_prod
- cumulative_sum
- finfo
- iinfo
- isdtype
- matrix_transpose
- permute_dims
- pow
- sort
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat adds to numpy:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
array-api-compat adds to torch:
- UniqueAllResult
- UniqueCountsResult
- UniqueInverseResult
- __array_api_version__
- __array_namespace_info__
- astype
- bitwise_invert
- broadcast_arrays
- cumulative_prod
- cumulative_sum
- expand_dims
- isdtype
- matrix_transpose
- permute_dims
- repeat
- take_along_axis
- unique_all
- unique_counts
- unique_inverse
- unique_values
- unstack
- vecdot
array-api-compat hides from cupy:
+ - __builtins__
+ - __cached__
+ - __doc__
+ - __file__
- __getattr__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
- __version__
- _binary
- _core
- _creation
- _cupy
- _cupyx
- _default_memory_pool
- _default_pinned_memory_pool
- _deprecated_apis
- _embed_signatures
- _environment
- _functional
- _functools
- _indexing
- _io
- _logic
- _manipulation
- _math
- _misc
- _numpy
- _padding
- _sorting
- _statistics
- _sys
- _template
- _util
- _version
array-api-compat hides from dask.array:
- __all__
+ - __annotations__
+ - __cached__
+ - __doc__
+ - __file__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
- _array_expr_enabled
- _reductions_generic
- _shuffle
array-api-compat hides from numpy:
- _CopyMode
- _NoValue
- __NUMPY_SETUP__
- __all__
+ - __cached__
- __config__
- __dir__
+ - __doc__
- __expired_attributes__
+ - __file__
- __former_attrs__
- __future_scalars__
- __getattr__
+ - __loader__
+ - __name__
- __numpy_submodules__
+ - __package__
+ - __path__
+ - __spec__
- _array_api_info
- _core
- _distributor_init
- _expired_attrs_2_0
- _globals
- _int_extended_msg
- _mat
- _msg
- _pyinstaller_hooks_dir
- _pytesttester
- _specific_msg
- _type_info
+ - _typing
- _utils
array-api-compat hides from torch:
- _Any
- _C
- _Callable
- _GLOBAL_DEVICE_CONTEXT
- _InputT
- _Optional
- _ParamSpec
- _RetT
- _TorchCompileInductorWrapper
- _TorchCompileWrapper
- _TritonLibrary
- _TypeIs
- _TypeVar
- _Union
- _VF
- __all__
- __all_and_float_types
- __annotations__
+ - __cached__
- __config__
+ - __doc__
+ - __file__
- __future__
- __getattr__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
- __version__
- _adaptive_avg_pool2d
- _adaptive_avg_pool3d
- _add_batch_dim
- _add_relu
- _add_relu_
- _addmm_activation
- _aminmax
- _amp_foreach_non_finite_check_and_unscale_
- _amp_update_scale_
- _as_tensor_fullprec
- _assert
- _assert_async
- _assert_scalar
- _assert_tensor_metadata
- _awaits
- _batch_norm_impl_index
- _cast_Byte
- _cast_Char
- _cast_Double
- _cast_Float
- _cast_Half
- _cast_Int
- _cast_Long
- _cast_Short
- _check
- _check_index
- _check_is_size
- _check_not_implemented
- _check_tensor_all
- _check_tensor_all_with
- _check_type
- _check_value
- _check_with
- _choose_qparams_per_tensor
- _chunk_cat
- _classes
- _coalesce
- _compile
- _compute_linear_combination
- _conj
- _conj_copy
- _conj_physical
- _constrain_as_size
- _convert_indices_from_coo_to_csr
- _convert_indices_from_csr_to_coo
- _convert_weight_to_int4pack
- _convert_weight_to_int4pack_for_cpu
- _convolution
- _convolution_mode
- _copy_from
- _copy_from_and_resize
- _cslt_compress
- _cslt_sparse_mm
- _cslt_sparse_mm_search
- _ctc_loss
- _cudnn_ctc_loss
- _cudnn_init_dropout_state
- _cudnn_rnn
- _cudnn_rnn_flatten_weight
- _cufft_clear_plan_cache
- _cufft_get_plan_cache_max_size
- _cufft_get_plan_cache_size
- _cufft_set_plan_cache_max_size
- _cummax_helper
- _cummin_helper
- _custom_op
- _custom_ops
- _debug_has_internal_overlap
- _decomp
- _deprecated_attrs
- _dim_arange
- _dirichlet_grad
- _disable_dynamo
- _disable_functionalization
- _dispatch
- _dyn_quant_matmul_4bit
- _dyn_quant_pack_4bit_weight
- _efficientzerotensor
- _embedding_bag
- _embedding_bag_forward_only
- _empty_affine_quantized
- _empty_per_channel_affine_quantized
- _enable_functionalization
- _environment
- _euclidean_dist
- _export
- _fake_quantize_learnable_per_channel_affine
- _fake_quantize_learnable_per_tensor_affine
- _fake_quantize_per_tensor_affine_cachemask_tensor_qparams
- _fft_c2c
- _fft_c2r
- _fft_r2c
- _fill_mem_eff_dropout_mask_
- _foobar
- _foreach_abs
- _foreach_abs_
- _foreach_acos
- _foreach_acos_
- _foreach_add
- _foreach_add_
- _foreach_addcdiv
- _foreach_addcdiv_
- _foreach_addcmul
- _foreach_addcmul_
- _foreach_asin
- _foreach_asin_
- _foreach_atan
- _foreach_atan_
- _foreach_ceil
- _foreach_ceil_
- _foreach_clamp_max
- _foreach_clamp_max_
- _foreach_clamp_min
- _foreach_clamp_min_
- _foreach_copy_
- _foreach_cos
- _foreach_cos_
- _foreach_cosh
- _foreach_cosh_
- _foreach_div
- _foreach_div_
- _foreach_erf
- _foreach_erf_
- _foreach_erfc
- _foreach_erfc_
- _foreach_exp
- _foreach_exp_
- _foreach_expm1
- _foreach_expm1_
- _foreach_floor
- _foreach_floor_
- _foreach_frac
- _foreach_frac_
- _foreach_lerp
- _foreach_lerp_
- _foreach_lgamma
- _foreach_lgamma_
- _foreach_log
- _foreach_log10
- _foreach_log10_
- _foreach_log1p
- _foreach_log1p_
- _foreach_log2
- _foreach_log2_
- _foreach_log_
- _foreach_max
- _foreach_maximum
- _foreach_maximum_
- _foreach_minimum
- _foreach_minimum_
- _foreach_mul
- _foreach_mul_
- _foreach_neg
- _foreach_neg_
- _foreach_norm
- _foreach_pow
- _foreach_pow_
- _foreach_reciprocal
- _foreach_reciprocal_
- _foreach_round
- _foreach_round_
- _foreach_rsqrt
- _foreach_rsqrt_
- _foreach_sigmoid
- _foreach_sigmoid_
- _foreach_sign
- _foreach_sign_
- _foreach_sin
- _foreach_sin_
- _foreach_sinh
- _foreach_sinh_
- _foreach_sqrt
- _foreach_sqrt_
- _foreach_sub
- _foreach_sub_
- _foreach_tan
- _foreach_tan_
- _foreach_tanh
- _foreach_tanh_
- _foreach_trunc
- _foreach_trunc_
- _foreach_zero_
- _freeze_functional_tensor
- _from_functional_tensor
- _functional_assert_async
- _functional_assert_scalar
- _functional_sym_constrain_range
- _functional_sym_constrain_range_for_size
- _functionalize_apply_view_metas
- _functionalize_are_all_mutations_hidden_from_autograd
- _functionalize_are_all_mutations_under_no_grad_or_inference_mode
- _functionalize_commit_update
- _functionalize_enable_reapply_views
- _functionalize_get_storage_size
- _functionalize_has_data_mutation
- _functionalize_has_metadata_mutation
- _functionalize_is_multi_output_view
- _functionalize_is_symbolic
- _functionalize_mark_mutation_hidden_from_autograd
- _functionalize_replace
- _functionalize_set_storage_changed
- _functionalize_sync
- _functionalize_unsafe_set
- _functionalize_was_inductor_storage_resized
- _functionalize_was_storage_changed
- _functorch
- _fused_adagrad_
- _fused_adam_
- _fused_adamw_
- _fused_dropout
- _fused_moving_avg_obs_fq_helper
- _fused_sdp_choice
- _fused_sgd_
- _fw_primal_copy
- _get_cuda_dep_paths
- _get_origin
- _grid_sampler_2d_cpu_fallback
- _guards
- _has_compatible_shallow_copy_type
- _higher_order_ops
- _histogramdd_bin_edges
- _histogramdd_from_bin_cts
- _histogramdd_from_bin_tensors
- _import_device_backends
- _import_dotted_name
- _index_put_impl_
- _indices_copy
- _initExtension
- _int_mm
- _is_all_true
- _is_any_true
- _is_device_backend_autoload_enabled
- _is_functional_tensor
- _is_functional_tensor_base
- _is_zerotensor
- _jit_internal
- _lazy_clone
- _lazy_modules
- _library
- _linalg_check_errors
- _linalg_det
- _linalg_eigh
- _linalg_slogdet
- _linalg_solve_ex
- _linalg_svd
- _linalg_utils
- _load_global_deps
- _lobpcg
- _log_softmax
- _log_softmax_backward_data
- _logcumsumexp
- _logging
- _lowrank
- _lstm_mps
- _lu_with_info
- _make_dep_token
- _make_dual
- _make_dual_copy
- _make_per_channel_quantized_tensor
- _make_per_tensor_quantized_tensor
- _masked_scale
- _masked_softmax
- _meta_registrations
- _mirror_autograd_meta_to
- _mixed_dtypes_linear
- _mkldnn
- _mkldnn_reshape
- _mkldnn_transpose
- _mkldnn_transpose_
- _mps_convolution
- _mps_convolution_transpose
- _namedtensor_internals
- _native_batch_norm_legit
- _native_batch_norm_legit_no_training
- _native_multi_head_attention
- _neg_view
- _neg_view_copy
- _nested_compute_contiguous_strides_offsets
- _nested_from_padded
- _nested_from_padded_and_nested_example
- _nested_from_padded_tensor
- _nested_get_jagged_dummy
- _nested_get_lengths
- _nested_get_max_seqlen
- _nested_get_min_seqlen
- _nested_get_offsets
- _nested_get_ragged_idx
- _nested_get_values
- _nested_get_values_copy
- _nested_tensor_from_mask
- _nested_tensor_from_mask_left_aligned
- _nested_tensor_from_tensor_list
- _nested_tensor_softmax_with_shape
- _nested_view_from_buffer
- _nested_view_from_buffer_copy
- _nested_view_from_jagged
- _nested_view_from_jagged_copy
- _nnpack_available
- _nnpack_spatial_convolution
- _ops
- _overload
- _pack_padded_sequence
- _pad_packed_sequence
- _pin_memory
- _preload_cuda_deps
- _prelu_kernel
- _prims
- _prims_common
- _print
- _propagate_xla_data
- _refs
- _register_device_module
- _remove_batch_dim
- _reshape_alias_copy
- _reshape_from_tensor
- _resize_output_
- _rowwise_prune
- _running_with_deploy
- _safe_softmax
- _sample_dirichlet
- _saturate_weight_to_fp16
- _scaled_dot_product_attention_math
- _scaled_dot_product_attention_math_for_mps
- _scaled_dot_product_cudnn_attention
- _scaled_dot_product_efficient_attention
- _scaled_dot_product_flash_attention
- _scaled_dot_product_flash_attention_for_cpu
- _scaled_grouped_mm
- _scaled_mm
- _segment_reduce
- _shape_as_tensor
- _sobol_engine_draw
- _sobol_engine_ff_
- _sobol_engine_initialize_state_
- _sobol_engine_scramble_
- _softmax
- _softmax_backward_data
- _sources
- _sparse_broadcast_to
- _sparse_broadcast_to_copy
- _sparse_csr_prod
- _sparse_csr_sum
- _sparse_log_softmax_backward_data
- _sparse_semi_structured_addmm
- _sparse_semi_structured_apply
- _sparse_semi_structured_apply_dense
- _sparse_semi_structured_linear
- _sparse_semi_structured_mm
- _sparse_semi_structured_tile
- _sparse_softmax_backward_data
- _sparse_sparse_matmul
- _sparse_sum
- _stack
- _standard_gamma
- _standard_gamma_grad
- _storage_classes
- _strobelight
- _subclasses
- _sym_acos
- _sym_asin
- _sym_atan
- _sym_cos
- _sym_cosh
- _sym_log2
- _sym_sin
- _sym_sinh
- _sym_sqrt
- _sym_tan
- _sym_tanh
- _sync
- _tensor
- _tensor_classes
- _tensor_str
- _test_autograd_multiple_dispatch
- _test_autograd_multiple_dispatch_view
- _test_autograd_multiple_dispatch_view_copy
- _test_check_tensor
- _test_functorch_fallback
- _test_parallel_materialize
- _test_serialization_subcmul
- _to_cpu
- _to_functional_tensor
- _to_sparse_semi_structured
- _transform_bias_rescale_qkv
- _transformer_encoder_layer_fwd
- _trilinear
- _triton_multi_head_attention
- _triton_scaled_dot_attention
- _unique
- _unique2
- _unpack_dual
- _unsafe_index
- _unsafe_index_put
- _unsafe_masked_index
- _unsafe_masked_index_put_accumulate
- _use_cudnn_ctc_loss
- _use_cudnn_rnn_flatten_weight
- _utils
- _utils_internal
- _validate_compressed_sparse_indices
- _validate_sparse_bsc_tensor_args
- _validate_sparse_bsr_tensor_args
- _validate_sparse_compressed_tensor_args
- _validate_sparse_coo_tensor_args
- _validate_sparse_csc_tensor_args
- _validate_sparse_csr_tensor_args
- _values_copy
- _vendor
- _vmap_internals
- _warn_typed_storage_removal
- _weight_int4pack_mm
- _weight_int4pack_mm_for_cpu
- _weight_int8pack_mm
- _weight_norm
- _weight_norm_interface
- _weights_only_unpickler
- _wrapped_linear_prepack
- _wrapped_quantized_linear_prepacked
Okay, thanks. So, if I read this right, as compared to main this PR
- adds some symbols (
Finalfor dask.array) - hides some symbols present in the bare namespace (
torch.cuda, ~400 private symbols on torch, something on other backends, too).
Extra symbols would be nice to hide, and previously the package worked quite a lot to hide them. It's a nice-to-have though.
Hiding things is a bit more problematic IMO. If array-api-compat's job is to extend the namespace to be compatible with the spec, it should not second-guess the namespace on what should be visible and what shouldn't. The target namespace should contain just what is in the bare namespace, plus spec-mandated symbols IMO.
<aside>
It's a bit suboptimal that a PR which claims to add type hints changes unrelated properties of the namespace, and then a PR which claims to improve tests has to undo some of these unrelated changes (and of course adds some more changes, too, because it's just too messy otherwise.)
</aside>
Okay, thanks. So, if I read this right, as compared to main this PR
- adds some symbols (
Finalfor dask.array)- hides some symbols present in the bare namespace (
torch.cuda, ~400 private symbols on torch, something on other backends, too).
No, it's the other way around.
This PR no longer adds Final and a bunch of private symbols.
It no longer hides these public symbols from Dask:
array-api-compat hides from dask.array:
- - ARRAY_EXPR_ENABLED
- __all__
- _array_expr_enabled
- _reductions_generic
- _shuffle
- - annotations
- - chunk
- - chunk_types
- - core
- - creation
- - dispatch
- - einsumfuncs
- - importlib
- - numpy_compat
- - optimization
- - reductions
- - routines
- - slicing
- - tiledb_io
- - ufunc
- - utils
- - warnings
- - wrap
It no longer hides these public symbols from torch:
- - cpu
- - cuda
It starts hiding a handful extra private symbols of no importance.
array-api-compat hides from cupy:
+ - __builtins__
+ - __cached__
+ - __doc__
+ - __file__
- __getattr__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
[...]
array-api-compat hides from dask.array:
- __all__
+ - __annotations__
+ - __cached__
+ - __doc__
+ - __file__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
- _array_expr_enabled
- _reductions_generic
- _shuffle
array-api-compat hides from numpy:
- _CopyMode
- _NoValue
- __NUMPY_SETUP__
- __all__
+ - __cached__
- __config__
- __dir__
+ - __doc__
- __expired_attributes__
+ - __file__
- __former_attrs__
- __future_scalars__
- __getattr__
+ - __loader__
+ - __name__
- __numpy_submodules__
+ - __package__
+ - __path__
+ - __spec__
[...]
+ - _typing
- _utils
array-api-compat hides from torch:
[...]
+ - __cached__
- __config__
+ - __doc__
+ - __file__
- __future__
- __getattr__
+ - __loader__
+ - __name__
+ - __package__
+ - __path__
+ - __spec__
Great, thanks. I misread then.
What still exists is hiding private symbols (see below for torch). Would it be difficult to remove the filter and pass through whatever the library has in its dir list?
In [12]: from array_api_compat import torch as xp
In [13]: set(dir(torch)) - set(dir(xp))
Out[13]:
{'_Any',
'_C',
'_Callable',
'_GLOBAL_DEVICE_CONTEXT',
'_InputT',
'_Optional',
'_ParamSpec',
'_RetT',
'_TorchCompileInductorWrapper',
'_TorchCompileWrapper',
'_TritonLibrary',
'_TypeIs',
'_TypeVar',
'_Union',
'_VF',
'__all__',
'__all_and_float_types',
'__annotations__',
'__cached__',
'__config__',
'__doc__',
'__file__',
'__future__',
'__getattr__',
'__loader__',
'__name__',
'__package__',
'__path__',
'__spec__',
'__version__',
'_adaptive_avg_pool2d',
'_adaptive_avg_pool3d',
'_add_batch_dim',
'_add_relu',
'_add_relu_',
'_addmm_activation',
'_aminmax',
'_amp_foreach_non_finite_check_and_unscale_',
'_amp_update_scale_',
'_as_tensor_fullprec',
'_assert',
'_assert_async',
'_assert_scalar',
'_assert_tensor_metadata',
'_awaits',
'_batch_norm_impl_index',
'_cast_Byte',
'_cast_Char',
'_cast_Double',
'_cast_Float',
'_cast_Half',
'_cast_Int',
'_cast_Long',
'_cast_Short',
'_check',
'_check_index',
'_check_is_size',
'_check_not_implemented',
'_check_tensor_all',
'_check_tensor_all_with',
'_check_type',
'_check_value',
'_check_with',
'_choose_qparams_per_tensor',
'_chunk_cat',
'_classes',
'_coalesce',
'_compile',
'_compute_linear_combination',
'_conj',
'_conj_copy',
'_conj_physical',
'_constrain_as_size',
'_convert_indices_from_coo_to_csr',
'_convert_indices_from_csr_to_coo',
'_convert_weight_to_int4pack',
'_convert_weight_to_int4pack_for_cpu',
'_convolution',
'_convolution_mode',
'_copy_from',
'_copy_from_and_resize',
'_cslt_compress',
'_cslt_sparse_mm',
'_cslt_sparse_mm_search',
'_ctc_loss',
'_cudnn_ctc_loss',
'_cudnn_init_dropout_state',
'_cudnn_rnn',
'_cudnn_rnn_flatten_weight',
'_cufft_clear_plan_cache',
'_cufft_get_plan_cache_max_size',
'_cufft_get_plan_cache_size',
'_cufft_set_plan_cache_max_size',
'_cummax_helper',
'_cummin_helper',
'_custom_op',
'_custom_ops',
'_debug_has_internal_overlap',
'_decomp',
'_deprecated_attrs',
'_dim_arange',
'_dirichlet_grad',
'_disable_dynamo',
'_disable_functionalization',
'_dispatch',
'_dyn_quant_matmul_4bit',
'_dyn_quant_pack_4bit_weight',
'_efficientzerotensor',
'_embedding_bag',
'_embedding_bag_forward_only',
'_empty_affine_quantized',
'_empty_per_channel_affine_quantized',
'_enable_functionalization',
'_environment',
'_euclidean_dist',
'_export',
'_fake_quantize_learnable_per_channel_affine',
'_fake_quantize_learnable_per_tensor_affine',
'_fake_quantize_per_tensor_affine_cachemask_tensor_qparams',
'_fft_c2c',
'_fft_c2r',
'_fft_r2c',
'_fill_mem_eff_dropout_mask_',
'_foobar',
'_foreach_abs',
'_foreach_abs_',
'_foreach_acos',
'_foreach_acos_',
'_foreach_add',
'_foreach_add_',
'_foreach_addcdiv',
'_foreach_addcdiv_',
'_foreach_addcmul',
'_foreach_addcmul_',
'_foreach_asin',
'_foreach_asin_',
'_foreach_atan',
'_foreach_atan_',
'_foreach_ceil',
'_foreach_ceil_',
'_foreach_clamp_max',
'_foreach_clamp_max_',
'_foreach_clamp_min',
'_foreach_clamp_min_',
'_foreach_copy_',
'_foreach_cos',
'_foreach_cos_',
'_foreach_cosh',
'_foreach_cosh_',
'_foreach_div',
'_foreach_div_',
'_foreach_erf',
'_foreach_erf_',
'_foreach_erfc',
'_foreach_erfc_',
'_foreach_exp',
'_foreach_exp_',
'_foreach_expm1',
'_foreach_expm1_',
'_foreach_floor',
'_foreach_floor_',
'_foreach_frac',
'_foreach_frac_',
'_foreach_lerp',
'_foreach_lerp_',
'_foreach_lgamma',
'_foreach_lgamma_',
'_foreach_log',
'_foreach_log10',
'_foreach_log10_',
'_foreach_log1p',
'_foreach_log1p_',
'_foreach_log2',
'_foreach_log2_',
'_foreach_log_',
'_foreach_max',
'_foreach_maximum',
'_foreach_maximum_',
'_foreach_minimum',
'_foreach_minimum_',
'_foreach_mul',
'_foreach_mul_',
'_foreach_neg',
'_foreach_neg_',
'_foreach_norm',
'_foreach_pow',
'_foreach_pow_',
'_foreach_reciprocal',
'_foreach_reciprocal_',
'_foreach_round',
'_foreach_round_',
'_foreach_rsqrt',
'_foreach_rsqrt_',
'_foreach_sigmoid',
'_foreach_sigmoid_',
'_foreach_sign',
'_foreach_sign_',
'_foreach_sin',
'_foreach_sin_',
'_foreach_sinh',
'_foreach_sinh_',
'_foreach_sqrt',
'_foreach_sqrt_',
'_foreach_sub',
'_foreach_sub_',
'_foreach_tan',
'_foreach_tan_',
'_foreach_tanh',
'_foreach_tanh_',
'_foreach_trunc',
'_foreach_trunc_',
'_foreach_zero_',
'_freeze_functional_tensor',
'_from_functional_tensor',
'_functional_assert_async',
'_functional_assert_scalar',
'_functional_sym_constrain_range',
'_functional_sym_constrain_range_for_size',
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Great, thanks. I misread then.
What still exists is hiding private symbols (see below for torch). Would it be difficult to remove the filter and pass through whatever the library has in its
dirlist?
It's non-trivial, because right now dir() and __all__ are one and the same. And you don't want the private symbols in __all__. Since it is not a regression, I'd much rather leave it to a follow-up.
One problem is it is a regression. On main (unless I'm being dense again):
In [3]: set(dir(xp)) - set(dir(torch))
Out[3]:
{'UniqueAllResult',
'UniqueCountsResult',
'UniqueInverseResult',
'__array_api_version__',
'__array_namespace_info__',
'_aliases',
'_info',
'_typing',
'astype',
'bitwise_invert',
'broadcast_arrays',
'cumulative_prod',
'cumulative_sum',
'expand_dims',
'isdtype',
'matrix_transpose',
'permute_dims',
'repeat',
'take_along_axis',
'unique_all',
'unique_counts',
'unique_inverse',
'unique_values',
'unstack',
'vecdot'}
Or are you saying it brings the status quo back to one of previous versions?
EDIT: Nevermind, I am being dense. Here are all these private functions, safely hidden, also on main.
In [5]: len(set(dir(torch)) - set(dir(xp)))
Out[5]: 442
Okay, lets merge this and see about exporting private items separately (Checked it: they have been hidden from at least 1.9.1; thus it's rather low prio; let's wait for if and when it becomes a problem).
Thanks @crusaderky