Getting started
Resources, guides, and references
shard_map
jax.checkpoint
jax.remat
checkify
set_xla_metadata
Ref
jax.numpy
jax.scipy
jax.lax
jax.random
jax.sharding
jax.debug
jax.dlpack
jax.distributed
jax.dtypes
jax.ffi
jax.flatten_util
jax.image
jax.nn
jax.nn.initializers
jax.ops
jax.profiler
jax.ref
jax.stages
jax.test_util
jax.tree
jax.tree_util
jax.typing
jax.export
jax.extend
jax.extend.core
jax.extend.linear_util
jax.extend.mlir
jax.extend.random
jax.example_libraries
jax.example_libraries.optimizers
jax.example_libraries.stax
jax.experimental
jax.experimental.checkify
jax.experimental.compilation_cache
jax.experimental.custom_dce
jax.experimental.custom_partitioning
jax.experimental.jet
jax.experimental.key_reuse
jax.experimental.mesh_utils
jax.experimental.multihost_utils
jax.experimental.pallas
jax.experimental.pallas.mosaic_gpu
jax.experimental.pallas.triton
jax.experimental.pallas.tpu
jax.experimental.serialize_executable
jax.experimental.sparse
Array.mT
Compute the (batched) matrix transpose.
Refer tojax.numpy.matrix_transpose() for details.
jax.numpy.matrix_transpose()
