TF_Forum_22662.ipynb

tf_forum_22662.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyO/x91DT4wW0PJttERZzyCZ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/kiransair/b98dadd179bac57ac54790e8c3a49360/tf_forum_22662.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "l81mRrEbV4K-"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mnist=keras.datasets.mnist.load_data()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mhW11bqSV-Jt",
        "outputId": "b9206e6a-a686-4faf-e6b8-a65b6f44c756"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n",
            "11490434/11490434 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "(x_train,y_train),(x_test,y_test)=mnist"
      ],
      "metadata": {
        "id": "kBPL_fWYWAcv"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_train=x_train.astype('float32')/255\n",
        "x_test=x_test.astype('float32')/255"
      ],
      "metadata": {
        "id": "D_bAdC9CWCTu"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_train=keras.utils.to_categorical(y_train,10)\n",
        "y_test=keras.utils.to_categorical(y_test,10)"
      ],
      "metadata": {
        "id": "_ofWINugWEJd"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model=keras.Sequential([\n",
        "                        keras.Input(shape=(28,28,1)),\n",
        "                        keras.layers.Conv2D(32,kernel_size=(3,3),activation='relu',),\n",
        "                        keras.layers.MaxPooling2D(pool_size=(2,2)),\n",
        "                        keras.layers.Conv2D(64,kernel_size=(3,3),activation='relu'),\n",
        "                        keras.layers.MaxPooling2D(pool_size=(2,2)),\n",
        "                        keras.layers.GlobalAveragePooling2D(),\n",
        "                        keras.layers.Dropout(0.5),\n",
        "                        keras.layers.Dense(10,activation='softmax')\n",
        "])"
      ],
      "metadata": {
        "id": "cfekXdZsWFme"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "optimizer=tf.keras.optimizers.Adam()"
      ],
      "metadata": {
        "id": "jprJx9SCWHQn"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(loss=\"categorical_crossentropy\", optimizer=optimizer,metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "NFUzgnf7WJAk"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(x_train,y_train,epochs=2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2oy2szfAWL21",
        "outputId": "2b098663-4887-44f9-f666-ceef1974590a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/2\n",
            "1875/1875 [==============================] - 49s 26ms/step - loss: 1.3896 - accuracy: 0.5195\n",
            "Epoch 2/2\n",
            "1875/1875 [==============================] - 46s 25ms/step - loss: 0.7924 - accuracy: 0.7463\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7f5949151930>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.keras.saving.save_model(model,'./model')"
      ],
      "metadata": {
        "id": "XTarUed7WQXb"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!tflite_convert --saved_model_dir='/content/model' --graph_def_file='/content/model/saved_model.pb' --output_file='model1_clpb.tflite' --input_shapes=1,28,28,1 --input_arrays='input' --output_arrays='Softmax'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vMJYAzzyWTGr",
        "outputId": "5dd99272-e1a8-4bb9-8fe1-3ee5d56d805b"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-03-05 06:44:28.136040: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2024-03-05 06:44:28.136114: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2024-03-05 06:44:28.138076: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2024-03-05 06:44:29.398578: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "2024-03-05 06:44:31.594119: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:378] Ignored output_format.\n",
            "2024-03-05 06:44:31.594191: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:381] Ignored drop_control_dependency.\n",
            "Summary on the non-converted ops:\n",
            "---------------------------------\n",
            " * Accepted dialects: tfl, builtin, func\n",
            " * Non-Converted Ops: 7, Total Ops 17, % non-converted = 41.18 %\n",
            " * 7 ARITH ops\n",
            "\n",
            "- arith.constant:    7 occurrences  (f32: 6, i32: 1)\n",
            "\n",
            "\n",
            "\n",
            "  (f32: 2)\n",
            "  (f32: 1)\n",
            "  (f32: 2)\n",
            "  (f32: 1)\n",
            "  (f32: 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "ht7IE0z1WcXr"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}