cnn model design

1baa2780 · Jayesh · 19c5fbba · 1baa2780 · 1baa2780 · 1baa2780
Commit 1baa2780 authored Jun 22, 2024 by Jayesh
--- a/Assignment-3/Week2/CNN_model.ipynb
+++ b/Assignment-3/Week2/CNN_model.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import keras_tuner as kt\n",
+    "import numpy as np\n",
+    "import tensorflow as tf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from constants import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class StackOverflowCNN:\n",
+    "    \"\"\"\n",
+    "    A class representing a CNN model for Stack Overflow classification.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    def __init__(self, vocab_length, embedding_matrix, filters=64, hidden_layer_size=0,\n",
+    "                 num_convolutions=3, kernel_size=3):\n",
+    "        \"\"\"\n",
+    "        Initializes the StackOverflowCNN model.\n",
+    "\n",
+    "        Args:\n",
+    "            vocab_length (int): The length of the vocabulary.\n",
+    "            embedding_matrix (numpy.ndarray): The embedding matrix.\n",
+    "            filters (int, optional): The number of filters in the convolutional layers. Defaults to 64.\n",
+    "            hidden_layer_size (int, optional): The size of the hidden layer. Defaults to 0.\n",
+    "            num_convolutions (int, optional): The number of convolutional layers. Defaults to 3.\n",
+    "            kernel_size (int, optional): The size of the convolutional kernel. Defaults to 3.\n",
+    "        \"\"\"\n",
+    "        input_layer = tf.keras.layers.Input(\n",
+    "            shape=(MAX_SEQUENCE_LENGTH,),\n",
+    "            batch_size=32\n",
+    "        )\n",
+    "\n",
+    "        embedding = tf.keras.layers.Embedding(vocab_length,\n",
+    "                                              EMBEDDING_DIM,\n",
+    "                                              input_length=MAX_SEQUENCE_LENGTH,\n",
+    "                                              embeddings_initializer=tf.keras.initializers.Constant(embedding_matrix),\n",
+    "                                              trainable=True, mask_zero=True)(input_layer)\n",
+    "\n",
+    "        conv_layers = [\n",
+    "            tf.keras.layers.Conv1D(filters=filters,\n",
+    "                                   kernel_size=kernel_size)(embedding)\n",
+    "            for _ in range(num_convolutions)\n",
+    "        ]\n",
+    "\n",
+    "        pooling_layers = [\n",
+    "            tf.keras.layers.GlobalMaxPooling1D()(conv)\n",
+    "            for conv in conv_layers\n",
+    "        ]\n",
+    "\n",
+    "        if len(pooling_layers) == 1:\n",
+    "            hidden = pooling_layers[0]\n",
+    "        else:\n",
+    "            hidden = tf.keras.layers.concatenate(pooling_layers, axis=1)\n",
+    "\n",
+    "        if hidden_layer_size > 0:\n",
+    "            hidden = tf.keras.layers.Dense(hidden_layer_size, activation='relu')(hidden)\n",
+    "\n",
+    "        outputs = tf.keras.layers.Dense(NUM_CLASSES)(hidden)\n",
+    "        self.model = tf.keras.Model(inputs=[embedding], outputs=outputs)\n",
+    "\n",
+    "    def get_model(self):\n",
+    "        \"\"\"\n",
+    "        Returns the CNN model.\n",
+    "\n",
+    "        Returns:\n",
+    "            tf.keras.Model: The CNN model.\n",
+    "        \"\"\"\n",
+    "        return self.model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
+%% Cell type:code id: tags:
+
+``` python
+import keras_tuner as kt
+import numpy as np
+import tensorflow as tf
+```
+
+%% Cell type:code id: tags:
+
+``` python
+from constants import *
+```
+
+%% Cell type:code id: tags:
+
+``` python
+class StackOverflowCNN:
+    """
+    A class representing a CNN model for Stack Overflow classification.
+    """
+
+    def __init__(self, vocab_length, embedding_matrix, filters=64, hidden_layer_size=0,
+                 num_convolutions=3, kernel_size=3):
+        """
+        Initializes the StackOverflowCNN model.
+
+        Args:
+            vocab_length (int): The length of the vocabulary.
+            embedding_matrix (numpy.ndarray): The embedding matrix.
+            filters (int, optional): The number of filters in the convolutional layers. Defaults to 64.
+            hidden_layer_size (int, optional): The size of the hidden layer. Defaults to 0.
+            num_convolutions (int, optional): The number of convolutional layers. Defaults to 3.
+            kernel_size (int, optional): The size of the convolutional kernel. Defaults to 3.
+        """
+        input_layer = tf.keras.layers.Input(
+            shape=(MAX_SEQUENCE_LENGTH,),
+            batch_size=32
+        )
+
+        embedding = tf.keras.layers.Embedding(vocab_length,
+                                              EMBEDDING_DIM,
+                                              input_length=MAX_SEQUENCE_LENGTH,
+                                              embeddings_initializer=tf.keras.initializers.Constant(embedding_matrix),
+                                              trainable=True, mask_zero=True)(input_layer)
+
+        conv_layers = [
+            tf.keras.layers.Conv1D(filters=filters,
+                                   kernel_size=kernel_size)(embedding)
+            for _ in range(num_convolutions)
+        ]
+
+        pooling_layers = [
+            tf.keras.layers.GlobalMaxPooling1D()(conv)
+            for conv in conv_layers
+        ]
+
+        if len(pooling_layers) == 1:
+            hidden = pooling_layers[0]
+        else:
+            hidden = tf.keras.layers.concatenate(pooling_layers, axis=1)
+
+        if hidden_layer_size > 0:
+            hidden = tf.keras.layers.Dense(hidden_layer_size, activation='relu')(hidden)
+
+        outputs = tf.keras.layers.Dense(NUM_CLASSES)(hidden)
+        self.model = tf.keras.Model(inputs=[embedding], outputs=outputs)
+
+    def get_model(self):
+        """
+        Returns the CNN model.
+
+        Returns:
+            tf.keras.Model: The CNN model.
+        """
+        return self.model
+```
+
+%% Cell type:code id: tags:
+
+``` python
+```
--- a/Assignment-3/Week2/constants.py
+++ b/Assignment-3/Week2/constants.py
+MAX_SEQUENCE_LENGTH = 200
+EMBEDDING_DIM = 100
+NUM_CLASSES = 3
\ No newline at end of file
--- a/Assignment-3/Week2/requirements.txt
+++ b/Assignment-3/Week2/requirements.txt
+absl-py==2.1.0
+annotated-types==0.6.0
+anyio==3.7.1
+argon2-cffi==23.1.0
+argon2-cffi-bindings==21.2.0
+arrow==1.3.0
+asttokens==2.4.0
+astunparse==1.6.3
+async-lru==2.0.4
+attrs==23.2.0
+Babel==2.15.0
+backcall==0.2.0
+backports.tarfile==1.1.1
+beautifulsoup4==4.12.3
+bleach==6.1.0
+certifi==2023.7.22
+cffi==1.16.0
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+comm==0.1.4
+contourpy==1.1.1
+cycler==0.12.1
+debugpy==1.8.0
+decorator==5.1.1
+defusedxml==0.7.1
+dnspython==2.4.2
+email-validator==2.0.0.post2
+et-xmlfile==1.1.0
+exceptiongroup==1.1.3
+executing==2.0.0
+fastapi==0.103.2
+fastjsonschema==2.19.1
+flatbuffers==24.3.25
+fonttools==4.43.1
+fqdn==1.5.1
+funcy==2.0
+gast==0.5.4
+gensim==4.3.2
+google-pasta==0.2.0
+grpcio==1.64.1
+h11==0.14.0
+h5py==3.11.0
+httpcore==0.18.0
+httptools==0.6.1
+httpx==0.25.0
+idna==3.4
+importlib_metadata==7.1.0
+ipykernel==6.25.2
+ipython==8.16.1
+ipywidgets==8.1.3
+isoduration==20.11.0
+itsdangerous==2.1.2
+jaraco.classes==3.4.0
+jaraco.context==5.3.0
+jaraco.functools==4.0.1
+jedi==0.19.1
+Jinja2==3.1.2
+jira==3.8.0
+joblib==1.4.2
+json5==0.9.25
+jsonpointer==2.4
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+jupyter==1.0.0
+jupyter-console==6.6.3
+jupyter-events==0.10.0
+jupyter-lsp==2.2.5
+jupyter_client==8.4.0
+jupyter_core==5.4.0
+jupyter_server==2.14.1
+jupyter_server_terminals==0.5.3
+jupyterlab==4.2.1
+jupyterlab_pygments==0.3.0
+jupyterlab_server==2.27.2
+jupyterlab_widgets==3.0.11
+keras==3.3.3
+keras-tuner==1.4.7
+keyring==25.2.1
+kiwisolver==1.4.5
+kt-legacy==1.0.5
+libclang==18.1.1
+Markdown==3.6
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+matplotlib==3.8.0
+matplotlib-inline==0.1.6
+mdurl==0.1.2
+mistune==3.0.2
+ml-dtypes==0.3.2
+more-itertools==10.2.0
+namex==0.0.8
+nbclient==0.10.0
+nbconvert==7.16.4
+nbformat==5.10.4
+nest-asyncio==1.5.8
+nltk==3.8.1
+notebook==7.2.1
+notebook_shim==0.2.4
+numexpr==2.10.0
+numpy==1.26.1
+oauthlib==3.2.2
+openpyxl==3.1.2
+opt-einsum==3.3.0
+optree==0.11.0
+orjson==3.9.9
+overrides==7.7.0
+packaging==23.2
+pandas==2.1.1
+pandocfilters==1.5.1
+parso==0.8.3
+patsy==0.5.6
+pickleshare==0.7.5
+Pillow==10.1.0
+platformdirs==3.11.0
+plotly==5.22.0
+prometheus_client==0.20.0
+prompt-toolkit==3.0.39
+protobuf==4.25.3
+psutil==5.9.6
+pure-eval==0.2.2
+pycparser==2.22
+pydantic==2.4.2
+pydantic-extra-types==2.1.0
+pydantic-settings==2.0.3
+pydantic_core==2.10.1
+Pygments==2.16.1
+pyLDAvis==3.4.1
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-dotenv==1.0.0
+python-json-logger==2.0.7
+python-multipart==0.0.6
+pytz==2023.3.post1
+pywin32==306
+pywin32-ctypes==0.2.2
+pywinpty==2.0.13
+PyYAML==6.0.1
+pyzmq==25.1.1
+qtconsole==5.5.2
+QtPy==2.4.1
+referencing==0.35.1
+regex==2024.5.15
+requests==2.32.2
+requests-oauthlib==2.0.0
+requests-toolbelt==1.0.0
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
+rich==13.7.1
+rpds-py==0.18.1
+scikit-learn==1.5.0
+scikit-posthocs==0.9.0
+scipy==1.12.0
+seaborn==0.13.2
+Send2Trash==1.8.3
+six==1.16.0
+smart-open==7.0.4
+sniffio==1.3.0
+soupsieve==2.5
+stack-data==0.6.3
+starlette==0.27.0
+statsmodels==0.14.2
+tenacity==8.3.0
+tensorboard==2.16.2
+tensorboard-data-server==0.7.2
+tensorflow==2.16.1
+tensorflow-intel==2.16.1
+tensorflow-io-gcs-filesystem==0.31.0
+termcolor==2.4.0
+terminado==0.18.1
+threadpoolctl==3.5.0
+tinycss2==1.3.0
+tomli==2.0.1
+tornado==6.3.3
+tqdm==4.66.4
+traitlets==5.11.2
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.8.0
+tzdata==2023.3
+ujson==5.8.0
+uri-template==1.3.0
+urllib3==2.2.1
+uvicorn==0.23.2
+watchfiles==0.21.0
+wcwidth==0.2.8
+webcolors==24.6.0
+webencodings==0.5.1
+websocket-client==1.8.0
+websockets==11.0.3
+Werkzeug==3.0.3
+widgetsnbextension==4.0.11
+wrapt==1.16.0
+zipp==3.19.0