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Functions4,946 in github.com/ml-explore/mlx

↓ 2 callersFunctionensure_row_contiguous
mlx/backend/cpu/distributed.cpp:12
↓ 2 callersFunctioneval
mlx/transforms.cpp:330
↓ 2 callersFunctioneval_cpu
mlx/primitives.h:137
↓ 2 callersFunctioneval_gpu
mlx/primitives.h:142
↓ 2 callersFunctioneval_impl
mlx/transforms.cpp:74
↓ 2 callersFunctionexpand_dims_impl
mlx/ops.cpp:589
↓ 2 callersFunctionexpm1f
Compute exponential base e minus 1. max ulp err = 0.99746 */
mlx/backend/metal/kernels/expm1f.h:80
↓ 2 callersFunctionexport_to_dot
mlx/graph_utils.h:48
↓ 2 callersFunctionflop_count
mlx/einsum.cpp:125
↓ 2 callersFunctionfmt_bytes
mlx/distributed/jaccl/lib/examples/allreduce_bench.cpp:70
↓ 2 callersFunctionfmt_row
(row)
benchmarks/python/segmented_mm_bench.py:88
↓ 2 callersFunctionfmt_row
(row)
benchmarks/python/block_masked_mm_bench.py:74
↓ 2 callersFunctionfp_qmm_dispatch
mlx/backend/cpu/quantized.cpp:673
↓ 2 callersFunctionfp_quantize
mlx/backend/metal/kernels/fp_quantized.h:1805
↓ 2 callersMethodfree
mlx/backend/cuda/allocator.cpp:147
↓ 2 callersMethodfrom_embedding
Create a :obj:`QuantizedEmbedding` layer from an :obj:`Embedding` layer.
python/mlx/nn/layers/quantized.py:180
↓ 2 callersMethodfrom_file
Parse the json hostfile that contains both the hostnames to ssh into and the ips to communicate over when using the ring backend. It can also
python/mlx/_distributed_utils/common.py:37
↓ 2 callersMethodfrom_linear
Create a :obj:`QQLinear` layer from a :obj:`Linear` layer.
python/mlx/nn/layers/quantized.py:411
↓ 2 callersMethodfrom_list
(cls, hostlist, repeats=1)
python/mlx/_distributed_utils/common.py:91
↓ 2 callersMethodfrom_quantized_linear
( cls, quantized_linear_layer: Module, *, segments: Union[int, list] = 1,
python/mlx/nn/layers/distributed.py:459
↓ 2 callersFunctionfull_impl
mlx/ops.cpp:297
↓ 2 callersFunctionfull_like
mlx/ops.cpp:317
↓ 2 callersFunctiongather_mm
Compute matrix product with matrix-level gather */
mlx/ops.cpp:5785
↓ 2 callersFunctiongather_mm_grad
Calculate the gradient wrt to the weights of the following calculation y = gather_mm(x, w.T, lhs_indices, rhs_indices, sorted) Note the transpose ab
mlx/primitives.cpp:121
↓ 2 callersFunctiongather_qmm
mlx/ops.cpp:5266
↓ 2 callersFunctiongather_qmv
mlx/backend/metal/quantized.cpp:960
↓ 2 callersFunctiongather_sort
(x, indices)
benchmarks/python/gather_qmm_bench.py:13
↓ 2 callersFunctiongelu_1
tests/compile_tests.cpp:409
↓ 2 callersFunctiongemm_conv
mlx/backend/cuda/conv/conv.h:77
↓ 2 callersFunctiongemv
mlx/backend/metal/matmul.cpp:1182
↓ 2 callersFunctionget_2d_grid_dims_common
mlx/backend/common/utils.cpp:148
↓ 2 callersFunctionget_block_dims_common
mlx/backend/common/utils.cpp:117
↓ 2 callersFunctionget_copy_kernel
mlx/backend/metal/jit_kernels.cpp:194
↓ 2 callersFunctionget_cpu_architecture
Get CPU architecture string at runtime
mlx/backend/cpu/device_info.cpp:20
↓ 2 callersFunctionget_gbyte_size
(in_vec_len, out_vec_len, np_dtype)
benchmarks/python/blas/bench_gemv.py:129
↓ 2 callersFunctionget_gflop_count
(in_vec_len, out_vec_len)
benchmarks/python/blas/bench_gemv.py:123
↓ 2 callersFunctionget_memory_limit
mlx/backend/cuda/allocator.cpp:433
↓ 2 callersFunctionget_padded_scale_dims
Compute padded dimensions for tiled layout Tiles are 128 rows × 4 columns, must allocate full tiles
mlx/backend/cuda/quantized/qqmm_utils.h:12
↓ 2 callersFunctionget_peak_memory
mlx/backend/cuda/allocator.cpp:424
↓ 2 callersFunctionget_ptx_path
mlx/backend/cuda/jit_module.cpp:124
↓ 2 callersFunctionget_qmv_batch_limit
mlx/backend/metal/quantized.cpp:84
↓ 2 callersMethodget_ring_connectivity
mlx/distributed/jaccl/lib/jaccl/jaccl.cpp:158
↓ 2 callersFunctionget_shape
mlx/io/gguf.cpp:50
↓ 2 callersMethodget_size
mlx/distributed/jaccl/lib/jaccl/jaccl.h:29
↓ 2 callersFunctionget_steel_gemm_gather_kernel
mlx/backend/metal/jit_kernels.cpp:626
↓ 2 callersFunctionget_steel_gemm_splitk_accum_kernel
mlx/backend/metal/jit_kernels.cpp:559
↓ 2 callersFunctionget_twiddle
Compute an FFT twiddle factor
mlx/backend/metal/kernels/fft/radix.h:29
↓ 2 callersFunctionget_version
()
setup.py:26
↓ 2 callersFunctiongumbel
mlx/random.cpp:361
↓ 2 callersFunctionhadamard_mn_contiguous
mlx/backend/metal/hadamard.cpp:60
↓ 2 callersFunctionimplicit_gemm_conv_2D_gpu
mlx/backend/metal/conv.cpp:191
↓ 2 callersFunctionimplicit_gemm_conv_3D_gpu
mlx/backend/metal/conv.cpp:503
↓ 2 callersFunctionin_tracing
Return true if we are currently performing a function transformation in * order to keep the graph when evaluating tracer arrays. */
mlx/transforms_impl.h:69
↓ 2 callersFunctioninit
mlx/distributed/mpi/mpi.cpp:490
↓ 2 callersFunctioninv_impl
mlx/linalg.cpp:296
↓ 2 callersFunctionis_available
mlx/backend/metal/metal.cpp:10
↓ 2 callersFunctionis_available
mlx/distributed/mpi/mpi.cpp:486
↓ 2 callersFunctionis_big_endian
mlx/export.cpp:23
↓ 2 callersFunctionis_empty_dim
mlx/backend/cuda/device.cpp:33
↓ 2 callersMethodis_equivalent
mlx/fast.cpp:180
↓ 2 callersFunctionis_none_slice
python/src/indexing.cpp:12
↓ 2 callersFunctionis_ostream_object
python/src/load.cpp:39
↓ 2 callersMethodis_signaled
mlx/backend/metal/event.cpp:57
↓ 2 callersFunctionis_valid_index_type
python/src/indexing.cpp:81
↓ 2 callersMethodis_valid_ring
mlx/distributed/jaccl/lib/jaccl/jaccl.cpp:125
↓ 2 callersFunctionitemsize
The size of the array's datatype in bytes. */
mlx/array.h:95
↓ 2 callersFunctionlayer_norm
(x, w, b, eps)
benchmarks/python/layer_norm_bench.py:10
↓ 2 callersMethodlisten
mlx/distributed/jaccl/lib/jaccl/tcp.cpp:90
↓ 2 callersMethodload
mlx/backend/metal/kernels/steel/gemm/nax.h:666
↓ 2 callersFunctionload_nvrtc
mlx/backend/cuda/delayload.cpp:26
↓ 2 callersMethodload_safe
mlx/backend/metal/kernels/steel/conv/loaders/loader_general.h:140
↓ 2 callersFunctionload_swiftpm_library
mlx/backend/metal/device.cpp:129
↓ 2 callersMethodlog_debug
mlx/backend/metal/kernels/logging.h:19
↓ 2 callersFunctionloss_fn
(params, X, y)
examples/export/train_mlp.py:51
↓ 2 callersFunctionlu_helper
mlx/linalg.cpp:586
↓ 2 callersFunctionmake_connections
* The counterpoint of `accept_connections`. Basically connect to each of the * provided addresses. */
mlx/distributed/ring/ring.cpp:349
↓ 2 callersFunctionmake_index_args
mlx/backend/metal/indexing.cpp:24
↓ 2 callersFunctionmake_regex_search
(regexes)
benchmarks/python/comparative/compare.py:38
↓ 2 callersFunctionmake_string
mlx/backend/metal/utils.h:22
↓ 2 callersFunctionmake_tracer
Create a tracer copy of a primal for use in vjp/jvp. If the primal is a stale Copy from a previous transform call (not an active tracer), peel it off
mlx/transforms.cpp:32
↓ 2 callersMethodmalloc
mlx/backend/cuda/allocator.cpp:134
↓ 2 callersFunctionmask_matrix
mlx/backend/cpu/masked_mm.cpp:18
↓ 2 callersFunctionmatmul_bnns
mlx/backend/cpu/gemms/bnns.cpp:29
↓ 2 callersFunctionmatmul_general
mlx/backend/cpu/matmul.cpp:69
↓ 2 callersFunctionmatrix_norm
mlx/linalg.cpp:80
↓ 2 callersFunctionmax_mb_per_buffer
mlx/utils.h:160
↓ 2 callersFunctionmax_ops_per_buffer
mlx/utils.h:154
↓ 2 callersFunctionmeasure
(fn)
benchmarks/python/masked_scatter.py:99
↓ 2 callersFunctionmerge
Helper that merges two arrays in the graph by setting the parents of the source to point to the destination. The arrays are assumed to be coming from
mlx/compile.cpp:257
↓ 2 callersFunctionmlx_get_item_array
python/src/indexing.cpp:108
↓ 2 callersFunctionmlx_naive_block_masked_mm
MLX naive: expand masks and use regular matmul.
benchmarks/python/block_masked_mm_bench.py:38
↓ 2 callersFunctionmlx_savez_helper
python/src/load.cpp:423
↓ 2 callersFunctionmlx_to_np_array
python/src/convert.cpp:153
↓ 2 callersMethodmove_to_unified_memory
mlx/backend/cuda/allocator.cpp:301
↓ 2 callersMethodmtl_residency_set
mlx/backend/metal/resident.h:19
↓ 2 callersFunctionndim
The number of dimensions of the array. */
mlx/array.h:110
↓ 2 callersFunctionnormalize_dynamic_slice_inputs
mlx/ops.cpp:701
↓ 2 callersFunctionnormalized_strides
In MLX a singleton dim (shape[dim] == 1) can have any stride, but in cuDNN whether a tensor is contiguous is determined with: shape[dim] == shape[dim
mlx/backend/cuda/cudnn_utils.cpp:21
↓ 2 callersFunctionnp_logaddexp
(x1: np.ndarray, x2: np.ndarray)
python/tests/test_ops.py:25
↓ 2 callersMethodopen
python/src/load.cpp:76
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