Source code for bittensor.synapse

# The MIT License (MIT)
# Copyright © 2021 Yuma Rao
# Copyright © 2022 Opentensor Foundation

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import base64
import json
import sys
import warnings

from pydantic import (
    BaseModel,
    ConfigDict,
    Field,
    field_validator,
    model_validator,
)
import bittensor
from typing import Optional, Any, Dict, ClassVar, Tuple


[docs] def get_size(obj, seen=None) -> int: """ Recursively finds size of objects. This function traverses every item of a given object and sums their sizes to compute the total size. Args: obj (any type): The object to get the size of. seen (set): Set of object ids that have been calculated. Returns: int: The total size of the object. """ size = sys.getsizeof(obj) if seen is None: seen = set() obj_id = id(obj) if obj_id in seen: return 0 # Important mark as seen *before* entering recursion to gracefully handle # self-referential objects seen.add(obj_id) if isinstance(obj, dict): size += sum([get_size(v, seen) for v in obj.values()]) size += sum([get_size(k, seen) for k in obj.keys()]) elif hasattr(obj, "__dict__"): size += get_size(obj.__dict__, seen) elif hasattr(obj, "__iter__") and not isinstance(obj, (str, bytes, bytearray)): size += sum([get_size(i, seen) for i in obj]) return size
[docs] def cast_int(raw: str) -> int: """ Converts a string to an integer, if the string is not ``None``. This function attempts to convert a string to an integer. If the string is ``None``, it simply returns ``None``. Args: raw (str): The string to convert. Returns: int or None: The converted integer, or ``None`` if the input was ``None``. """ return int(raw) if raw is not None else raw # type: ignore
[docs] def cast_float(raw: str) -> float: """ Converts a string to a float, if the string is not ``None``. This function attempts to convert a string to a float. If the string is ``None``, it simply returns ``None``. Args: raw (str): The string to convert. Returns: float or None: The converted float, or ``None`` if the input was ``None``. """ return float(raw) if raw is not None else raw # type: ignore
[docs] class TerminalInfo(BaseModel): """ TerminalInfo encapsulates detailed information about a network synapse (node) involved in a communication process. This class serves as a metadata carrier, providing essential details about the state and configuration of a terminal during network interactions. This is a crucial class in the Bittensor framework. The TerminalInfo class contains information such as HTTP status codes and messages, processing times, IP addresses, ports, Bittensor version numbers, and unique identifiers. These details are vital for maintaining network reliability, security, and efficient data flow within the Bittensor network. This class includes Pydantic validators and root validators to enforce data integrity and format. It is designed to be used natively within Synapses, so that you will not need to call this directly, but rather is used as a helper class for Synapses. Args: status_code (int): HTTP status code indicating the result of a network request. Essential for identifying the outcome of network interactions. status_message (str): Descriptive message associated with the status code, providing additional context about the request's result. process_time (float): Time taken by the terminal to process the call, important for performance monitoring and optimization. ip (str): IP address of the terminal, crucial for network routing and data transmission. port (int): Network port used by the terminal, key for establishing network connections. version (int): Bittensor version running on the terminal, ensuring compatibility between different nodes in the network. nonce (int): Unique, monotonically increasing number for each terminal, aiding in identifying and ordering network interactions. uuid (str): Unique identifier for the terminal, fundamental for network security and identification. hotkey (str): Encoded hotkey string of the terminal wallet, important for transaction and identity verification in the network. signature (str): Digital signature verifying the tuple of nonce, axon_hotkey, dendrite_hotkey, and uuid, critical for ensuring data authenticity and security. Usage:: # Creating a TerminalInfo instance terminal_info = TerminalInfo( status_code=200, status_message="Success", process_time=0.1, ip="198.123.23.1", port=9282, version=111, nonce=111111, uuid="5ecbd69c-1cec-11ee-b0dc-e29ce36fec1a", hotkey="5EnjDGNqqWnuL2HCAdxeEtN2oqtXZw6BMBe936Kfy2PFz1J1", signature="0x0813029319030129u4120u10841824y0182u091u230912u" ) # Accessing TerminalInfo attributes ip_address = terminal_info.ip processing_duration = terminal_info.process_time # TerminalInfo can be used to monitor and verify network interactions, ensuring proper communication and security within the Bittensor network. TerminalInfo plays a pivotal role in providing transparency and control over network operations, making it an indispensable tool for developers and users interacting with the Bittensor ecosystem. """ model_config = ConfigDict(validate_assignment=True) # The HTTP status code from: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status status_code: Optional[int] = Field( title="status_code", description="The HTTP status code from: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status", examples=[200], default=None, frozen=False, ) # The HTTP status code from: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status status_message: Optional[str] = Field( title="status_message", description="The status_message associated with the status_code", examples=["Success"], default=None, frozen=False, ) # Process time on this terminal side of call process_time: Optional[float] = Field( title="process_time", description="Process time on this terminal side of call", examples=[0.1], default=None, frozen=False, ) # The terminal ip. ip: Optional[str] = Field( title="ip", description="The ip of the axon receiving the request.", examples=["198.123.23.1"], default=None, frozen=False, ) # The host port of the terminal. port: Optional[int] = Field( title="port", description="The port of the terminal.", examples=["9282"], default=None, frozen=False, ) # The bittensor version on the terminal as an int. version: Optional[int] = Field( title="version", description="The bittensor version on the axon as str(int)", examples=[111], default=None, frozen=False, ) # A Unix timestamp to associate with the terminal nonce: Optional[int] = Field( title="nonce", description="A Unix timestamp that prevents replay attacks", examples=[111111], default=None, frozen=False, ) # A unique identifier associated with the terminal, set on the axon side. uuid: Optional[str] = Field( title="uuid", description="A unique identifier associated with the terminal", examples=["5ecbd69c-1cec-11ee-b0dc-e29ce36fec1a"], default=None, frozen=False, ) # The bittensor version on the terminal as an int. hotkey: Optional[str] = Field( title="hotkey", description="The ss58 encoded hotkey string of the terminal wallet.", examples=["5EnjDGNqqWnuL2HCAdxeEtN2oqtXZw6BMBe936Kfy2PFz1J1"], default=None, frozen=False, ) # A signature verifying the tuple (axon_nonce, axon_hotkey, dendrite_hotkey, axon_uuid) signature: Optional[str] = Field( title="signature", description="A signature verifying the tuple (nonce, axon_hotkey, dendrite_hotkey, uuid)", examples=["0x0813029319030129u4120u10841824y0182u091u230912u"], default=None, frozen=False, ) # Extract the process time on this terminal side of call as a float _extract_process_time = field_validator("process_time", mode="before")(cast_float) # Extract the host port of the terminal as an int _extract_port = field_validator("port", mode="before")(cast_int) # Extract the bittensor version on the terminal as an int. _extract_version = field_validator("version", mode="before")(cast_int) # Extract the Unix timestamp associated with the terminal as an int _extract_nonce = field_validator("nonce", mode="before")(cast_int) # Extract the HTTP status code as an int _extract_status_code = field_validator("status_code", mode="before")(cast_int)
[docs] class Synapse(BaseModel): """ Represents a Synapse in the Bittensor network, serving as a communication schema between neurons (nodes). Synapses ensure the format and correctness of transmission tensors according to the Bittensor protocol. Each Synapse type is tailored for a specific machine learning (ML) task, following unique compression and communication processes. This helps maintain sanitized, correct, and useful information flow across the network. The Synapse class encompasses essential network properties such as HTTP route names, timeouts, request sizes, and terminal information. It also includes methods for serialization, deserialization, attribute setting, and hash computation, ensuring secure and efficient data exchange in the network. The class includes Pydantic validators and root validators to enforce data integrity and format. Additionally, properties like ``is_success``, ``is_failure``, ``is_timeout``, etc., provide convenient status checks based on dendrite responses. Think of Bittensor Synapses as glorified pydantic wrappers that have been designed to be used in a distributed network. They provide a standardized way to communicate between neurons, and are the primary mechanism for communication between neurons in Bittensor. Key Features: 1. HTTP Route Name (``name`` attribute): Enables the identification and proper routing of requests within the network. Essential for users defining custom routes for specific machine learning tasks. 2. Query Timeout (``timeout`` attribute): Determines the maximum duration allowed for a query, ensuring timely responses and network efficiency. Crucial for users to manage network latency and response times, particularly in time-sensitive applications. 3. Request Sizes (``total_size``, ``header_size`` attributes): Keeps track of the size of request bodies and headers, ensuring efficient data transmission without overloading the network. Important for users to monitor and optimize the data payload, especially in bandwidth-constrained environments. 4. Terminal Information (``dendrite``, ``axon`` attributes): Stores information about the dendrite (receiving end) and axon (sending end), facilitating communication between nodes. Users can access detailed information about the communication endpoints, aiding in debugging and network analysis. 5. Body Hash Computation (``computed_body_hash``, ``required_hash_fields``): Ensures data integrity and security by computing hashes of transmitted data. Provides users with a mechanism to verify data integrity and detect any tampering during transmission. It is recommended that names of fields in `required_hash_fields` are listed in the order they are defined in the class. 6. Serialization and Deserialization Methods: Facilitates the conversion of Synapse objects to and from a format suitable for network transmission. Essential for users who need to customize data formats for specific machine learning models or tasks. 7. Status Check Properties (``is_success``, ``is_failure``, ``is_timeout``, etc.): Provides quick and easy methods to check the status of a request, improving error handling and response management. Users can efficiently handle different outcomes of network requests, enhancing the robustness of their applications. Example usage:: # Creating a Synapse instance with default values synapse = Synapse() # Setting properties and input synapse.timeout = 15.0 synapse.name = "MySynapse" # Not setting fields that are not defined in your synapse class will result in an error, e.g.: synapse.dummy_input = 1 # This will raise an error because dummy_input is not defined in the Synapse class # Get a dictionary of headers and body from the synapse instance synapse_dict = synapse.model_dump_json() # Get a dictionary of headers from the synapse instance headers = synapse.to_headers() # Reconstruct the synapse from headers using the classmethod 'from_headers' synapse = Synapse.from_headers(headers) # Deserialize synapse after receiving it over the network, controlled by `deserialize` method deserialized_synapse = synapse.deserialize() # Checking the status of the request if synapse.is_success: print("Request succeeded") # Checking and setting the status of the request print(synapse.axon.status_code) synapse.axon.status_code = 408 # Timeout Args: name (str): HTTP route name, set on :func:`axon.attach`. timeout (float): Total query length, set by the dendrite terminal. total_size (int): Total size of request body in bytes. header_size (int): Size of request header in bytes. dendrite (TerminalInfo): Information about the dendrite terminal. axon (TerminalInfo): Information about the axon terminal. computed_body_hash (str): Computed hash of the request body. required_hash_fields (List[str]): Fields required to compute the body hash. Methods: deserialize: Custom deserialization logic for subclasses. __setattr__: Override method to make ``required_hash_fields`` read-only. get_total_size: Calculates and returns the total size of the object. to_headers: Constructs a dictionary of headers from instance properties. body_hash: Computes a SHA3-256 hash of the serialized body. parse_headers_to_inputs: Parses headers to construct an inputs dictionary. from_headers: Creates an instance from a headers dictionary. This class is a cornerstone in the Bittensor framework, providing the necessary tools for secure, efficient, and standardized communication in a decentralized environment. """ model_config = ConfigDict(validate_assignment=True) _model_json_schema: ClassVar[Dict[str, Any]]
[docs] def deserialize(self) -> "Synapse": """ Deserializes the Synapse object. This method is intended to be overridden by subclasses for custom deserialization logic. In the context of the Synapse superclass, this method simply returns the instance itself. When inheriting from this class, subclasses should provide their own implementation for deserialization if specific deserialization behavior is desired. By default, if a subclass does not provide its own implementation of this method, the Synapse's deserialize method will be used, returning the object instance as-is. In its default form, this method simply returns the instance of the Synapse itself without any modifications. Subclasses of Synapse can override this method to add specific deserialization behaviors, such as converting serialized data back into complex object types or performing additional data integrity checks. Example:: class CustomSynapse(Synapse): additional_data: str def deserialize(self) -> "CustomSynapse": # Custom deserialization logic # For example, decoding a base64 encoded string in 'additional_data' if self.additional_data: self.additional_data = base64.b64decode(self.additional_data).decode('utf-8') return self serialized_data = '{"additional_data": "SGVsbG8gV29ybGQ="}' # Base64 for 'Hello World' custom_synapse = CustomSynapse.model_validate_json(serialized_data) deserialized_synapse = custom_synapse.deserialize() # deserialized_synapse.additional_data would now be 'Hello World' Returns: Synapse: The deserialized Synapse object. In this default implementation, it returns the object itself. """ return self
[docs] @model_validator(mode="before") def set_name_type(cls, values) -> dict: values["name"] = cls.__name__ # type: ignore return values
# Defines the http route name which is set on axon.attach( callable( request: RequestName )) name: Optional[str] = Field( title="name", description="Defines the http route name which is set on axon.attach( callable( request: RequestName ))", examples=["Forward"], frozen=False, default=None, repr=False, ) # The call timeout, set by the dendrite terminal. timeout: Optional[float] = Field( title="timeout", description="Defines the total query length.", examples=[12.0], default=12.0, frozen=False, repr=False, ) # The call timeout, set by the dendrite terminal. total_size: Optional[int] = Field( title="total_size", description="Total size of request body in bytes.", examples=[1000], default=0, frozen=False, repr=False, ) # The call timeout, set by the dendrite terminal. header_size: Optional[int] = Field( title="header_size", description="Size of request header in bytes.", examples=[1000], default=0, frozen=False, repr=False, ) # The dendrite Terminal Information. dendrite: Optional[TerminalInfo] = Field( title="dendrite", description="Dendrite Terminal Information", examples=["bittensor.TerminalInfo"], default=TerminalInfo(), frozen=False, repr=False, ) # A axon terminal information axon: Optional[TerminalInfo] = Field( title="axon", description="Axon Terminal Information", examples=["bittensor.TerminalInfo"], default=TerminalInfo(), frozen=False, repr=False, ) computed_body_hash: Optional[str] = Field( title="computed_body_hash", description="The computed body hash of the request.", examples=["0x0813029319030129u4120u10841824y0182u091u230912u"], default="", frozen=True, repr=False, ) required_hash_fields: ClassVar[Tuple[str, ...]] = () _extract_total_size = field_validator("total_size", mode="before")(cast_int) _extract_header_size = field_validator("header_size", mode="before")(cast_int) _extract_timeout = field_validator("timeout", mode="before")(cast_float)
[docs] def __setattr__(self, name: str, value: Any): """ Override the :func:`__setattr__` method to make the ``required_hash_fields`` property read-only. This is a security mechanism such that the ``required_hash_fields`` property cannot be overridden by the user or malicious code. """ if name == "body_hash": raise AttributeError( "body_hash property is read-only and cannot be overridden." ) super().__setattr__(name, value)
[docs] def get_total_size(self) -> int: """ Get the total size of the current object. This method first calculates the size of the current object, then assigns it to the instance variable :func:`self.total_size` and finally returns this value. Returns: int: The total size of the current object. """ self.total_size = get_size(self) return self.total_size
@property def is_success(self) -> bool: """ Checks if the dendrite's status code indicates success. This method returns ``True`` if the status code of the dendrite is ``200``, which typically represents a successful HTTP request. Returns: bool: ``True`` if dendrite's status code is ``200``, ``False`` otherwise. """ return self.dendrite is not None and self.dendrite.status_code == 200 @property def is_failure(self) -> bool: """ Checks if the dendrite's status code indicates failure. This method returns ``True`` if the status code of the dendrite is not ``200``, which would mean the HTTP request was not successful. Returns: bool: ``True`` if dendrite's status code is not ``200``, ``False`` otherwise. """ return self.dendrite is not None and self.dendrite.status_code != 200 @property def is_timeout(self) -> bool: """ Checks if the dendrite's status code indicates a timeout. This method returns ``True`` if the status code of the dendrite is ``408``, which is the HTTP status code for a request timeout. Returns: bool: ``True`` if dendrite's status code is ``408``, ``False`` otherwise. """ return self.dendrite is not None and self.dendrite.status_code == 408 @property def is_blacklist(self) -> bool: """ Checks if the dendrite's status code indicates a blacklisted request. This method returns ``True`` if the status code of the dendrite is ``403``, which is the HTTP status code for a forbidden request. Returns: bool: ``True`` if dendrite's status code is ``403``, ``False`` otherwise. """ return self.dendrite is not None and self.dendrite.status_code == 403 @property def failed_verification(self) -> bool: """ Checks if the dendrite's status code indicates failed verification. This method returns ``True`` if the status code of the dendrite is ``401``, which is the HTTP status code for unauthorized access. Returns: bool: ``True`` if dendrite's status code is ``401``, ``False`` otherwise. """ return self.dendrite is not None and self.dendrite.status_code == 401
[docs] @classmethod def _get_cached_model_json_schema(cls) -> dict: """ Returns the JSON schema for the Synapse model. This method returns a cached version of the JSON schema for the Synapse model. The schema is stored in the class variable ``_model_json_schema`` and is only generated once to improve performance. Returns: dict: The JSON schema for the Synapse model. """ if "_model_json_schema" not in cls.__dict__: cls._model_json_schema = cls.model_json_schema() return cls._model_json_schema
[docs] def get_required_fields(self): """ Get the required fields from the model's JSON schema. """ schema = self._get_cached_model_json_schema() return schema.get("required", [])
[docs] def to_headers(self) -> dict: """ Converts the state of a Synapse instance into a dictionary of HTTP headers. This method is essential for packaging Synapse data for network transmission in the Bittensor framework, ensuring that each key aspect of the Synapse is represented in a format suitable for HTTP communication. Process: 1. Basic Information: It starts by including the ``name`` and ``timeout`` of the Synapse, which are fundamental for identifying the query and managing its lifespan on the network. 2. Complex Objects: The method serializes the ``axon`` and ``dendrite`` objects, if present, into strings. This serialization is crucial for preserving the state and structure of these objects over the network. 3. Encoding: Non-optional complex objects are serialized and encoded in base64, making them safe for HTTP transport. 4. Size Metrics: The method calculates and adds the size of headers and the total object size, providing valuable information for network bandwidth management. Example Usage:: synapse = Synapse(name="ExampleSynapse", timeout=30) headers = synapse.to_headers() # headers now contains a dictionary representing the Synapse instance Returns: dict: A dictionary containing key-value pairs representing the Synapse's properties, suitable for HTTP communication. """ # Initializing headers with 'name' and 'timeout' headers = {"name": self.name, "timeout": str(self.timeout)} # Adding headers for 'axon' and 'dendrite' if they are not None if self.axon: headers.update( { f"bt_header_axon_{k}": str(v) for k, v in self.axon.model_dump().items() if v is not None } ) if self.dendrite: headers.update( { f"bt_header_dendrite_{k}": str(v) for k, v in self.dendrite.model_dump().items() if v is not None } ) # Getting the fields of the instance instance_fields = self.model_dump() required = set(self.get_required_fields()) # Iterating over the fields of the instance for field, value in instance_fields.items(): # If the object is not optional, serializing it, encoding it, and adding it to the headers # Skipping the field if it's already in the headers or its value is None if field in headers or value is None: continue elif field in required: try: # create an empty (dummy) instance of type(value) to pass pydantic validation on the axon side serialized_value = json.dumps(value.__class__.__call__()) encoded_value = base64.b64encode(serialized_value.encode()).decode( "utf-8" ) headers[f"bt_header_input_obj_{field}"] = encoded_value except TypeError as e: raise ValueError( f"Error serializing {field} with value {value}. Objects must be json serializable." ) from e # Adding the size of the headers and the total size to the headers headers["header_size"] = str(sys.getsizeof(headers)) headers["total_size"] = str(self.get_total_size()) headers["computed_body_hash"] = self.body_hash return headers
@property def body_hash(self) -> str: """ Computes a SHA3-256 hash of the serialized body of the Synapse instance. This hash is used to ensure the data integrity and security of the Synapse instance when it's transmitted across the network. It is a crucial feature for verifying that the data received is the same as the data sent. Process: 1. Iterates over each required field as specified in ``required_hash_fields``. 2. Concatenates the string representation of these fields. 3. Applies SHA3-256 hashing to the concatenated string to produce a unique fingerprint of the data. Example:: synapse = Synapse(name="ExampleRoute", timeout=10) hash_value = synapse.body_hash # hash_value is the SHA3-256 hash of the serialized body of the Synapse instance Returns: str: The SHA3-256 hash as a hexadecimal string, providing a fingerprint of the Synapse instance's data for integrity checks. """ hashes = [] hash_fields_field = self.model_fields.get("required_hash_fields") instance_fields = None if hash_fields_field: warnings.warn( "The 'required_hash_fields' field handling deprecated and will be removed. " "Please update Synapse class definition to use 'required_hash_fields' class variable instead.", DeprecationWarning, ) required_hash_fields = hash_fields_field.default if required_hash_fields: instance_fields = self.model_dump() # Preserve backward compatibility in which fields will added in .model_dump() order # instead of the order one from `self.required_hash_fields` required_hash_fields = [ field for field in instance_fields if field in required_hash_fields ] # Hack to cache the required hash fields names if len(required_hash_fields) == len(required_hash_fields): self.__class__.required_hash_fields = tuple(required_hash_fields) else: required_hash_fields = self.__class__.required_hash_fields if required_hash_fields: instance_fields = instance_fields or self.model_dump() for field in required_hash_fields: hashes.append(bittensor.utils.hash(str(instance_fields[field]))) return bittensor.utils.hash("".join(hashes))
[docs] @classmethod def parse_headers_to_inputs(cls, headers: dict) -> dict: """ Interprets and transforms a given dictionary of headers into a structured dictionary, facilitating the reconstruction of Synapse objects. This method is essential for parsing network-transmitted data back into a Synapse instance, ensuring data consistency and integrity. Process: 1. Separates headers into categories based on prefixes (``axon``, ``dendrite``, etc.). 2. Decodes and deserializes ``input_obj`` headers into their original objects. 3. Assigns simple fields directly from the headers to the input dictionary. Example:: received_headers = { 'bt_header_axon_address': '127.0.0.1', 'bt_header_dendrite_port': '8080', # Other headers... } inputs = Synapse.parse_headers_to_inputs(received_headers) # inputs now contains a structured representation of Synapse properties based on the headers Note: This is handled automatically when calling :func:`Synapse.from_headers(headers)` and does not need to be called directly. Args: headers (dict): The headers dictionary to parse. Returns: dict: A structured dictionary representing the inputs for constructing a Synapse instance. """ # Initialize the input dictionary with empty sub-dictionaries for 'axon' and 'dendrite' inputs_dict: Dict[str, Dict[str, str]] = {"axon": {}, "dendrite": {}} # Iterate over each item in the headers for key, value in headers.items(): # Handle 'axon' headers if "bt_header_axon_" in key: try: new_key = key.split("bt_header_axon_")[1] inputs_dict["axon"][new_key] = value except Exception as e: bittensor.logging.error( f"Error while parsing 'axon' header {key}: {e}" ) continue # Handle 'dendrite' headers elif "bt_header_dendrite_" in key: try: new_key = key.split("bt_header_dendrite_")[1] inputs_dict["dendrite"][new_key] = value except Exception as e: bittensor.logging.error( f"Error while parsing 'dendrite' header {key}: {e}" ) continue # Handle 'input_obj' headers elif "bt_header_input_obj" in key: try: new_key = key.split("bt_header_input_obj_")[1] # Skip if the key already exists in the dictionary if new_key in inputs_dict: continue # Decode and load the serialized object inputs_dict[new_key] = json.loads( base64.b64decode(value.encode()).decode("utf-8") ) except json.JSONDecodeError as e: bittensor.logging.error( f"Error while json decoding 'input_obj' header {key}: {e}" ) continue except Exception as e: bittensor.logging.error( f"Error while parsing 'input_obj' header {key}: {e}" ) continue else: pass # TODO: log unexpected keys # Assign the remaining known headers directly inputs_dict["timeout"] = headers.get("timeout", None) inputs_dict["name"] = headers.get("name", None) inputs_dict["header_size"] = headers.get("header_size", None) inputs_dict["total_size"] = headers.get("total_size", None) inputs_dict["computed_body_hash"] = headers.get("computed_body_hash", None) return inputs_dict
[docs] @classmethod def from_headers(cls, headers: dict) -> "Synapse": """ Constructs a new Synapse instance from a given headers dictionary, enabling the re-creation of the Synapse's state as it was prior to network transmission. This method is a key part of the deserialization process in the Bittensor network, allowing nodes to accurately reconstruct Synapse objects from received data. Example:: received_headers = { 'bt_header_axon_address': '127.0.0.1', 'bt_header_dendrite_port': '8080', # Other headers... } synapse = Synapse.from_headers(received_headers) # synapse is a new Synapse instance reconstructed from the received headers Args: headers (dict): The dictionary of headers containing serialized Synapse information. Returns: Synapse: A new instance of Synapse, reconstructed from the parsed header information, replicating the original instance's state. """ # Get the inputs dictionary from the headers input_dict = cls.parse_headers_to_inputs(headers) # Use the dictionary unpacking operator to pass the inputs to the class constructor synapse = cls(**input_dict) return synapse