Merge pull request #33 from Vivswan/master

v1.0.6

.flake8

@@ -2,17 +2,36 @@
 max-line-length = 120
 
 extend-ignore =
-    C101, # Coding magic comment
-    D100, # Missing docstring in public module
-    D104, # Missing docstring in public package
-    D202, # No blank lines allowed after function docstring
-    D210, # No whitespaces allowed surrounding docstring text
-    D401, # First line should be in imperative mood
-    R504, # unnecessary variable assignment before return statement
-    R505, # unnecessary else after return statement
+    # No explicit stacklevel argument found
+    B028,
+
+    # Coding magic comment
+    C101,
+
+    # Missing docstring in public module
+    D100,
+
+    # Missing docstring in public package
+    D104,
+
+    # No blank lines allowed after function docstring
+    D202,
+
+    # No whitespaces allowed surrounding docstring text
+    D210,
+
+    # First line should be in imperative mood
+    D401,
+
+    # unnecessary variable assignment before return statement
+    R504,
+
+    # unnecessary else after return statement
+    R505,
 
 per-file-ignores =
     sample_code.py: D100, D101, D102, D103, D104
+    sample_code_non_analog.py: D100, D101, D102, D103, D104
     sample_code_with_logs.py: D100, D101, D102, D103, D104
 
 exclude =

.gitignore

@@ -226,3 +226,4 @@ fabric.properties
 
 # Android studio 3.1+ serialized cache file
 .idea/caches/build_file_checksums.ser
+.pdm-python

CHANGELOG.md

@@ -1,15 +1,21 @@
 # Changelog
 
+## 1.0.6
+
+* `Model` is subclass of `BackwardModule` for additional functionality.
+* Using `inspect.isclass` to check if `backward_class` is a class in `Linear.set_backward_function`.
+* Repr using `self.__class__.__name__` in all classes.
+
 ## 1.0.5 (Patches for Pytorch 2.0.1)
 
 * Removed unnecessary `PseudoParameter.grad` property.
 * Patch for Pytorch 2.0.1, add filtering inputs in `BackwardGraph._calculate_gradients`.
 
 ## 1.0.4
 
-* Combined `PseudoParameter` and `PseudoParameterModule` for better visibility
-  * BugFix: fixed save and load of state_dict of `PseudoParameter` and transformation module
-* Removed redundant class `analogvnn.parameter.Parameter`
+* Combined `PseudoParameter` and `PseudoParameterModule` for better visibility.
+  * BugFix: fixed save and load of state_dict of `PseudoParameter` and transformation module.
+* Removed redundant class `analogvnn.parameter.Parameter`.
 
 ## 1.0.3
 

README.md

@@ -1,11 +1,11 @@
 # AnalogVNN
 
 [![arXiv](https://img.shields.io/badge/arXiv-2210.10048-orange.svg)](https://arxiv.org/abs/2210.10048)
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb)
 
 [![PyPI version](https://badge.fury.io/py/analogvnn.svg)](https://badge.fury.io/py/analogvnn)
 [![Documentation Status](https://readthedocs.org/projects/analogvnn/badge/?version=stable)](https://analogvnn.readthedocs.io/en/stable/?badge=stable)
-[![Python](https://img.shields.io/badge/python-3.7--3.10-blue)](https://badge.fury.io/py/analogvnn)
+[![Python](https://img.shields.io/badge/python-3.7--3.11-blue)](https://badge.fury.io/py/analogvnn)
 [![License: MPL 2.0](https://img.shields.io/badge/License-MPL_2.0-blue.svg)](https://opensource.org/licenses/MPL-2.0)
 
 Documentation: [https://analogvnn.readthedocs.io/](https://analogvnn.readthedocs.io/)
@@ -16,15 +16,29 @@ Documentation: [https://analogvnn.readthedocs.io/](https://analogvnn.readthedocs
 - Install AnalogVNN using [pip](https://pypi.org/project/analogvnn/)
 
 ```bash
-pip install analogvnn
+  # Current stable release for CPU and GPU
+  pip install analogvnn
+
+  # For additional optional features
+  pip install analogvnn[full]
 ```
 
-![3 Layered Linear Photonic Analog Neural Network](docs/_static/analogvnn_model.png)
+## Usage:
 
-[//]: # (![3 Layered Linear Photonic Analog Neural Network](https://github.com/Vivswan/AnalogVNN/raw/release/docs/_static/analogvnn_model.png))
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb)
+
+- Sample code with AnalogVNN: [sample_code.py](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code.py)
+- Sample code without
+  AnalogVNN: [sample_code_non_analog.py](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code_non_analog.py)
+- Sample code with AnalogVNN and
+  Logs: [sample_code_with_logs.py](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code_with_logs.py)
+- Jupyter
+  Notebook: [AnalogVNN_Demo.ipynb](https://github.com/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb)
 
 ## Abstract
 
+![3 Layered Linear Photonic Analog Neural Network](https://github.com/Vivswan/AnalogVNN/raw/release/docs/_static/analogvnn_model.png)
+
 **AnalogVNN** is a simulation framework built on PyTorch which can simulate the effects of
 optoelectronic noise, limited precision, and signal normalization present in photonic
 neural network accelerators. We use this framework to train and optimize linear and

analogvnn/graph/AccumulateGrad.py

@@ -41,7 +41,7 @@ def __repr__(self):
             str: String representation of the module.
         """
 
-        return f'AccumulateGrad({self.module})'
+        return f'{self.__class__.__name__}({self.module})'
 
     def __call__(  # noqa: C901
             self,

analogvnn/graph/AcyclicDirectedGraph.py

@@ -131,8 +131,8 @@ def add_edge(
         self.graph.nodes[v_of_edge]['fillcolor'] = 'lightblue'
         return self
 
-    @staticmethod  # noqa: C901
-    def check_edge_parameters(
+    @staticmethod
+    def check_edge_parameters(  # noqa: C901
             in_arg: Union[None, int, bool],
             in_kwarg: Union[None, str, bool],
             out_arg: Union[None, int, bool],

analogvnn/graph/ArgsKwargs.py

@@ -62,7 +62,7 @@ def is_empty(self):
     def __repr__(self):
         """Returns a string representation of the parameter."""
 
-        return f'ArgsKwargs(args={self.args}, kwargs={self.kwargs})'
+        return f'{self.__class__.__name__}(args={self.args}, kwargs={self.kwargs})'
 
     @classmethod
     def to_args_kwargs_object(cls, outputs: ArgsKwargsInput) -> ArgsKwargs:

analogvnn/nn/module/Layer.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import functools
+import inspect
 from typing import Union, Type, Callable, Sequence, Optional, Set, Iterator, Tuple
 
 from torch import nn, Tensor
@@ -178,7 +179,7 @@ def set_backward_function(self, backward_class: Union[Callable, BackwardModule,
         if backward_class == self:
             return self
 
-        if issubclass(backward_class, BackwardModule):
+        if inspect.isclass(backward_class) and issubclass(backward_class, BackwardModule):
             self._backward_module = backward_class(self)
         elif isinstance(backward_class, BackwardModule):
             backward_class.set_layer(self)

analogvnn/nn/module/Model.py

@@ -7,6 +7,7 @@
 from torch import optim, Tensor, nn
 from torch.utils.data import DataLoader
 
+from analogvnn.backward.BackwardModule import BackwardModule
 from analogvnn.fn.test import test
 from analogvnn.fn.train import train
 from analogvnn.graph.BackwardGraph import BackwardGraph
@@ -22,7 +23,7 @@
 __all__ = ['Model']
 
 
-class Model(Layer):
+class Model(Layer, BackwardModule):
     """Base class for analog neural network models.
 
     Attributes:

analogvnn/parameter/PseudoParameter.py

@@ -66,7 +66,7 @@ def __init__(self, data=None, requires_grad=True, transformation=None):
         self._transformed.original = self
         self._transformation = self.identity
         self.set_transformation(transformation)
-        self.substitute_member(self.original, self._transformed, "grad")
+        self.substitute_member(self.original, self._transformed, 'grad')
 
     def __call__(self, *args, **kwargs):
         """Transforms the parameter.
@@ -117,7 +117,7 @@ def __repr__(self):
             str: the string representation.
         """
 
-        return f'{PseudoParameter.__name__}(' \
+        return f'{self.__class__.__name__}(' \
                f'transform={self.transformation}' \
                f', original={self.original}' \
                f')'

analogvnn/utils/TensorboardModelLog.py

@@ -179,7 +179,7 @@ def add_summary(
             model=model,
             input_size=input_size,
             train_loader=train_loader,
-            *args,
+            *args,  # noqa: B026
             **kwargs
         )
 

analogvnn/utils/get_model_summaries.py

@@ -6,7 +6,7 @@
 from analogvnn.nn.module.Layer import Layer
 
 
-def get_model_summaries(
+def get_model_summaries(  # noqa: C901
         model: Optional[nn.Module],
         input_size: Optional[Sequence[int]] = None,
         train_loader: DataLoader = None,

docs/_static/AnalogVNN_Demo.ipynb

@@ -18,31 +18,31 @@
     "\n",
     "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
     "  <td>\n",
-    "    <a target=\"_blank\" href=\"https://analogvnn.readthedocs.io/en/v1.0.0/tutorial.html\">\n",
+    "    <a target=\"_blank\" href=\"https://analogvnn.readthedocs.io/en/release/tutorial.html\">\n",
     "      <center>\n",
     "        <img src=\"https://analogvnn.readthedocs.io/en/in_progess/_static/analogvnn-logo-square-black.svg\" height=\"32px\" />\n",
     "      </center>\n",
     "      View on AnalogVNN\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb\">\n",
+    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb\">\n",
     "      <center>\n",
     "        <img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />\n",
     "      </center>\n",
     "      Run in Google Colab\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a target=\"_blank\" href=\"https://github.com/Vivswan/AnalogVNN/blob/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb\">\n",
+    "    <a target=\"_blank\" href=\"https://github.com/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb\">\n",
     "      <center>\n",
     "        <img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />\n",
     "      </center>\n",
     "      View source on GitHub\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://github.com/Vivswan/AnalogVNN/raw/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb\">\n",
+    "    <a href=\"https://github.com/Vivswan/AnalogVNN/raw/release/docs/_static/AnalogVNN_Demo.ipynb\">\n",
     "      <center>\n",
     "        <img src=\"https://www.tensorflow.org/images/download_logo_32px.png\" />\n",
     "      </center>\n",
@@ -55,14 +55,14 @@
   {
    "cell_type": "markdown",
    "source": [
-    "#### To create 3 layered linear photonic analog neural network with 4-bit [precision](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#reduceprecision), 0.5 [leakage](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#leakage-or-error-probability) and [clamp](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#clamp) normalization:\n",
+    "#### To create 3 layered linear photonic analog neural network with 4-bit [precision](https://analogvnn.readthedocs.io/en/release/extra_classes.html#reduceprecision), 0.5 [leakage](https://analogvnn.readthedocs.io/en/release/extra_classes.html#leakage-or-error-probability) and [clamp](https://analogvnn.readthedocs.io/en/release/extra_classes.html#clamp) normalization:\n",
     "\n",
     "![3 Layered Linear Photonic Analog Neural Network](analogvnn_model.png)\n",
     "\n",
     "Python file:\n",
-    "[Sample code](https://github.com/Vivswan/AnalogVNN/blob/v1.0.0/sample_code.py)\n",
+    "[Sample code](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code.py)\n",
     "and\n",
-    "[Sample code with logs](https://github.com/Vivswan/AnalogVNN/blob/v1.0.0/sample_code_with_logs.py)"
+    "[Sample code with logs](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code_with_logs.py)"
    ],
    "metadata": {
     "collapsed": false
@@ -192,11 +192,11 @@
    "source": [
     "## Build a 3 layered linear photonic analog neural network\n",
     "\n",
-    "[`FullSequential`](https://analogvnn.readthedocs.io/en/v1.0.0/autoapi/analogvnn/nn/module/FullSequential/index.html#analogvnn.nn.module.FullSequential.FullSequential) is sequential model where backward graph is the reverse of forward graph.\n",
+    "[`FullSequential`](https://analogvnn.readthedocs.io/en/release/autoapi/analogvnn/nn/module/FullSequential/index.html#analogvnn.nn.module.FullSequential.FullSequential) is sequential model where backward graph is the reverse of forward graph.\n",
     "\n",
-    "To add the [Reduce Precision](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#reduce-precision), [Normalization](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#normalization), and [Noise](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#noise) before and after the main Linear layer, `add_layer` function is used.\n",
+    "To add the [Reduce Precision](https://analogvnn.readthedocs.io/en/release/extra_classes.html#reduce-precision), [Normalization](https://analogvnn.readthedocs.io/en/release/extra_classes.html#normalization), and [Noise](https://analogvnn.readthedocs.io/en/release/extra_classes.html#noise) before and after the main Linear layer, `add_layer` function is used.\n",
     "\n",
-    "Leakage definition: [https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#leakage-or-error-probability](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#leakage-or-error-probability)"
+    "Leakage definition: [https://analogvnn.readthedocs.io/en/release/extra_classes.html#leakage-or-error-probability](https://analogvnn.readthedocs.io/en/release/extra_classes.html#leakage-or-error-probability)"
    ]
   },
   {
@@ -244,7 +244,7 @@
     "id": "iOkIKXWoZbmn"
    },
    "source": [
-    "Note: [`analogvnn.nn.module.Sequential.Sequential.add_sequence()`](https://analogvnn.readthedocs.io/en/v1.0.0/autoapi/analogvnn/nn/module/Sequential/index.html#analogvnn.nn.module.Sequential.Sequential.add_sequence) is used to create and set forward and backward graphs in AnalogVNN, more information in Inner Workings"
+    "Note: [`analogvnn.nn.module.Sequential.Sequential.add_sequence()`](https://analogvnn.readthedocs.io/en/release/autoapi/analogvnn/nn/module/Sequential/index.html#analogvnn.nn.module.Sequential.Sequential.add_sequence) is used to create and set forward and backward graphs in AnalogVNN, more information in Inner Workings"
    ]
   },
   {
@@ -276,7 +276,7 @@
     "\n",
     "WeightModel is used to parametrize the parameter of LinearModel to simulate photonic weights\n",
     "\n",
-    "[`FullSequential`](https://analogvnn.readthedocs.io/en/v1.0.0/autoapi/analogvnn/nn/module/FullSequential/index.html#analogvnn.nn.module.FullSequential.FullSequential) is sequential model where backward graph is the reverse of forward graph."
+    "[`FullSequential`](https://analogvnn.readthedocs.io/en/release/autoapi/analogvnn/nn/module/FullSequential/index.html#analogvnn.nn.module.FullSequential.FullSequential) is sequential model where backward graph is the reverse of forward graph."
    ]
   },
   {
@@ -333,7 +333,7 @@
     "id": "Dtg27Y80WwR0"
    },
    "source": [
-    "Using [`PseudoParameter`](https://analogvnn.readthedocs.io/en/v1.0.0/inner_workings.html#pseudoparameters) to parametrize the parameter"
+    "Using [`PseudoParameter`](https://analogvnn.readthedocs.io/en/release/inner_workings.html#pseudoparameters) to parametrize the parameter"
    ]
   },
   {
@@ -443,7 +443,7 @@
    "source": [
     "## Conclusion\n",
     "\n",
-    "Congratulations! You have trained a 3 layered linear photonic analog neural network with 4-bit [precision](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#reduceprecision), 0.5 [leakage](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#leakage-or-error-probability) and [clamp](https://analogvnn.readthedocs.io/en/v1.0.0/extra_classes.html#clamp) normalization"
+    "Congratulations! You have trained a 3 layered linear photonic analog neural network with 4-bit [precision](https://analogvnn.readthedocs.io/en/release/extra_classes.html#reduceprecision), 0.5 [leakage](https://analogvnn.readthedocs.io/en/release/extra_classes.html#leakage-or-error-probability) and [clamp](https://analogvnn.readthedocs.io/en/release/extra_classes.html#clamp) normalization"
    ]
   },
   {

docs/conf.py

@@ -107,8 +107,7 @@
     'light_logo': 'analogvnn-logo-wide-white.svg',
     'dark_logo': 'analogvnn-logo-wide-black.svg',
     'source_repository': 'https://github.com/Vivswan/AnalogVNN',
-    # 'source_branch': 'master',
-    'source_branch': 'v1.0.0',
+    'source_branch': 'release',
     'source_directory': 'docs/',
 }
 # html_logo = '_static/analogvnn-logo-wide-black.svg'

docs/install.md

@@ -2,7 +2,7 @@
 
 AnalogVNN is tested and supported on the following 64-bit systems:
 
-- Python 3.7, 3.8, 3.9, 3.10
+- Python 3.7, 3.8, 3.9, 3.10, 3.11
 - Windows 7 and later
 - Ubuntu 16.04 and later, including WSL
 - Red Hat Enterprise Linux 7 and later

docs/sample_code.md

@@ -1,15 +1,15 @@
 # Sample code
 
-<a href="https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb" style="font-size:24px;">
+<a href="https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb" style="font-size:24px;">
 Run in Google Colab:
 <img alt="Google Colab" src="https://www.tensorflow.org/images/colab_logo_32px.png" style="vertical-align: bottom;">
 </a>
 
 ![3 Layered Linear Photonic Analog Neural Network](_static/analogvnn_model.png)
 
-[Sample code](https://github.com/Vivswan/AnalogVNN/blob/v1.0.0/sample_code.py)
+[Sample code](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code.py)
 and
-[Sample code with logs](https://github.com/Vivswan/AnalogVNN/blob/v1.0.0/sample_code_with_logs.py)
+[Sample code with logs](https://github.com/Vivswan/AnalogVNN/blob/release/sample_code_with_logs.py)
 for 3 layered linear photonic analog neural network with 4-bit precision,
 0.5 {ref}`extra_classes:leakage` and {ref}`extra_classes:clamp`
 normalization:

docs/tutorial.md

@@ -1,6 +1,6 @@
 # Tutorial
 
-<a href="https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/v1.0.0/docs/_static/AnalogVNN_Demo.ipynb" style="font-size:24px;">
+<a href="https://colab.research.google.com/github/Vivswan/AnalogVNN/blob/release/docs/_static/AnalogVNN_Demo.ipynb" style="font-size:24px;">
 Run in Google Colab:
 <img alt="Google Colab" src="https://www.tensorflow.org/images/colab_logo_32px.png" style="vertical-align: bottom;">
 </a>