MindSpore
Design
Functional Differential Programming
Distributed Training Design
MindSpore IR (MindIR)
Second Order Optimizer
Design of Visualization↗
Glossary
Specification
Benchmarks
Network List↗
API List
Syntax Support
API
mindspore
Tensor
mindspore.Tensor
Neural Network Layer Methods
Tensor Operation Methods
Parameter Operation Methods
Other Methods
mindspore.COOTensor
mindspore.CSRTensor
mindspore.RowTensor
mindspore.SparseTensor
Parameter
DataType
Seed
Context
Model
Callback
Dataset Helper
Serialization
JIT
Log
Installation Verification
Debugging and Tuning
Memory Recycle
Thor
mindspore.amp
mindspore.common.initializer
mindspore.communication
mindspore.dataset
mindspore.dataset.audio
mindspore.dataset.config
mindspore.dataset.text
mindspore.dataset.transforms
mindspore.dataset.vision
mindspore.mindrecord
mindspore.nn
mindspore.nn.probability
mindspore.nn.transformer
mindspore.numpy
mindspore.ops
mindspore.ops.function
mindspore.rewrite
mindspore.scipy
mindspore.boost
C++ API↗
API Mapping
PyTorch and MindSpore API Mapping Table
TensorFlow and MindSpore API Mapping Table
Migration Guide
Overview
Environment Preparation and Information Acquisition
Model Analysis and Preparation
Constructing MindSpore Network
Debugging and Tuning
Network Migration Debugging Example
FAQs
Differences Between MindSpore and PyTorch
Using Third-party Operator Libraries Based on Customized Interfaces
FAQ
Installation
Data Processing
Implement Problem
Network Compilation
Operators Compile
Migration from a Third-party Framework
Performance Tuning
Precision Tuning
Distributed Configuration
Inference
Feature Advice
RELEASE NOTES
Release Notes
MindSpore
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mindspore
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mindspore.Tensor
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mindspore.Tensor.T
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mindspore.Tensor.T
property
Tensor.
T
Return the transposed tensor.