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
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 »
mindspore.Tensor »
mindspore.Tensor.has_init
View page source

mindspore.Tensor.has_init

property Tensor.has_init: Whether tensor is initialized.

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