path: root/python-bittensor.spec

%global _empty_manifest_terminate_build 0
Name:		python-bittensor
Version:	4.0.1
Release:	1
Summary:	bittensor
License:	MIT
URL:		https://github.com/opentensor/bittensor
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b2/b7/edd639c895875c16cc864ebc383a7c660fc849cb7bb0551c89b252ac1398/bittensor-4.0.1.tar.gz
BuildArch:	noarch

Requires:	python3-ansible-vault
Requires:	python3-argparse
Requires:	python3-backoff
Requires:	python3-base58
Requires:	python3-certifi
Requires:	python3-cryptography
Requires:	python3-fuzzywuzzy
Requires:	python3-google-api-python-client
Requires:	python3-grpcio-tools
Requires:	python3-grpcio
Requires:	python3-hypothesis
Requires:	python3-idna
Requires:	python3-jinja2
Requires:	python3-jsonschema[format-nongpl]
Requires:	python3-loguru
Requires:	python3-markupsafe
Requires:	python3-miniupnpc
Requires:	python3-msgpack-numpy
Requires:	python3-msgpack
Requires:	python3-munch
Requires:	python3-nest-asyncio
Requires:	python3-netaddr
Requires:	python3-numpy
Requires:	python3-pandas
Requires:	python3-password-strength
Requires:	python3-prometheus-client
Requires:	python3-protobuf
Requires:	python3-psutil
Requires:	python3-py-bip39-bindings
Requires:	python3-py-ed25519-bindings
Requires:	python3-py-sr25519-bindings
Requires:	python3-pycryptodome
Requires:	python3-levenshtein
Requires:	python3-pyyaml
Requires:	python3-qqdm
Requires:	python3-requests
Requires:	python3-retry
Requires:	python3-rich
Requires:	python3-scalecodec
Requires:	python3-sentencepiece
Requires:	python3-substrate-interface
Requires:	python3-termcolor
Requires:	python3-torch
Requires:	python3-tqdm
Requires:	python3-transformers
Requires:	python3-wandb
Requires:	python3-wheel
Requires:	python3-coveralls
Requires:	python3-ddt
Requires:	python3-pytest-cov
Requires:	python3-pytest-rerunfailures
Requires:	python3-pytest-split
Requires:	python3-pytest-xdist
Requires:	python3-pytest

%description
### Internet-scale Neural Networks <!-- omit in toc -->
[Discord](https://discord.gg/bittensor) • [Docs](https://docs.bittensor.com/) • [Network](https://www.bittensor.com/network) • [Research](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU) • [Code](https://github.com/opentensor/BitTensor)
</div>
This repository contains Bittensor's Python API, which can be used for the following purposes:
1. Querying the Bittensor network as a [client](https://github.com/opentensor/bittensor#31-client).
2. Running and building Bittensor miners and validators for [mining TAO](https://github.com/opentensor/bittensor#43-running-a-template-miner).
3. Pulling network [state information](https://github.com/opentensor/bittensor#3-using-bittensor).
4. Managing [TAO wallets](https://github.com/opentensor/bittensor#41-cli), balances, transfers, etc.
Bittensor is a mining network, similar to Bitcoin, that includes built-in incentives designed to encourage miners to provide value by hosting trained or training machine learning models. These models can be queried by clients seeking inference over inputs, such as token-based text generations or numerical embeddings from a large foundation model like GPT-NeoX-20B.
Token-based incentives are designed to drive the network's growth and distribute the value generated by the network directly to the individuals producing that value, without intermediaries. The network is open to all participants, and no individual or group has full control over what is learned, who can profit from it, or who can access it.
To learn more about Bittensor, please read our [paper](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU/view).
- [1. Documentation](#1-documentation)
- [2. Install](#2-install)
- [3. Using Bittensor](#3-using-bittensor)
  - [3.1. Client](#31-client)
  - [3.2. Server](#32-server)
  - [3.3. Validator](#33-validator)
- [4. Features](#4-features)
  - [4.1. Using the CLI](#41-cli)
  - [4.2. Selecting the network to join](#42-selecting-the-network-to-join)
  - [4.3. Running a template miner](#43-running-a-template-miner)
  - [4.4. Running a template server](#44-running-a-template-server)
  - [4.5. Syncing with the chain/ Finding the ranks/stake/uids of other nodes](#46-syncing-with-the-chain-finding-the-ranksstakeuids-of-other-nodes)
  - [4.6. Finding and creating the endpoints for other nodes in the network](#47-finding-and-creating-the-endpoints-for-other-nodes-in-the-network)
  - [4.7. Querying others in the network](#48-querying-others-in-the-network)
- [5. Release](#5-release)
- [6. License](#6-license)
- [7. Acknowledgments](#7-acknowledgments)
## 1. Documentation
https://docs.bittensor.com/
## 2. Install
Three ways to install Bittensor
1. Through the installer:
```
$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/opentensor/bittensor/master/scripts/install.sh)"
```
2. With pip:
```bash
$ pip3 install bittensor
```
3. From source:
```
$ git clone https://github.com/opentensor/bittensor.git
$ python3 -m pip install -e bittensor/
```
## 3. Using Bittensor
The following examples showcase how to use the Bittensor API for 3 separate purposes.
### 3.1. Client 
Querying the network for generations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).generate
        ( 
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            prompt = "The quick brown fox jumped over the lazy dog", 
            num_to_generate = 20
        )
)
```
Querying the network for representations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).text_last_hidden_state
        (
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            inputs = "The quick brown fox jumped over the lazy dog"
        )
)
// Apply model. 
loss.backward() // Accumulate gradients on endpoints.
```
### 3.2. Server
Serving a custom model.
```python
import bittensor
import torch
from transformers import GPT2Model, GPT2Config
model = GPT2Model( GPT2Config(vocab_size = bittensor.__vocab_size__, n_embd = bittensor.__network_dim__ , n_head = 8))
optimizer = torch.optim.SGD( [ {"params": model.parameters()} ], lr = 0.01 )
def forward_text( pubkey, inputs_x ):
    return model( inputs_x )
def backward_text( pubkey, inputs_x, grads_dy ):
    with torch.enable_grad():
        outputs_y = model( inputs_x.to(device) ).last_hidden_state
        torch.autograd.backward (
            tensors = [ outputs_y.to(device) ],
            grad_tensors = [ grads_dy.to(device) ]
        )
        optimizer.step()
        optimizer.zero_grad() 
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 3.3. Validator 
Validating models by setting weights.
```python
import bittensor
import torch
graph = bittensor.metagraph().sync()
dataset = bittensor.dataset()
chain_weights = torch.ones( [graph.n.item()], dtype = torch.float32 )
for batch in dataset.dataloader( 10 ):
    // Train chain_weights.
bittensor.subtensor().set_weights (
    weights = chain_weights,
    uids = graph.uids,
    wait_for_inclusion = True,
    wallet = bittensor.wallet(),
)
```
## 4. Features
### 4.1. CLI
Creating a new wallet.
```bash
$ btcli new_coldkey
$ btcli new_hotkey
```
Listing your wallets
```bash
$ btcli list
```
Registering a wallet
```bash
$ btcli register
```
Running a miner
```bash
$ btcli run
```
Checking balances
```bash
$ btcli overview
```
Checking the incentive mechanism.
```bash
$ btcli metagraph
```
Transfering funds
```bash
$ btcli transfer
```
Staking/Unstaking from a hotkey
```bash
$ btcli stake
$ btcli unstake
```
### 4.2. Selecting the network to join 
There are two open Bittensor networks: staging (Nobunaga) and main (Nakamoto, Local).
- Nobunaga (staging)
- Nakamoto (main)
- Local (localhost, mirrors nakamoto)
```bash
$ export NETWORK=local 
$ python (..) --subtensor.network $NETWORK
or
>> btcli run --subtensor.network $NETWORK
```
### 4.3. Running a template miner
The following command will run Bittensor's template miner
```bash
$ cd bittensor
$ python ./bittensor/_neuron/text/template_miner/main.py
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.template_miner.neuron().run()
```
OR with customized settings
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/template_miner/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
For the full list of settings, please run
```bash
$ python3 ~/.bittensor/bittensor/bittensor/_neuron/neurons/text/template_miner/main.py --help
```
### 4.4. Running a template server
The template server follows a similar structure as the template miner. 
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.core_server.neuron().run()
```
For the full list of settings, please run
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --help
```
###  4.5. Serving an endpoint on the network
Endpoints are served to the bittensor network through the axon. The axon is instantiated via a wallet which holds an account on the Bittensor network.
```python
import bittensor
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 4.6. Syncing with the chain/ Finding the ranks/stake/uids of other nodes
Information from the chain is collected/formated by the metagraph.
```bash
btcli metagraph
```
and
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
# --- uid ---
print(meta.uids)
# --- hotkeys ---
print(meta.hotkeys)
# --- ranks ---
print(meta.R)
# --- stake ---
print(meta.S)
```
### 4.7. Finding and creating the endpoints for other nodes in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_as_tensor = meta.endpoints[0]
endpoint_as_object = meta.endpoint_objs[0]
```
### 4.8. Querying others in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_0 = meta.endpoints[0]
### Creating the wallet, and dendrite
wallet = bittensor.wallet().create().register()
den = bittensor.dendrite(wallet = wallet)
representations, _, _ = den.forward_text (
    endpoints = endpoint_0,
    inputs = "Hello World"
)
```
## 5. Release
The release manager should follow the instructions of the [RELEASE_GUIDELINES.md](./RELEASE_GUIDELINES.md) document.
## 6. License
The MIT License (MIT)
Copyright © 2021 Yuma Rao
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
## 7. Acknowledgments
**learning-at-home/hivemind**

%package -n python3-bittensor
Summary:	bittensor
Provides:	python-bittensor
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-bittensor
### Internet-scale Neural Networks <!-- omit in toc -->
[Discord](https://discord.gg/bittensor) • [Docs](https://docs.bittensor.com/) • [Network](https://www.bittensor.com/network) • [Research](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU) • [Code](https://github.com/opentensor/BitTensor)
</div>
This repository contains Bittensor's Python API, which can be used for the following purposes:
1. Querying the Bittensor network as a [client](https://github.com/opentensor/bittensor#31-client).
2. Running and building Bittensor miners and validators for [mining TAO](https://github.com/opentensor/bittensor#43-running-a-template-miner).
3. Pulling network [state information](https://github.com/opentensor/bittensor#3-using-bittensor).
4. Managing [TAO wallets](https://github.com/opentensor/bittensor#41-cli), balances, transfers, etc.
Bittensor is a mining network, similar to Bitcoin, that includes built-in incentives designed to encourage miners to provide value by hosting trained or training machine learning models. These models can be queried by clients seeking inference over inputs, such as token-based text generations or numerical embeddings from a large foundation model like GPT-NeoX-20B.
Token-based incentives are designed to drive the network's growth and distribute the value generated by the network directly to the individuals producing that value, without intermediaries. The network is open to all participants, and no individual or group has full control over what is learned, who can profit from it, or who can access it.
To learn more about Bittensor, please read our [paper](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU/view).
- [1. Documentation](#1-documentation)
- [2. Install](#2-install)
- [3. Using Bittensor](#3-using-bittensor)
  - [3.1. Client](#31-client)
  - [3.2. Server](#32-server)
  - [3.3. Validator](#33-validator)
- [4. Features](#4-features)
  - [4.1. Using the CLI](#41-cli)
  - [4.2. Selecting the network to join](#42-selecting-the-network-to-join)
  - [4.3. Running a template miner](#43-running-a-template-miner)
  - [4.4. Running a template server](#44-running-a-template-server)
  - [4.5. Syncing with the chain/ Finding the ranks/stake/uids of other nodes](#46-syncing-with-the-chain-finding-the-ranksstakeuids-of-other-nodes)
  - [4.6. Finding and creating the endpoints for other nodes in the network](#47-finding-and-creating-the-endpoints-for-other-nodes-in-the-network)
  - [4.7. Querying others in the network](#48-querying-others-in-the-network)
- [5. Release](#5-release)
- [6. License](#6-license)
- [7. Acknowledgments](#7-acknowledgments)
## 1. Documentation
https://docs.bittensor.com/
## 2. Install
Three ways to install Bittensor
1. Through the installer:
```
$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/opentensor/bittensor/master/scripts/install.sh)"
```
2. With pip:
```bash
$ pip3 install bittensor
```
3. From source:
```
$ git clone https://github.com/opentensor/bittensor.git
$ python3 -m pip install -e bittensor/
```
## 3. Using Bittensor
The following examples showcase how to use the Bittensor API for 3 separate purposes.
### 3.1. Client 
Querying the network for generations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).generate
        ( 
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            prompt = "The quick brown fox jumped over the lazy dog", 
            num_to_generate = 20
        )
)
```
Querying the network for representations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).text_last_hidden_state
        (
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            inputs = "The quick brown fox jumped over the lazy dog"
        )
)
// Apply model. 
loss.backward() // Accumulate gradients on endpoints.
```
### 3.2. Server
Serving a custom model.
```python
import bittensor
import torch
from transformers import GPT2Model, GPT2Config
model = GPT2Model( GPT2Config(vocab_size = bittensor.__vocab_size__, n_embd = bittensor.__network_dim__ , n_head = 8))
optimizer = torch.optim.SGD( [ {"params": model.parameters()} ], lr = 0.01 )
def forward_text( pubkey, inputs_x ):
    return model( inputs_x )
def backward_text( pubkey, inputs_x, grads_dy ):
    with torch.enable_grad():
        outputs_y = model( inputs_x.to(device) ).last_hidden_state
        torch.autograd.backward (
            tensors = [ outputs_y.to(device) ],
            grad_tensors = [ grads_dy.to(device) ]
        )
        optimizer.step()
        optimizer.zero_grad() 
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 3.3. Validator 
Validating models by setting weights.
```python
import bittensor
import torch
graph = bittensor.metagraph().sync()
dataset = bittensor.dataset()
chain_weights = torch.ones( [graph.n.item()], dtype = torch.float32 )
for batch in dataset.dataloader( 10 ):
    // Train chain_weights.
bittensor.subtensor().set_weights (
    weights = chain_weights,
    uids = graph.uids,
    wait_for_inclusion = True,
    wallet = bittensor.wallet(),
)
```
## 4. Features
### 4.1. CLI
Creating a new wallet.
```bash
$ btcli new_coldkey
$ btcli new_hotkey
```
Listing your wallets
```bash
$ btcli list
```
Registering a wallet
```bash
$ btcli register
```
Running a miner
```bash
$ btcli run
```
Checking balances
```bash
$ btcli overview
```
Checking the incentive mechanism.
```bash
$ btcli metagraph
```
Transfering funds
```bash
$ btcli transfer
```
Staking/Unstaking from a hotkey
```bash
$ btcli stake
$ btcli unstake
```
### 4.2. Selecting the network to join 
There are two open Bittensor networks: staging (Nobunaga) and main (Nakamoto, Local).
- Nobunaga (staging)
- Nakamoto (main)
- Local (localhost, mirrors nakamoto)
```bash
$ export NETWORK=local 
$ python (..) --subtensor.network $NETWORK
or
>> btcli run --subtensor.network $NETWORK
```
### 4.3. Running a template miner
The following command will run Bittensor's template miner
```bash
$ cd bittensor
$ python ./bittensor/_neuron/text/template_miner/main.py
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.template_miner.neuron().run()
```
OR with customized settings
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/template_miner/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
For the full list of settings, please run
```bash
$ python3 ~/.bittensor/bittensor/bittensor/_neuron/neurons/text/template_miner/main.py --help
```
### 4.4. Running a template server
The template server follows a similar structure as the template miner. 
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.core_server.neuron().run()
```
For the full list of settings, please run
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --help
```
###  4.5. Serving an endpoint on the network
Endpoints are served to the bittensor network through the axon. The axon is instantiated via a wallet which holds an account on the Bittensor network.
```python
import bittensor
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 4.6. Syncing with the chain/ Finding the ranks/stake/uids of other nodes
Information from the chain is collected/formated by the metagraph.
```bash
btcli metagraph
```
and
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
# --- uid ---
print(meta.uids)
# --- hotkeys ---
print(meta.hotkeys)
# --- ranks ---
print(meta.R)
# --- stake ---
print(meta.S)
```
### 4.7. Finding and creating the endpoints for other nodes in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_as_tensor = meta.endpoints[0]
endpoint_as_object = meta.endpoint_objs[0]
```
### 4.8. Querying others in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_0 = meta.endpoints[0]
### Creating the wallet, and dendrite
wallet = bittensor.wallet().create().register()
den = bittensor.dendrite(wallet = wallet)
representations, _, _ = den.forward_text (
    endpoints = endpoint_0,
    inputs = "Hello World"
)
```
## 5. Release
The release manager should follow the instructions of the [RELEASE_GUIDELINES.md](./RELEASE_GUIDELINES.md) document.
## 6. License
The MIT License (MIT)
Copyright © 2021 Yuma Rao
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
## 7. Acknowledgments
**learning-at-home/hivemind**

%package help
Summary:	Development documents and examples for bittensor
Provides:	python3-bittensor-doc
%description help
### Internet-scale Neural Networks <!-- omit in toc -->
[Discord](https://discord.gg/bittensor) • [Docs](https://docs.bittensor.com/) • [Network](https://www.bittensor.com/network) • [Research](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU) • [Code](https://github.com/opentensor/BitTensor)
</div>
This repository contains Bittensor's Python API, which can be used for the following purposes:
1. Querying the Bittensor network as a [client](https://github.com/opentensor/bittensor#31-client).
2. Running and building Bittensor miners and validators for [mining TAO](https://github.com/opentensor/bittensor#43-running-a-template-miner).
3. Pulling network [state information](https://github.com/opentensor/bittensor#3-using-bittensor).
4. Managing [TAO wallets](https://github.com/opentensor/bittensor#41-cli), balances, transfers, etc.
Bittensor is a mining network, similar to Bitcoin, that includes built-in incentives designed to encourage miners to provide value by hosting trained or training machine learning models. These models can be queried by clients seeking inference over inputs, such as token-based text generations or numerical embeddings from a large foundation model like GPT-NeoX-20B.
Token-based incentives are designed to drive the network's growth and distribute the value generated by the network directly to the individuals producing that value, without intermediaries. The network is open to all participants, and no individual or group has full control over what is learned, who can profit from it, or who can access it.
To learn more about Bittensor, please read our [paper](https://drive.google.com/file/d/1VnsobL6lIAAqcA1_Tbm8AYIQscfJV4KU/view).
- [1. Documentation](#1-documentation)
- [2. Install](#2-install)
- [3. Using Bittensor](#3-using-bittensor)
  - [3.1. Client](#31-client)
  - [3.2. Server](#32-server)
  - [3.3. Validator](#33-validator)
- [4. Features](#4-features)
  - [4.1. Using the CLI](#41-cli)
  - [4.2. Selecting the network to join](#42-selecting-the-network-to-join)
  - [4.3. Running a template miner](#43-running-a-template-miner)
  - [4.4. Running a template server](#44-running-a-template-server)
  - [4.5. Syncing with the chain/ Finding the ranks/stake/uids of other nodes](#46-syncing-with-the-chain-finding-the-ranksstakeuids-of-other-nodes)
  - [4.6. Finding and creating the endpoints for other nodes in the network](#47-finding-and-creating-the-endpoints-for-other-nodes-in-the-network)
  - [4.7. Querying others in the network](#48-querying-others-in-the-network)
- [5. Release](#5-release)
- [6. License](#6-license)
- [7. Acknowledgments](#7-acknowledgments)
## 1. Documentation
https://docs.bittensor.com/
## 2. Install
Three ways to install Bittensor
1. Through the installer:
```
$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/opentensor/bittensor/master/scripts/install.sh)"
```
2. With pip:
```bash
$ pip3 install bittensor
```
3. From source:
```
$ git clone https://github.com/opentensor/bittensor.git
$ python3 -m pip install -e bittensor/
```
## 3. Using Bittensor
The following examples showcase how to use the Bittensor API for 3 separate purposes.
### 3.1. Client 
Querying the network for generations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).generate
        ( 
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            prompt = "The quick brown fox jumped over the lazy dog", 
            num_to_generate = 20
        )
)
```
Querying the network for representations.
```python
import bittensor
wallet = bittensor.wallet().create_if_non_existent()
graph = bittensor.metagraph().sync()
print ( bittensor.dendrite( wallet = wallet ).text_last_hidden_state
        (
            endpoints = graph.endpoints[graph.incentive.sort()[1][-1]],  // The highest ranked peer.
            inputs = "The quick brown fox jumped over the lazy dog"
        )
)
// Apply model. 
loss.backward() // Accumulate gradients on endpoints.
```
### 3.2. Server
Serving a custom model.
```python
import bittensor
import torch
from transformers import GPT2Model, GPT2Config
model = GPT2Model( GPT2Config(vocab_size = bittensor.__vocab_size__, n_embd = bittensor.__network_dim__ , n_head = 8))
optimizer = torch.optim.SGD( [ {"params": model.parameters()} ], lr = 0.01 )
def forward_text( pubkey, inputs_x ):
    return model( inputs_x )
def backward_text( pubkey, inputs_x, grads_dy ):
    with torch.enable_grad():
        outputs_y = model( inputs_x.to(device) ).last_hidden_state
        torch.autograd.backward (
            tensors = [ outputs_y.to(device) ],
            grad_tensors = [ grads_dy.to(device) ]
        )
        optimizer.step()
        optimizer.zero_grad() 
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 3.3. Validator 
Validating models by setting weights.
```python
import bittensor
import torch
graph = bittensor.metagraph().sync()
dataset = bittensor.dataset()
chain_weights = torch.ones( [graph.n.item()], dtype = torch.float32 )
for batch in dataset.dataloader( 10 ):
    // Train chain_weights.
bittensor.subtensor().set_weights (
    weights = chain_weights,
    uids = graph.uids,
    wait_for_inclusion = True,
    wallet = bittensor.wallet(),
)
```
## 4. Features
### 4.1. CLI
Creating a new wallet.
```bash
$ btcli new_coldkey
$ btcli new_hotkey
```
Listing your wallets
```bash
$ btcli list
```
Registering a wallet
```bash
$ btcli register
```
Running a miner
```bash
$ btcli run
```
Checking balances
```bash
$ btcli overview
```
Checking the incentive mechanism.
```bash
$ btcli metagraph
```
Transfering funds
```bash
$ btcli transfer
```
Staking/Unstaking from a hotkey
```bash
$ btcli stake
$ btcli unstake
```
### 4.2. Selecting the network to join 
There are two open Bittensor networks: staging (Nobunaga) and main (Nakamoto, Local).
- Nobunaga (staging)
- Nakamoto (main)
- Local (localhost, mirrors nakamoto)
```bash
$ export NETWORK=local 
$ python (..) --subtensor.network $NETWORK
or
>> btcli run --subtensor.network $NETWORK
```
### 4.3. Running a template miner
The following command will run Bittensor's template miner
```bash
$ cd bittensor
$ python ./bittensor/_neuron/text/template_miner/main.py
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.template_miner.neuron().run()
```
OR with customized settings
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/template_miner/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
For the full list of settings, please run
```bash
$ python3 ~/.bittensor/bittensor/bittensor/_neuron/neurons/text/template_miner/main.py --help
```
### 4.4. Running a template server
The template server follows a similar structure as the template miner. 
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --wallet.name <WALLET NAME> --wallet.hotkey <HOTKEY NAME>
```
or 
```python3
>> import bittensor
>> bittensor.neurons.text.core_server.neuron().run()
```
For the full list of settings, please run
```bash
$ cd bittensor
$ python3 ./bittensor/_neuron/text/core_server/main.py --help
```
###  4.5. Serving an endpoint on the network
Endpoints are served to the bittensor network through the axon. The axon is instantiated via a wallet which holds an account on the Bittensor network.
```python
import bittensor
wallet = bittensor.wallet().create().register()
axon = bittensor.axon (
    wallet = wallet,
    forward_text = forward_text,
    backward_text = backward_text
).start().serve()
```
### 4.6. Syncing with the chain/ Finding the ranks/stake/uids of other nodes
Information from the chain is collected/formated by the metagraph.
```bash
btcli metagraph
```
and
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
# --- uid ---
print(meta.uids)
# --- hotkeys ---
print(meta.hotkeys)
# --- ranks ---
print(meta.R)
# --- stake ---
print(meta.S)
```
### 4.7. Finding and creating the endpoints for other nodes in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_as_tensor = meta.endpoints[0]
endpoint_as_object = meta.endpoint_objs[0]
```
### 4.8. Querying others in the network
```python
import bittensor
meta = bittensor.metagraph()
meta.sync()
### Address for the node uid 0
endpoint_0 = meta.endpoints[0]
### Creating the wallet, and dendrite
wallet = bittensor.wallet().create().register()
den = bittensor.dendrite(wallet = wallet)
representations, _, _ = den.forward_text (
    endpoints = endpoint_0,
    inputs = "Hello World"
)
```
## 5. Release
The release manager should follow the instructions of the [RELEASE_GUIDELINES.md](./RELEASE_GUIDELINES.md) document.
## 6. License
The MIT License (MIT)
Copyright © 2021 Yuma Rao
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
## 7. Acknowledgments
**learning-at-home/hivemind**

%prep
%autosetup -n bittensor-4.0.1

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
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fi
if [ -d usr/bin ]; then
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fi
if [ -d usr/sbin ]; then
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fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-bittensor -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 4.0.1-1
- Package Spec generated