cuTensorNet (cuquantum.bindings.cutensornet)

Python objects & constants

Objects

tensor_qualifiers_dtype	NumPy dtype object that encapsulates the tensor qualifiers in bindings.cutensornet.
contraction_path_dtype	NumPy dtype object that encapsulates the contraction path in bindings.cutensornet.
slice_info_pair_dtype	NumPy dtype object that encapsulates the slice info pair in bindings.cutensornet.
slicing_config_dtype	NumPy dtype object that encapsulates the slicing config in bindings.cutensornet.

Enums

Status(value)	See cutensornetStatus_t.
NetworkAttribute(value)	See cutensornetNetworkAttributes_t.
ContractionAutotunePreferenceAttribute(value)	See cutensornetContractionAutotunePreferenceAttributes_t.
ContractionOptimizerConfigAttribute(value)	See cutensornetContractionOptimizerConfigAttributes_t.
ContractionOptimizerInfoAttribute(value)	See cutensornetContractionOptimizerInfoAttributes_t.
GraphAlgo(value)	See cutensornetGraphAlgo_t.
MemoryModel(value)	See cutensornetMemoryModel_t.
OptimizerCost(value)	See cutensornetOptimizerCost_t.
SmartOption(value)	See cutensornetSmartOption_t.
WorksizePref(value)	See cutensornetWorksizePref_t.
Memspace(value)	See cutensornetMemspace_t.
WorkspaceKind(value)	See cutensornetWorkspaceKind_t.
TensorSVDConfigAttribute(value)	See cutensornetTensorSVDConfigAttributes_t.
TensorSVDInfoAttribute(value)	See cutensornetTensorSVDInfoAttributes_t.
TensorSVDNormalization(value)	See cutensornetTensorSVDNormalization_t.
TensorSVDPartition(value)	See cutensornetTensorSVDPartition_t.
TensorSVDAlgo(value)	See cutensornetTensorSVDAlgo_t.
GateSplitAlgo(value)	See cutensornetGateSplitAlgo_t.
StatePurity(value)	See cutensornetStatePurity_t.
BoundaryCondition(value)	See cutensornetBoundaryCondition_t.
StateAttribute(value)	See cutensornetStateAttributes_t.
StateMPOApplication(value)	See cutensornetStateMPOApplication_t.
StateMPSGaugeOption(value)	See cutensornetStateMPSGaugeOption_t.
MarginalAttribute(value)	See cutensornetMarginalAttributes_t.
SamplerAttribute(value)	See cutensornetSamplerAttributes_t.
AccessorAttribute(value)	See cutensornetAccessorAttributes_t.
ExpectationAttribute(value)	See cutensornetExpectationAttributes_t.

Python functions

Handle management API

create()	Initializes the cuTensorNet library.
destroy(intptr_t handle)	Destroys the cuTensorNet library handle.

Network descriptor API

create_network_descriptor(intptr_t handle, ...)	Initializes a cutensornetNetworkDescriptor_t, describing the connectivity (i.e., network topology) between the tensors.
destroy_network_descriptor(intptr_t desc)	Frees all the memory associated with the network descriptor.
get_output_tensor_descriptor(...)	Creates a cutensornetTensorDescriptor_t representing the output tensor of the network.
network_get_attribute(intptr_t handle, ...)	Gets attributes of network_descriptor.
network_set_attribute(intptr_t handle, ...)	Sets attributes of network_descriptor.
get_network_attribute_dtype(int attr)	Get the Python data type of the corresponding NetworkAttribute attribute.

Tensor descriptor API

create_tensor_descriptor(intptr_t handle, ...)	Initializes a cutensornetTensorDescriptor_t, describing the information of a tensor.
destroy_tensor_descriptor(intptr_t desc_tensor)	Frees all the memory associated with the tensor descriptor.
get_tensor_details(intptr_t handle, ...)	Get the tensor's metadata.

Contraction optimizer API

create_contraction_optimizer_info(...)	Allocates resources for optimizerInfo.
create_contraction_optimizer_info_from_packed_data(...)	Create an optimizerInfo object from the provided buffer.
update_contraction_optimizer_info_from_packed_data(...)	Update the provided optimizer_info object from the provided buffer.
destroy_contraction_optimizer_info(...)	Frees all the memory associated with optimizer_info.
get_contraction_optimizer_info_attribute_dtype(...)	Get the Python data type of the corresponding ContractionOptimizerInfoAttribute attribute.
contraction_optimizer_info_get_attribute(...)	Gets attributes of optimizer_info.
contraction_optimizer_info_set_attribute(...)	Sets attributes of optimizer_info.
contraction_optimizer_info_get_packed_size(...)	Gets the packed size of the optimizer_info object.
contraction_optimizer_info_pack_data(...)	Packs the optimizer_info object into the provided buffer.
create_contraction_optimizer_config(...)	Sets up the required hyper-optimization parameters for the contraction order solver (see contraction_optimize()).
destroy_contraction_optimizer_config(...)	Frees all the memory associated with optimizer_config.
get_contraction_optimizer_config_attribute_dtype(...)	Get the Python data type of the corresponding ContractionOptimizerConfigAttribute attribute.
contraction_optimizer_config_get_attribute(...)	Gets attributes of optimizer_config.
contraction_optimizer_config_set_attribute(...)	Sets attributes of optimizer_config.
contraction_optimize(intptr_t handle, ...)	Computes an "optimized" contraction order as well as slicing info (for more information see Overview section) for a given tensor network such that the total time to solution is minimized while adhering to the user-provided memory constraint.

Contraction plan API

create_contraction_plan(intptr_t handle, ...)	Initializes a cutensornetContractionPlan_t.
destroy_contraction_plan(intptr_t plan)	Frees all resources owned by plan.
create_contraction_autotune_preference(...)	Sets up the required auto-tune parameters for the contraction plan.
destroy_contraction_autotune_preference(...)	Frees all the memory associated with autotune_preference.
get_contraction_autotune_preference_attribute_dtype(...)	Get the Python data type of the corresponding ContractionAutotunePreferenceAttribute attribute.
contraction_autotune_preference_get_attribute(...)	Gets attributes of autotune_preference.
contraction_autotune_preference_set_attribute(...)	Sets attributes of autotune_preference.
contraction_autotune(intptr_t handle, ...)	Auto-tunes the contraction plan to find the best cutensorContractionPlan_t for each pair-wise contraction.

Workspace management API

create_workspace_descriptor(intptr_t handle)	Creates a workspace descriptor that holds information about the user provided memory buffer.
destroy_workspace_descriptor(intptr_t desc)	Frees the workspace descriptor.
workspace_compute_contraction_sizes(...)	Computes the workspace size needed to contract the input tensor network using the provided contraction path.
workspace_compute_qr_sizes(intptr_t handle, ...)	Computes the workspace size needed to perform the tensor QR operation.
workspace_compute_svd_sizes(intptr_t handle, ...)	Computes the workspace size needed to perform the tensor SVD operation.
workspace_compute_gate_split_sizes(...)	Computes the workspace size needed to perform the gating operation.
workspace_get_memory_size(intptr_t handle, ...)	Retrieves the needed workspace size for the given workspace preference, memory space, workspace kind.
workspace_set_memory(intptr_t handle, ...)	Sets the memory address and workspace size of the workspace provided by user.
workspace_get_memory(intptr_t handle, ...)	Retrieves the memory address and workspace size of workspace hosted in the workspace descriptor.
workspace_purge_cache(intptr_t handle, ...)	Purges the cached data in the specified memory space.

Memory management API

set_device_mem_handler(intptr_t handle, handler)	Set the device memory handler for cuTensorNet.
get_device_mem_handler(intptr_t handle)	Get the device memory handler for cuTensorNet.

Network contraction API

contract_slices(intptr_t handle, ...)

Performs the actual contraction of the tensor network.

Gradient computation API

compute_gradients_backward(intptr_t handle, ...)

Computes the gradients of the network w.r.t.

Slice group API

create_slice_group_from_id_range(...)	Create a cutensornetSliceGroup_t object from a range, which produces a sequence of slice IDs from the specified start (inclusive) to the specified stop (exclusive) values with the specified step.
create_slice_group_from_ids(intptr_t handle, ...)	Create a slice group from a sequence of slice IDs.
destroy_slice_group(intptr_t slice_group)	Releases the resources associated with a cutensornetSliceGroup_t object and sets its value to null.

Approximate tensor network execution API

tensor_qr(intptr_t handle, ...)	Performs QR decomposition of a tensor.
tensor_svd(intptr_t handle, ...)	Performs SVD decomposition of a tensor.
gate_split(intptr_t handle, ...)	Performs gate split operation.

Tensor SVD config API

create_tensor_svd_config(intptr_t handle)	Sets up the options for singular value decomposition and truncation.
destroy_tensor_svd_config(intptr_t svd_config)	Frees all the memory associated with the tensor svd configuration.
get_tensor_svd_config_attribute_dtype(int attr)	Get the Python data type of the corresponding TensorSVDConfigAttribute attribute.
tensor_svd_config_get_attribute(...)	Gets attributes of svd_config.
tensor_svd_config_set_attribute(...)	Sets attributes of svd_config.
tensor_svd_algo_params_get_dtype(int svd_algo)	Get the Python data type of the corresponding tensor SVD parameters attribute.

Tensor SVD info API

create_tensor_svd_info(intptr_t handle)	Sets up the information for singular value decomposition.
destroy_tensor_svd_info(intptr_t svd_info)	Frees all the memory associated with the TensorSVDInfo object.
get_tensor_svd_info_attribute_dtype(int attr)	Get the Python data type of the corresponding TensorSVDInfoAttribute attribute.
tensor_svd_info_get_attribute(...)	Gets attributes of svd_info.
tensor_svd_algo_status_get_dtype(int svd_algo)	Get the Python data type of the corresponding tensor SVD status attribute.

Distributed parallelization API

distributed_reset_configuration(...)	Resets the distributed MPI parallelization configuration.
distributed_get_num_ranks(intptr_t handle)	Queries the number of MPI ranks in the current distributed MPI configuration.
distributed_get_proc_rank(intptr_t handle)	Queries the rank of the current MPI process in the current distributed MPI configuration.
distributed_synchronize(intptr_t handle)	Globally synchronizes all MPI processes in the current distributed MPI configuration, ensuring that all preceding cutensornet API calls have completed across all MPI processes.

Tensor network state API

create_state(intptr_t handle, int purity, ...)	Creates an empty tensor network state of a given shape defined by the number of primary tensor modes and their extents.
destroy_state(intptr_t tensor_network_state)	Frees all resources owned by the tensor network state.
state_apply_tensor(intptr_t handle, ...)	DEPRECATED: Applies a tensor operator to the tensor network state.
state_apply_tensor_operator(intptr_t handle, ...)	Applies a tensor operator to the tensor network state.
state_apply_controlled_tensor_operator(...)	Applies a controlled tensor operator to the tensor network state.
state_apply_unitary_channel(intptr_t handle, ...)	Applies a tensor channel consisting of one or more unitary tensor operators to the tensor network state.
state_apply_general_channel(intptr_t handle, ...)	Applies a tensor channel consisting of one or more gneral Kraus operators to the tensor network state.
state_apply_network_operator(...)	Applies a tensor network operator to a tensor network state.
state_update_tensor(intptr_t handle, ...)	Registers an external update of the elements of the specified tensor operator that was previously applied to the tensor network state.
state_update_tensor_operator(...)	Registers an external update of the elements of the specified tensor operator that was previously applied to the tensor network state.
get_state_attribute_dtype(int attr)	Get the Python data type of the corresponding StateAttribute attribute.
state_configure(intptr_t handle, ...)	Configures computation of the full tensor network state, either in the exact or a factorized form.
state_prepare(intptr_t handle, ...)	Prepares computation of the full tensor network state, either in the exact or a factorized form.
state_get_info(intptr_t handle, ...)	Retrieves an attribute related to computation of the full tensor network state, either in the exact or a factorized form.
state_compute(intptr_t handle, ...)	Computes the tensor network state representation.
state_initialize_mps(intptr_t handle, ...)	Imposes a user-defined MPS (Matrix Product State) factorization on the initial tensor network state with the given shape and data.
state_finalize_mps(intptr_t handle, ...)	Imposes a user-defined MPS (Matrix Product State) factorization on the final tensor network state with the given shape.
state_capture_mps(intptr_t handle, ...)	Resets the tensor network state to the MPS state previously computed via cutensornetStateCompute.
get_output_state_details(intptr_t handle, ...)	Get the output state tensors' metadata.
create_marginal(intptr_t handle, ...)	Creates a representation of the specified marginal tensor for a given tensor network state.
destroy_marginal(...)	Destroys the tensor network state marginal.
get_marginal_attribute_dtype(int attr)	Get the Python data type of the corresponding MarginalAttribute attribute.
marginal_configure(intptr_t handle, ...)	Configures computation of the requested tensor network state marginal tensor.
marginal_prepare(intptr_t handle, ...)	Prepares computation of the requested tensor network state marginal tensor.
marginal_get_info(intptr_t handle, ...)	Retrieves an attribute related to computation of the requested tensor network state marginal tensor.
marginal_compute(intptr_t handle, ...)	Computes the requested tensor network state marginal tensor.
create_sampler(intptr_t handle, ...)	Creates a tensor network state sampler.
destroy_sampler(intptr_t tensor_network_sampler)	Destroys the tensor network state sampler.
get_sampler_attribute_dtype(int attr)	Get the Python data type of the corresponding SamplerAttribute attribute.
sampler_configure(intptr_t handle, ...)	Configures the tensor network state sampler.
sampler_prepare(intptr_t handle, ...)	Prepares the tensor network state sampler.
sampler_get_info(intptr_t handle, ...)	Retrieves an attribute related to tensor network state sampling.
sampler_sample(intptr_t handle, ...)	Performs sampling of the tensor network state, that is, generates the requested number of samples.
create_accessor(intptr_t handle, ...)	Creates a tensor network state amplitudes accessor.
destroy_accessor(...)	Destroyes the tensor network state amplitudes accessor.
get_accessor_attribute_dtype(int attr)	Get the Python data type of the corresponding AccessorAttribute attribute.
accessor_configure(intptr_t handle, ...)	Configures computation of the requested tensor network state amplitudes tensor.
accessor_prepare(intptr_t handle, ...)	Prepares computation of the requested tensor network state amplitudes tensor.
accessor_get_info(intptr_t handle, ...)	Retrieves an attribute related to computation of the requested tensor network state amplitudes tensor.
accessor_compute(intptr_t handle, ...)	Computes the amplitudes of the tensor network state.
create_expectation(intptr_t handle, ...)	Creates a representation of the tensor network state expectation value.
destroy_expectation(...)	Destroyes the tensor network state expectation value representation.
get_expectation_attribute_dtype(int attr)	Get the Python data type of the corresponding ExpectationAttribute attribute.
expectation_configure(intptr_t handle, ...)	Configures computation of the requested tensor network state expectation value.
expectation_prepare(intptr_t handle, ...)	Prepares computation of the requested tensor network state expectation value.
expectation_get_info(intptr_t handle, ...)	Retrieves an attribute related to computation of the requested tensor network state expectation value.
expectation_compute(intptr_t handle, ...)	Computes an (unnormalized) expectation value of a given tensor network operator over a given tensor network state.

Tensor network operator API

create_network_operator(intptr_t handle, ...)	Creates an uninitialized tensor network operator of a given shape defined by the number of state modes and their extents.
network_operator_append_product(...)	Appends a tensor product operator component to the tensor network operator.
network_operator_append_mpo(intptr_t handle, ...)	Appends a Matrix Product Operator (MPO) component to the tensor network operator.
destroy_network_operator(...)	Frees all resources owned by the tensor network operator.

Error management API

get_error_string(int error)

Returns the description string for an error code.

Logger API

logger_set_callback_data(callback, *args, ...)	Set the logger callback along with arguments.
logger_open_file(log_file)	This function opens a logging output file in the given path.
logger_set_level(int32_t level)	This function sets the value of the logging level.
logger_set_mask(int32_t mask)	This function sets the value of the log mask.
logger_force_disable()	This function disables logging for the entire run.
logger_set_file(intptr_t file)	This function sets the logging output file.

Versioning API

get_version()	Returns Version number of the cuTensorNet library.
get_cudart_version()	Returns version number of the CUDA runtime that cuTensorNet was compiled against.