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dcblundelldcblundell
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Replace ORM Querying and Marshmallow Serialization (#112)
# Description ## Removes ORM The use of SQLAlchemy's ORM framework (and its integration w/ Flask) isn't a fit for the way that we're operating on databases within the application. Rather than having a single database that hosts data for a single application we allow the user to dynamically swap the target database that they are using - because of this problems arise with the ORM's session/caching logic. This frees us up to implement SSH based querying, multi user environments and multi-tab environments but allowing the target database to be selected on a per-request basis. SQLAlchemy dependencies and configuration settings have been removed. ## New Queries/Dataclasses Queries have been moved to queries.py - these queries are optimized to perform as few reads on the file system as possible since performing complex joins against the SQLite database can result in thousands of file read operations which are considerably slower than filtering/joining/parsing the data programatically. ## New Serializers A new serializers.py file has been added that contains the logic of serialization the query results in the application. This replaces Marshmallow which integrated with the ORM to automagically serialize nested relationships of objects defined by the ORM. ## Minor Changes - Adds method to check for existence of tables to support backwards compatibility - Adds check against new table, captured_graph - Adds function name to timing functions. - Adds timing functions to other DB operations - Minor renaming - Adds 404 handlers for missing records - Adds handlers for missing database path - Changes database path to be on a per request basis (path is stubbed, dynamic path is next)
2 parents b886931 + b395399 commit 04bc513

11 files changed

Lines changed: 721 additions & 407 deletions

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‎backend/ttnn_visualizer/app.py‎

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@@ -70,7 +70,7 @@ def catch_all(path):
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def extensions(app: flask.Flask):
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from ttnn_visualizer.extensions import flask_static_digest, db, ma
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from ttnn_visualizer.extensions import flask_static_digest
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"""
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Register 0 or more extensions (mutates the app passed in).
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:return: None
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"""
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db.init_app(app)
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ma.init_app(app)
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flask_static_digest.init_app(app)
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# For automatically reflecting table data

‎backend/ttnn_visualizer/extensions.py‎

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@@ -1,18 +1,4 @@
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from flask_marshmallow import Marshmallow
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from flask_sqlalchemy import SQLAlchemy
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from flask_static_digest import FlaskStaticDigest
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class SQLiteAlchemy(SQLAlchemy):
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def apply_driver_hacks(self, app, info, options):
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options.update(
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{
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"isolation_level": "AUTOCOMMIT",
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}
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)
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super(SQLiteAlchemy, self).apply_driver_hacks(app, info, options)
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db = SQLiteAlchemy()
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flask_static_digest = FlaskStaticDigest()
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ma = Marshmallow()

‎backend/ttnn_visualizer/models.py‎

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Original file line numberDiff line numberDiff line change
@@ -1,181 +1,152 @@
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import dataclasses
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import enum
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import json
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from sqlalchemy import (
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Column,
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PrimaryKeyConstraint,
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Table,
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Integer,
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String,
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JSON,
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types,
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Text,
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Float,
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TypeDecorator,
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)
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from sqlalchemy.orm import relationship, Mapped, mapped_column
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from ttnn_visualizer.extensions import db
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operations = Table(
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"operations",
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db.metadata,
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Column("operation_id", Integer, primary_key=True),
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Column("name", String),
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Column("duration", Float),
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)
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# TODO Ask about PK for this table (UUID for instance)
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operation_arguments = Table(
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"operation_arguments",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column("name", Text),
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Column("value", Text),
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PrimaryKeyConstraint("operation_id", "value", "name"),
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)
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# TODO Ask about PK for this table (UUID for instance)
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input_tensors = Table(
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"input_tensors",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column("input_index", Integer),
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Column("tensor_id", db.ForeignKey("tensors.tensor_id")),
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PrimaryKeyConstraint("operation_id", "input_index", "tensor_id"),
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)
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tensors = Table(
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"tensors",
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db.metadata,
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Column("tensor_id", Integer, primary_key=True),
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Column("shape", Text),
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Column("dtype", Text),
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Column("layout", Text),
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Column("memory_config", Text),
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Column("device_id", Integer),
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Column("address", Integer),
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Column("buffer_type", Integer),
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)
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output_tensors = Table(
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"output_tensors",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column("output_index", Integer),
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Column("tensor_id", db.ForeignKey("tensors.tensor_id")),
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PrimaryKeyConstraint("operation_id", "output_index", "tensor_id"),
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)
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stack_traces = Table(
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"stack_traces",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column("stack_trace", Text),
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PrimaryKeyConstraint("operation_id", "stack_trace"),
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)
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buffers = Table(
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"buffers",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column("device_id", db.ForeignKey("devices.device_id")),
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Column("address", Integer),
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Column("max_size_per_bank", Integer),
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Column("buffer_type", Integer),
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PrimaryKeyConstraint("operation_id", "device_id", "address", "max_size_per_bank"),
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)
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devices = Table(
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"devices",
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db.metadata,
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Column("device_id", Integer, primary_key=True),
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Column("num_y_cores", Integer),
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Column("num_x_cores", Integer),
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Column("num_y_compute_cores", Integer),
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Column("num_x_compute_cores", Integer),
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Column("worker_l1_size", Integer),
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Column("l1_num_banks", Integer),
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Column("l1_bank_size", Integer),
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Column("address_at_first_l1_bank", Integer),
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Column("address_at_first_l1_cb_buffer", Integer),
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Column("num_banks_per_storage_core", Integer),
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Column("num_compute_cores", Integer),
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Column("num_storage_cores", Integer),
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Column("total_l1_memory", Integer),
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Column("total_l1_for_tensors", Integer),
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Column("total_l1_for_interleaved_buffers", Integer),
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Column("total_l1_for_sharded_buffers", Integer),
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Column("cb_limit", Integer),
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)
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device_operations = Table(
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"captured_graph",
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db.metadata,
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Column("operation_id", db.ForeignKey("operations.operation_id")),
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Column(
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"captured_graph",
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Text,
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),
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PrimaryKeyConstraint("operation_id", "captured_graph"),
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)
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class Device(db.Model):
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__table__ = devices
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class Tensor(db.Model):
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__table__ = tensors
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input_tensors = relationship("InputTensor", back_populates="tensor", lazy="joined")
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output_tensors = relationship(
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"OutputTensor", back_populates="tensor", lazy="joined"
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)
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@property
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def producers(self):
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return [i.operation_id for i in self.output_tensors]
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@property
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def consumers(self):
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return [i.operation_id for i in self.input_tensors]
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class Buffer(db.Model):
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__table__ = buffers
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device = relationship("Device")
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class InputTensor(db.Model):
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__table__ = input_tensors
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tensor = db.relationship(
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"Tensor", back_populates="input_tensors", innerjoin=True, lazy="joined"
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)
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class StackTrace(db.Model):
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__table__ = stack_traces
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class OutputTensor(db.Model):
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__table__ = output_tensors
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tensor = db.relationship(
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"Tensor", back_populates="output_tensors", innerjoin=True, lazy="joined"
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)
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class Operation(db.Model):
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__table__ = operations
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arguments = db.relationship("OperationArgument", lazy="joined")
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inputs = db.relationship("InputTensor", lazy="joined")
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outputs = db.relationship("OutputTensor", lazy="joined")
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stack_trace = db.relationship("StackTrace", lazy="joined")
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buffers = db.relationship("Buffer")
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device_operations = db.relationship("DeviceOperation", uselist=False, lazy="joined")
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175-
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class OperationArgument(db.Model):
177-
__table__ = operation_arguments
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class DeviceOperation(db.Model):
181-
__table__ = device_operations
4+
from json import JSONDecodeError
5+
6+
7+
class BufferType(enum.Enum):
8+
DRAM = 0
9+
L1 = 1
10+
SYSTEM_MEMORY = 2
11+
L1_SMALL = 3
12+
TRACE = 4
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15+
@dataclasses.dataclass
16+
class Operation:
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operation_id: int
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name: str
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duration: float
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21+
22+
@dataclasses.dataclass
23+
class Device:
24+
device_id: int
25+
num_y_cores: int
26+
num_x_cores: int
27+
num_y_compute_cores: int
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num_x_compute_cores: int
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worker_l1_size: int
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l1_num_banks: int
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l1_bank_size: int
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address_at_first_l1_bank: int
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address_at_first_l1_cb_buffer: int
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num_banks_per_storage_core: int
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num_compute_cores: int
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num_storage_cores: int
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total_l1_memory: int
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total_l1_for_tensors: int
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total_l1_for_interleaved_buffers: int
40+
total_l1_for_sharded_buffers: int
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cb_limit: int
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43+
44+
@dataclasses.dataclass
45+
class DeviceOperation:
46+
operation_id: int
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captured_graph: str
48+
49+
def __post_init__(self):
50+
try:
51+
captured_graph = json.loads(self.captured_graph)
52+
for graph in captured_graph:
53+
id = graph.pop("counter")
54+
graph.update({"id": id})
55+
56+
self.captured_graph = captured_graph
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except JSONDecodeError:
59+
self.captured_graph = []
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61+
62+
@dataclasses.dataclass
63+
class Buffer:
64+
operation_id: int
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device_id: int
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address: int
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max_size_per_bank: int
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buffer_type: BufferType
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70+
def __post_init__(self):
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self.buffer_type = (
72+
BufferType(self.buffer_type).value if self.buffer_type is not None else None
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)
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75+
76+
@dataclasses.dataclass
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class BufferPage:
78+
operation_id: int
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device_id: int
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address: int
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core_y: int
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core_x: int
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bank_id: int
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page_index: int
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page_address: int
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page_size: int
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buffer_type: BufferType
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def __post_init__(self):
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self.buffer_type = (
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BufferType(self.buffer_type).value if self.buffer_type is not None else None
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)
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94+
95+
@dataclasses.dataclass
96+
class ProducersConsumers:
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tensor_id: int
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producers: list[int]
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consumers: list[int]
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101+
102+
@dataclasses.dataclass
103+
class Tensor:
104+
tensor_id: int
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shape: str
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dtype: str
107+
layout: str
108+
memory_config: str
109+
device_id: int
110+
address: int
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buffer_type: BufferType
112+
113+
def __post_init__(self):
114+
self.buffer_type = (
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BufferType(self.buffer_type).value if self.buffer_type is not None else None
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)
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118+
119+
@dataclasses.dataclass
120+
class InputTensor:
121+
operation_id: int
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input_index: int
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tensor_id: int
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125+
126+
@dataclasses.dataclass
127+
class OutputTensor:
128+
operation_id: int
129+
output_index: int
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tensor_id: int
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@dataclasses.dataclass
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class TensorComparisonRecord:
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tensor_id: int
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golden_tensor_id: int
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matches: bool
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desired_pcc: bool
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actual_pcc: float
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141+
142+
@dataclasses.dataclass
143+
class OperationArgument:
144+
operation_id: int
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name: str
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value: str
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148+
149+
@dataclasses.dataclass
150+
class StackTrace:
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operation_id: int
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stack_trace: str

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