API reference¶

Core¶

class tensorstore.TensorStore

Asynchronous multi-dimensional array handle.

class tensorstore.Context

Manages shared TensorStore context resources, such as caches and credentials.

class tensorstore.KvStore

Key-value store that maps an ordered set of byte string keys to byte string values.

class tensorstore.Transaction

Transactions are used to stage a group of modifications (e.g. writes to tensorstore.TensorStore objects) in memory, and then either commit the group all at once or abort it.

class tensorstore.Batch

Batches are used to group together read operations for potentially improved efficiency.

tensorstore.open(spec: Spec | Any, *, ...) → Future[TensorStore]

Opens or creates a TensorStore from a Spec.

Indexing¶

tensorstore.inf : int = 4611686018427387903

Special constant equal to \(2^{62}-1\) that indicates an unbounded index domain.

class tensorstore.IndexDomain

Domain (including bounds and optional dimension labels) of an N-dimensional index space.

class tensorstore.IndexTransform

Represents a transform from an input index space to an output space.

class tensorstore.Dim

1-d index interval with optionally-implicit bounds and dimension label.

class tensorstore.OutputIndexMap

Represents an output index map for an index transform.

class tensorstore.OutputIndexMaps

View of the output index maps for an index transform.

class tensorstore.OutputIndexMethod

Indicates the output index method of an OutputIndexMap.

class tensorstore.DimExpression

Specifies an advanced indexing operation.

class tensorstore.DimSelection(DimExpression)

Specifies a dimension selection, for starting a dimension expression.

static tensorstore.d[selection: DimSelectionLike] → DimSelection

Constructs a DimSelection from a sequence of dimension indices, ranges, and/or labels.

tensorstore.newaxis = None

Alias for None used in indexing expressions to specify a new singleton dimension.

class tensorstore.Indexable

Abstract base class for types that support TensorStore indexing operations.

tensorstore.NumpyIndexTerm

Individual term in a NumpyIndexingSpec.

tensorstore.NumpyIndexingSpec

NumPy-style indexing expression.

tensorstore.DimSelectionLike

Subsequence of dimensions to select in a DimSelection object.

Spec¶

class tensorstore.Spec

Specification for opening or creating a TensorStore.

class tensorstore.Schema

Driver-independent options for defining a TensorStore schema.

class tensorstore.CodecSpec

Specifies driver-specific encoding/decoding parameters.

class tensorstore.OpenMode

Specifies the mode to use when opening a TensorStore.

class tensorstore.ChunkLayout

Describes the storage layout of a tensorstore.TensorStore.

class tensorstore.Unit

Specifies a physical quantity/unit.

tensorstore.RecheckCacheOption

Determines under what circumstances cached data is revalidated.

Views¶

tensorstore.DownsampleMethod

Downsampling method for use by the downsample driver.

tensorstore.cast(base: TensorStore, dtype: DTypeLike) → TensorStore

Returns a read/write view with the data type converted.

tensorstore.cast(base: Spec, dtype: DTypeLike) → Spec

Returns a view with the data type converted.

tensorstore.array(array: ArrayLike, ...) → TensorStore

Returns a TensorStore that reads/writes from an in-memory array.

tensorstore.overlay(layers, ...) → TensorStore

Virtually overlays a sequence of TensorStore layers within a common domain.

tensorstore.stack(layers, ...) → TensorStore

Virtually stacks a sequence of TensorStore layers along a new dimension.

tensorstore.concat(layers, ...) → TensorStore

Virtually concatenates a sequence of TensorStore layers along an existing dimension.

tensorstore.downsample(base: TensorStore, ...) → TensorStore

Returns a virtual downsampled view of a TensorStore.

tensorstore.downsample(base: Spec, downsample_factors, ...) → Spec

Returns a virtual downsampled view view of a Spec.

Virtual views¶

class tensorstore.VirtualChunkedReadParameters

Options passed to read callbacks used with virtual_chunked.

class tensorstore.VirtualChunkedWriteParameters

Options passed to write callbacks used with virtual_chunked.

tensorstore.virtual_chunked(...) → TensorStore

Creates a TensorStore where the content is read/written chunk-wise by an arbitrary function.

Data types¶

class tensorstore.dtype

TensorStore data type representation.

tensorstore.bool : dtype = dtype("bool")

Boolean data type (0 or 1). Corresponds to the bool type and numpy.bool_.

tensorstore.char : dtype = dtype("char")

Single byte, interpreted as an ASCII character.

tensorstore.byte : dtype = dtype("byte")

Single byte.

tensorstore.int2 : dtype = dtype("int2")

2-bit signed two’s-complement integer data type, internally stored as its 8-bit signed integer equivalent (i.e. sign-extended). Corresponds to jax.numpy.int2.

tensorstore.int4 : dtype = dtype("int4")

4-bit signed two’s-complement integer data type, internally stored as its 8-bit signed integer equivalent (i.e. sign-extended). Corresponds to jax.numpy.int4.

tensorstore.int8 : dtype = dtype("int8")

8-bit signed two’s-complement integer data type. Corresponds to numpy.int8.

tensorstore.uint8 : dtype = dtype("uint8")

8-bit unsigned integer. Corresponds to numpy.uint8.

tensorstore.int16 : dtype = dtype("int16")

16-bit signed two’s-complement integer data type. Corresponds to numpy.int16.

tensorstore.uint16 : dtype = dtype("uint16")

16-bit unsigned integer. Corresponds to numpy.uint16.

tensorstore.int32 : dtype = dtype("int32")

32-bit signed two’s-complement integer data type. Corresponds to numpy.int32.

tensorstore.uint32 : dtype = dtype("uint32")

32-bit unsigned integer. Corresponds to numpy.uint32.

tensorstore.int64 : dtype = dtype("int64")

32-bit signed two’s-complement integer data type. Corresponds to numpy.int64.

tensorstore.uint64 : dtype = dtype("uint64")

64-bit unsigned integer data type. Corresponds to numpy.uint64.

tensorstore.float8_e3m4 : dtype = dtype("float8_e3m4")