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Quantax 0.3.0 documentation

  • Quick Start
  • Exact diagonalization
  • Build your network
  • Samples and Measurement
  • Square J1-J2 model
    • Triangular Heisenberg model
    • Fermion mean field
    • Neural Jastrow
    • Real-time dynamics
    • Local updates
    • 🔪 The Sharp Bits 🔪
    • Restricted Boltzmann machine
    • Time-dependent variational principle
    • Minimum-norm stochastic reconfiguration
    • Neural network backflow
    • global_defs
    • sites
    • symmetry
    • operator
    • nn
    • model
    • state
    • sampler
    • optimizer
    • utils
    • Related packages
    • Research papers
  • Quick Start
  • Exact diagonalization
  • Build your network
  • Samples and Measurement
  • Square J1-J2 model
  • Triangular Heisenberg model
  • Fermion mean field
  • Neural Jastrow
  • Real-time dynamics
  • Local updates
  • 🔪 The Sharp Bits 🔪
  • Restricted Boltzmann machine
  • Time-dependent variational principle
  • Minimum-norm stochastic reconfiguration
  • Neural network backflow
  • global_defs
  • sites
  • symmetry
  • operator
  • nn
  • model
  • state
  • sampler
  • optimizer
  • utils
  • Related packages
  • Research papers

Section Navigation

  • quantax.utils.DataTracer
  • quantax.utils.make_mesh
  • quantax.utils.get_distributed_P
  • quantax.utils.get_distributed_sharding
  • quantax.utils.get_replicated_sharding
  • quantax.utils.is_sharded_array
  • quantax.utils.to_distributed_array
  • quantax.utils.to_replicated_array
  • quantax.utils.global_to_local
  • quantax.utils.local_to_global
  • quantax.utils.local_to_replicated
  • quantax.utils.to_replicated_numpy
  • quantax.utils.array_extend
  • quantax.utils.array_set
  • quantax.utils.tree_fully_flatten
  • quantax.utils.filter_tree_map
  • quantax.utils.tree_split_cpl
  • quantax.utils.tree_combine_cpl
  • quantax.utils.apply_updates
  • quantax.utils.jit_chunk_vmap
  • quantax.utils.chunk_map
  • quantax.utils.LogArray
  • quantax.utils.ScaleArray
  • quantax.utils.ints_to_array
  • quantax.utils.array_to_ints
  • quantax.utils.neel
  • quantax.utils.stripe
  • quantax.utils.Sqz_factor
  • quantax.utils.rand_states
  • utils
  • quantax.utils.to_replicated_numpy

quantax.utils.to_replicated_numpy#

quantax.utils.to_replicated_numpy(array: Array) → ndarray#

Gather a (possibly distributed) array into a contiguous numpy array holding the full data, identical on every process.

In multi-host jobs the array is first replicated and then brought to the host with jax.experimental.multihost_utils.global_array_to_host_local_array().

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