mindspore

Tensor

mindspore.Tensor

Tensor is a data structure that stores an n-dimensional array.

mindspore.COOTensor

A sparse representation of a set of nonzero elements from a tensor at given indices.

mindspore.CSRTensor

Constructs a sparse tensor in CSR (Compressed Sparse Row) format, with specified values indicated by values and row and column positions indicated by indptr and indices.

mindspore.RowTensor

A sparse representation of a set of tensor slices at given indices.

mindspore.SparseTensor

A sparse representation of a set of nonzero elements from a tensor at given indices.

Parameter

mindspore.Parameter

Parameter is a Tensor subclass, when they are assigned as Cell attributes they are automatically added to the list of its parameters, and will appear e.g.

mindspore.ParameterTuple

Inherited from tuple, ParameterTuple is used to save multiple parameter.

DataType

class mindspore.dtype

Create a data type object of MindSpore.

The actual path of dtype is /mindspore/common/dtype.py. Run the following command to import the package:

from mindspore import dtype as mstype
  • Numeric Type

    Currently, MindSpore supports Int type, Uint type, Float type and Complex type. The following table lists the details.

    Definition

    Description

    mindspore.int8 , mindspore.byte

    8-bit integer

    mindspore.int16 , mindspore.short

    16-bit integer

    mindspore.int32 , mindspore.intc

    32-bit integer

    mindspore.int64 , mindspore.intp

    64-bit integer

    mindspore.uint8 , mindspore.ubyte

    unsigned 8-bit integer

    mindspore.uint16 , mindspore.ushort

    unsigned 16-bit integer

    mindspore.uint32 , mindspore.uintc

    unsigned 32-bit integer

    mindspore.uint64 , mindspore.uintp

    unsigned 64-bit integer

    mindspore.float16 , mindspore.half

    16-bit floating-point number

    mindspore.float32 , mindspore.single

    32-bit floating-point number

    mindspore.float64 , mindspore.double

    64-bit floating-point number

    mindspore.complex64

    64-bit complex number

    mindspore.complex128

    128-bit complex number

  • Other Type

    For other defined types, see the following table.

    Type

    Description

    tensor

    MindSpore’s tensor type. Data format uses NCHW. For details, see tensor.

    bool_

    Boolean True or False.

    int_

    Integer scalar.

    uint

    Unsigned integer scalar.

    float_

    Floating-point scalar.

    complex

    Complex scalar.

    number

    Number, including int_ , uint , float_ , complex and bool_ .

    list_

    List constructed by tensor , such as List[T0,T1,...,Tn] , where the element Ti can be of different types.

    tuple_

    Tuple constructed by tensor , such as Tuple[T0,T1,...,Tn] , where the element Ti can be of different types.

    function

    Function. Return in two ways, when function is not None, returns Func directly, the other returns Func(args: List[T0,T1,…,Tn], retval: T) when function is None.

    type_type

    Type definition of type.

    type_none

    No matching return type, corresponding to the type(None) in Python.

    symbolic_key

    The value of a variable is used as a key of the variable in env_type .

    env_type

    Used to store the gradient of the free variable of a function, where the key is the symbolic_key of the free variable’s node and the value is the gradient.

  • Tree Topology

    The relationships of the above types are as follows:

    └─────── number
        │   ├─── bool_
        │   ├─── int_
        │   │   ├─── int8, byte
        │   │   ├─── int16, short
        │   │   ├─── int32, intc
        │   │   └─── int64, intp
        │   ├─── uint
        │   │   ├─── uint8, ubyte
        │   │   ├─── uint16, ushort
        │   │   ├─── uint32, uintc
        │   │   └─── uint64, uintp
        │   ├─── float_
        │   │   ├─── float16
        │   │   ├─── float32
        │   │   └─── float64
        │   └─── complex
        │       ├─── complex64
        │       └─── complex128
        ├─── tensor
        │   ├─── Array[Float32]
        │   └─── ...
        ├─── list_
        │   ├─── List[Int32,Float32]
        │   └─── ...
        ├─── tuple_
        │   ├─── Tuple[Int32,Float32]
        │   └─── ...
        ├─── function
        │   ├─── Func
        │   ├─── Func[(Int32, Float32), Int32]
        │   └─── ...
        ├─── type_type
        ├─── type_none
        ├─── symbolic_key
        └─── env_type
    

mindspore.dtype_to_nptype

Convert MindSpore dtype to numpy data type.

mindspore.issubclass_

Determine whether type_ is a subclass of dtype.

mindspore.dtype_to_pytype

Convert MindSpore dtype to python data type.

mindspore.pytype_to_dtype

Convert python type to MindSpore type.

mindspore.get_py_obj_dtype

Get the MindSpore data type, which corresponds to python type or variable.

Seed

mindspore.set_seed

Set global seed.

mindspore.get_seed

Get global seed.

Model

mindspore.Model

High-Level API for training or inference.

Dataset Helper

mindspore.DatasetHelper

DatasetHelper is a class to process the MindData dataset and provides the information of dataset.

mindspore.connect_network_with_dataset

Connect the network with dataset in dataset_helper.

Loss Scale Manager

mindspore.LossScaleManager

Loss scale (Magnification factor of gradients when mix precision is used) manager abstract class when using mixed precision.

mindspore.FixedLossScaleManager

Loss scale(Magnification factor of gradients when mix precision is used) manager with a fixed loss scale value, inherits from mindspore.LossScaleManager.

mindspore.DynamicLossScaleManager

Loss scale(Magnification factor of gradients when mix precision is used) manager with loss scale dynamically adjusted, inherits from mindspore.LossScaleManager.

Serialization

mindspore.save_checkpoint

Save checkpoint to a specified file.

mindspore.load_checkpoint

Load checkpoint info from a specified file.

mindspore.load_param_into_net

Load parameters into network, return parameter list that are not loaded in the network.

mindspore.export

Export the MindSpore network into an offline model in the specified format.

mindspore.load

Load MindIR.

mindspore.parse_print

Parse data file generated by mindspore.ops.Print.

mindspore.build_searched_strategy

Build strategy of every parameter in network.

mindspore.merge_sliced_parameter

Merge parameter slices into one parameter.

mindspore.load_distributed_checkpoint

Load checkpoint into net for distributed predication.

mindspore.async_ckpt_thread_status

Get the status of asynchronous save checkpoint thread.

mindspore.restore_group_info_list

Build rank list, the checkpoint of ranks in the rank list has the same contents with the local rank who saves the group_info_file_name.

JIT

mindspore.ms_function

Create a callable MindSpore graph from a Python function.

mindspore.ms_class

Class decorator for user-defined classes.

Log

mindspore.get_level

Get the logger level.

mindspore.get_log_config

Get logger configurations.

Automatic Mixed Precision

mindspore.build_train_network

Build the mixed precision training cell automatically.

Installation Verification

mindspore.run_check

Provide a convenient API to check if the installation is successful or failed.

Debugging

mindspore.set_dump

Enable or disable dump for the target and its contents.