DSA-Python-Cap10-Intro-TensorFlow.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 10</font>\n",
    "\n",
    "## Download: http://github.com/dsacademybr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Versão da Linguagem Python\n",
    "from platform import python_version\n",
    "print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introdução ao TensorFlow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O Tensorflow é uma das bibliotecas mais amplamente utilizadas para implementar o aprendizado de máquina e outros algoritmos que envolvem grandes operações matemáticas. O Tensorflow foi desenvolvido pelo Google e é uma das bibliotecas de aprendizado de máquina mais populares no GitHub. O Google usa o Tensorflow para aprendizado de máquina em quase todos os aplicativos. Se você já usou o Google Photos ou o Google Voice Search, então já utlizou uma aplicação criada com a ajuda do TensorFlow. Vamos compreender os detalhes por trás do TensorFlow.\n",
    "\n",
    "Matematicamente, um tensor é um vetor N-dimensional, significando que um tensor pode ser usado para representar conjuntos de dados N-dimensionais. Aqui está um exemplo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/tensor1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A figura acima mostra alguns tensores simplificados com dimensões mínimas. À medida que a dimensão continua crescendo, os dados se tornam mais e mais complexos. Por exemplo, se pegarmos um Tensor da forma (3x3), posso chamá-lo de matriz de 3 linhas e colunas. Se eu selecionar outro Tensor de forma (1000x3x3), posso chamá-lo como tensor ou conjunto de 1000 matrizes 3x3. Aqui chamamos (1000x3x3) como a forma ou dimensão do tensor resultante. Os tensores podem ser constantes ou variáveis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/tensor2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TensorFlow x NumPy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TensorFlow e NumPy são bastante semelhantes (ambos são bibliotecas de matriz N-d). NumPy é o pacote fundamental para computação científica com Python. Ele contém um poderoso objeto array N-dimensional, funções sofisticadas (broadcasting) e etc. Acredito que os usuários Python não podem viver sem o NumPy. O NumPy tem suporte a matriz N-d, mas não oferece métodos para criar funções de tensor e automaticamente computar derivadas, além de não ter suporte a GPU, e esta é uma das principais razões para a existência do TensorFlow. Abaixo uma comparação entre NumPy e TensorFlow, e você vai perceber que muitas palavras-chave são semelhantes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/tf_numpy.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grafo Computacional\n",
    "\n",
    "Conheça a Formação Inteligência Artificial, um programa completo, 100% online e 100% em português, com 402 horas em 9 cursos de nível intermediário/avançado, que vão ajudá-lo a se tornar um dos profissionais mais cobiçados do mercado de tecnologia. Clique no link abaixo, faça sua inscrição, comece hoje mesmo e aumente sua empregabilidade:\n",
    "\n",
    "https://www.datascienceacademy.com.br/pages/formacao-inteligencia-artificial\n",
    "\n",
    "Agora sabemos o que o tensor realmente significa e é hora de entender o fluxo. Este fluxo refere-se a um grafo computacional ou simplesmente um grafo. \n",
    "\n",
    "Grafos computacionais são uma boa maneira de pensar em expressões matemáticas. O conceito de grafo foi introduzido por Leonhard Euler em 1736 para tentar resolver o problema das Pontes de Konigsberg. Grafos são modelos matemáticos para resolver problemas práticos do dia a dia, com várias aplicações no mundo real tais como: circuitos elétricos, redes de distribuição, relações de parentesco entre pessoas, análise de redes sociais, logística, redes de estradas, redes de computadores e muito mais. Grafos são muito usados para modelar problemas em computação.\n",
    "\n",
    "Um Grafo é um modelo matemático que representa relações entre objetos. Um grafo G = (V, E) consiste de um conjunto de vértices V (também chamados de nós), ligados por um conjunto de bordas ou arestas E. \n",
    "\n",
    "Considere o diagrama abaixo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/grafo1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Existem três operações: duas adições e uma multiplicação. Ou seja: \n",
    "\n",
    "- c = a+b\n",
    "- d = b+1\n",
    "- e = c∗d\n",
    "\n",
    "Para criar um grafo computacional, fazemos cada uma dessas operações nos nós, juntamente com as variáveis de entrada. Quando o valor de um nó é a entrada para outro nó, uma seta vai de um para outro e temos nesse caso um grafo direcionado.\n",
    "\n",
    "Esses tipos de grafos surgem o tempo todo em Ciência da Computação, especialmente ao falar sobre programas funcionais. Eles estão intimamente relacionados com as noções de grafos de dependência e grafos de chamadas. Eles também são a principal abstração por trás do popular framework de Deep Learning, o TensorFlow.\n",
    "\n",
    "Para mais detalhes sobre grafos, leia um dos capítulos do Deep Learning Book:\n",
    "\n",
    "http://deeplearningbook.com.br/algoritmo-backpropagation-parte1-grafos-computacionais-e-chain-rule/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Um grafo para execução de um modelo de Machine Learning pode ser bem grande e podemos executar sub-grafos (porções dos grafos) em dispositivos diferentes, como uma GPU. Exemplo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/grafo2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A figura acima explica a execução paralela de sub-grafos. Aqui estão 2 operações de multiplicação de matrizes, já que ambas estão no mesmo nível. Os nós são executados em gpu_0 e gpu_1 em paralelo."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modelo de Programação TensorFlow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O principal objetivo de um programa TensorFlow é expressar uma computação numérica como um grafo direcionado. A figura abaixo é um exemplo de grafo de computação, que representa o cálculo de h = ReLU (Wx + b). Este é um componente muito clássico em muitas redes neurais, que conduz a transformação linear dos dados de entrada e, em seguida, alimenta uma linearidade (função de ativação linear retificada, neste caso)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/grafo3.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O grafo acima representa um cálculo de fluxo de dados; cada nó está em operação com zero ou mais entradas e zero ou mais saídas. As arestas do grafo são tensores que fluem entre os nós. Os clientes geralmente constroem um grafo computacional usando uma das linguagens frontend suportadas como Python e C ++ e, em seguida, iniciam o grafo em uma sessão a ser executada (Session é uma noção muito importante no TensorFlow, que estudaremos na sequência)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos ver o grafo computacional acima em detalhes. Truncamos o grafo e deixamos a parte acima do nó ReLU, que é exatamente o cálculo h = ReLU (Wx + b)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/grafo4.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podemos ver o grafo como um sistema, que tem entradas (os dados x), saída (h neste caso), variáveis com estado (W e b) e um monte de operações (matmul, add e ReLU). Deixe-me apresentar-lhe um por um.\n",
    "\n",
    "- Placeholders: para alimentar a entrada para treinar o modelo ou fazer inferência, devemos ter uma porta de entrada para o grafo. Espaços reservados (Placeholders) são nós cujos valores são alimentados em tempo de execução. Normalmente, queremos alimentar entradas de dados, rótulos e hiper-parâmetros no modelo.\n",
    "\n",
    "\n",
    "- Variáveis: quando treinamos um modelo, usamos variáveis para manter e atualizar parâmetros. Ao contrário de muitos tensores que fluem ao longo das margens do grafo, uma variável é um tipo especial de operação. Na maioria dos modelos de aprendizado de máquina, existem muitos parâmetros que temos que aprender, que são atualizados durante o treinamento. Variáveis são nós com estado que armazenam parâmetros e produzem seus valores atuais de tempos em tempos. Seus estados são mantidos em múltiplas execuções de um grafo. Por exemplo, os valores desses nós não serão atualizados até que uma etapa completa de treinamento usando um mini lote de dados seja concluída.\n",
    "\n",
    "\n",
    "- Operações matemáticas: Neste grafo, existem três tipos de operações matemáticas. A operação MatMul multiplica dois valores de matriz; A operação Add adiciona elementos e a operação ReLU é ativada com a função linear retificada de elementos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Variáveis devem ser explicitamente inicializadas. Quando criamos uma variável, passamos um tensor como seu valor inicial para o construtor variable (). O inicializador pode ser constantes, sequências e valores aleatórios. Neste caso, inicializamos o vetor de polarização b por constantes que são zeros e inicializamos a matriz de ponderações W por uniforme aleatório Observe que todos esses ops exigem que você especifique a forma dos tensores e que a forma se torne automaticamente a forma da variável , Neste caso, um tensor com forma (100,) e W é um tensor de classificação com forma (784, 100)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para executar o cálculo, devemos lançar o grafo em um tf.Session. O que é uma sessão? Podemos entender uma sessão como um ambiente para executar o grafo. Na verdade, para fazer computação numérica eficiente em Python, normalmente usamos bibliotecas como o NumPy que realizam operações custosas computacionalmente, como a multiplicação de matrizes, usando código altamente eficiente implementado em outro idioma (C). Infelizmente, ainda há muita sobrecarga voltando para o Python em todas as operações. Essa sobrecarga é particularmente ruim se você quiser fazer cálculos em GPUs ou de maneira distribuída, onde pode haver um alto custo para transferir dados. Para mais detalhes, visite: www.datascienceacademy.com.br."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hello World"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obs: Embora a versão 2.x do TensorFlow já esteja disponível, este Jupyter Notebook usar a versão 1.15, que também é mantida pela equipe do Google.\n",
    "\n",
    "Caso queira aprender TensorFlow 2.0, esta versão já está disponível nos cursos da Formação IA, aqui na DSA.\n",
    "\n",
    "Execute a célula abaixo para instalar o TensorFlow na sua máquina."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Versão do TensorFlow a ser usada \n",
    "!pip install -q tensorflow==1.15.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n",
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-4-64156d691fe5>\", line 1, in <module>\n",
      "    import tensorflow as tf\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 99, in <module>\n",
      "    from tensorflow_core import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'ImportError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1151, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 319, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 353, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1460, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 967, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 677, in _load_unlocked\n",
      "  File \"<frozen importlib._bootstrap_external>\", line 728, in exec_module\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-4-64156d691fe5>\", line 1, in <module>\n",
      "    import tensorflow as tf\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 99, in <module>\n",
      "    from tensorflow_core import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'ImportError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-4-64156d691fe5>\", line 1, in <module>\n",
      "    import tensorflow as tf\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 99, in <module>\n",
      "    from tensorflow_core import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'ImportError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3254, in run_ast_nodes\n",
      "    if (await self.run_code(code, result,  async_=asy)):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3348, in run_code\n",
      "    self.showtraceback(running_compiled_code=True)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2047, in showtraceback\n",
      "    value, tb, tb_offset=tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1418, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1318, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1186, in structured_traceback\n",
      "    formatted_exceptions += self.prepare_chained_exception_message(evalue.__cause__)\n",
      "TypeError: can only concatenate str (not \"list\") to str\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1151, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 319, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 353, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1460, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 967, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 677, in _load_unlocked\n",
      "  File \"<frozen importlib._bootstrap_external>\", line 728, in exec_module\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-4-64156d691fe5>\", line 1, in <module>\n",
      "    import tensorflow as tf\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 99, in <module>\n",
      "    from tensorflow_core import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'ImportError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3254, in run_ast_nodes\n",
      "    if (await self.run_code(code, result,  async_=asy)):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3348, in run_code\n",
      "    self.showtraceback(running_compiled_code=True)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2047, in showtraceback\n",
      "    value, tb, tb_offset=tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1418, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1318, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1186, in structured_traceback\n",
      "    formatted_exceptions += self.prepare_chained_exception_message(evalue.__cause__)\n",
      "TypeError: can only concatenate str (not \"list\") to str\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "can only concatenate str (not \"list\") to str",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     57\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 58\u001b[1;33m   \u001b[1;32mfrom\u001b[0m \u001b[0mtensorflow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpython\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpywrap_tensorflow_internal\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[1;33m*\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     59\u001b[0m   \u001b[1;32mfrom\u001b[0m \u001b[0mtensorflow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpython\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpywrap_tensorflow_internal\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0m__version__\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     27\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0m_mod\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 28\u001b[1;33m     \u001b[0m_pywrap_tensorflow_internal\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mswig_import_helper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     29\u001b[0m     \u001b[1;32mdel\u001b[0m \u001b[0mswig_import_helper\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\u001b[0m in \u001b[0;36mswig_import_helper\u001b[1;34m()\u001b[0m\n\u001b[0;32m     23\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 24\u001b[1;33m                 \u001b[0m_mod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mimp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload_module\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'_pywrap_tensorflow_internal'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpathname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdescription\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     25\u001b[0m             \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\imp.py\u001b[0m in \u001b[0;36mload_module\u001b[1;34m(name, file, filename, details)\u001b[0m\n\u001b[0;32m    241\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 242\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mload_dynamic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    243\u001b[0m     \u001b[1;32melif\u001b[0m \u001b[0mtype_\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mPKG_DIRECTORY\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\imp.py\u001b[0m in \u001b[0;36mload_dynamic\u001b[1;34m(name, path, file)\u001b[0m\n\u001b[0;32m    341\u001b[0m             name=name, loader=loader, origin=path)\n\u001b[1;32m--> 342\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0m_load\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mspec\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    343\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: DLL load failed with error code 3221225501",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[1;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[0;32m   2043\u001b[0m                         \u001b[1;31m# in the engines. This should return a list of strings.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2044\u001b[1;33m                         \u001b[0mstb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2045\u001b[0m                     \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'ImportError' object has no attribute '_render_traceback_'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\u001b[0m in \u001b[0;36mrun_code\u001b[1;34m(self, code_obj, result, async_)\u001b[0m\n\u001b[0;32m   3346\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3347\u001b[0m                 \u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merror_in_exec\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3348\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshowtraceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrunning_compiled_code\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3349\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3350\u001b[0m             \u001b[0moutflag\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[1;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[0;32m   2045\u001b[0m                     \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2046\u001b[0m                         stb = self.InteractiveTB.structured_traceback(etype,\n\u001b[1;32m-> 2047\u001b[1;33m                                             value, tb, tb_offset=tb_offset)\n\u001b[0m\u001b[0;32m   2048\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2049\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_showtraceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0metype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[1;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[0;32m   1416\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1417\u001b[0m         return FormattedTB.structured_traceback(\n\u001b[1;32m-> 1418\u001b[1;33m             self, etype, value, tb, tb_offset, number_of_lines_of_context)\n\u001b[0m\u001b[0;32m   1419\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1420\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[1;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[0;32m   1316\u001b[0m             \u001b[1;31m# Verbose modes need a full traceback\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1317\u001b[0m             return VerboseTB.structured_traceback(\n\u001b[1;32m-> 1318\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0metype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtb_offset\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnumber_of_lines_of_context\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1319\u001b[0m             )\n\u001b[0;32m   1320\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0mmode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'Minimal'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[1;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[0;32m   1184\u001b[0m         \u001b[0mexception\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_parts_of_chained_exception\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mevalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1185\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mexception\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1186\u001b[1;33m             \u001b[0mformatted_exceptions\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprepare_chained_exception_message\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mevalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__cause__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1187\u001b[0m             \u001b[0metype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0metb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexception\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1188\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: can only concatenate str (not \"list\") to str"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-5-65996cac02ec>\", line 1, in <module>\n",
      "    tf.__version__\n",
      "NameError: name 'tf' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1151, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 319, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 353, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1460, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 967, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 677, in _load_unlocked\n",
      "  File \"<frozen importlib._bootstrap_external>\", line 728, in exec_module\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-5-65996cac02ec>\", line 1, in <module>\n",
      "    tf.__version__\n",
      "NameError: name 'tf' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'tf' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m"
     ]
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-6-0c0b37b80bc4>\", line 3, in <module>\n",
      "    hello = tf.constant('Hello, TensorFlow!')\n",
      "NameError: name 'tf' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1151, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 319, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 353, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 1460, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 967, in _find_and_load_unlocked\n",
      "  File \"<frozen importlib._bootstrap>\", line 677, in _load_unlocked\n",
      "  File \"<frozen importlib._bootstrap_external>\", line 728, in exec_module\n",
      "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\__init__.py\", line 28, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\importlib\\__init__.py\", line 127, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\__init__.py\", line 49, in <module>\n",
      "    from tensorflow.python import pywrap_tensorflow\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 74, in <module>\n",
      "    raise ImportError(msg)\n",
      "ImportError: Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3331, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-6-0c0b37b80bc4>\", line 3, in <module>\n",
      "    hello = tf.constant('Hello, TensorFlow!')\n",
      "NameError: name 'tf' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow.py\", line 58, in <module>\n",
      "    from tensorflow.python.pywrap_tensorflow_internal import *\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 28, in <module>\n",
      "    _pywrap_tensorflow_internal = swig_import_helper()\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\site-packages\\tensorflow_core\\python\\pywrap_tensorflow_internal.py\", line 24, in swig_import_helper\n",
      "    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 242, in load_module\n",
      "    return load_dynamic(name, filename, file)\n",
      "  File \"C:\\Users\\HomeOffice\\anaconda3\\lib\\imp.py\", line 342, in load_dynamic\n",
      "    return _load(spec)\n",
      "ImportError: DLL load failed with error code 3221225501\n",
      "\n",
      "\n",
      "Failed to load the native TensorFlow runtime.\n",
      "\n",
      "See https://www.tensorflow.org/install/errors\n",
      "\n",
      "for some common reasons and solutions.  Include the entire stack trace\n",
      "above this error message when asking for help.\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'tf' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m"
     ]
    }
   ],
   "source": [
    "# Cria um tensor\n",
    "# Esse tensor é adicionado como um nó ao grafo.\n",
    "hello = tf.constant('Hello, TensorFlow!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const:0\", shape=(), dtype=string)\n"
     ]
    }
   ],
   "source": [
    "print(hello)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inicia a sessão TensorFlow\n",
    "sess = tf.Session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<tensorflow.python.client.session.Session object at 0x7fb1c8028b50>\n"
     ]
    }
   ],
   "source": [
    "print(sess)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'Hello, TensorFlow!'\n"
     ]
    }
   ],
   "source": [
    "# Executa o Grafo Computacional\n",
    "print(sess.run(hello))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Operações Matemáticas com Tensores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Soma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constantes\n",
    "const_a = tf.constant(5)\n",
    "const_b = tf.constant(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const_1:0\", shape=(), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(const_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Soma\n",
    "total = const_a + const_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"add:0\", shape=(), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "A soma do node1 com o node2 é: 14.000000\n"
     ]
    }
   ],
   "source": [
    "# Sessão TF\n",
    "with tf.compat.v1.Session() as sess:\n",
    "    print('\\nA soma do node1 com o node2 é: %f' % sess.run(total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "A soma do node1 com o node2 é: 14\n"
     ]
    }
   ],
   "source": [
    "# Criando os nodes no grafo computacional\n",
    "node1 = tf.constant(5, dtype = tf.int32)\n",
    "node2 = tf.constant(9, dtype = tf.int32)\n",
    "node3 = tf.add(node1, node2)\n",
    "\n",
    "# Cria a sessão TF\n",
    "sess = tf.Session()\n",
    " \n",
    "# Executa o grafo\n",
    "print(\"\\nA soma do node1 com o node2 é:\", sess.run(node3))\n",
    " \n",
    "# Fecha a sessão\n",
    "sess.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Subtração"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tensores randômicos\n",
    "rand_a = tf.random_normal([3], 2.0)\n",
    "rand_b = tf.random_uniform([3], 1.0, 4.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"random_normal:0\", shape=(3,), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "print(rand_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"random_uniform:0\", shape=(3,), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "print(rand_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Subtração\n",
    "diff = tf.subtract(rand_a, rand_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tensor rand_a:  [1.3410325 1.4872478 0.800948 ]\n",
      "\n",
      "Tensor rand_b:  [3.8123548 3.3592887 2.5301929]\n",
      "\n",
      "Subtração entre os 2 tensores é:  [ 0.50884175 -1.2474473  -0.8678696 ]\n"
     ]
    }
   ],
   "source": [
    "# Sessão TF\n",
    "with tf.Session() as sess:\n",
    "    print('\\nTensor rand_a: ', sess.run(rand_a))\n",
    "    print('\\nTensor rand_b: ', sess.run(rand_b))\n",
    "    print('\\nSubtração entre os 2 tensores é: ', sess.run(diff))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Divisão"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "node1 = tf.constant(21, dtype=tf.int32)\n",
    "node2 = tf.constant(7, dtype=tf.int32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-29-29650240f182>:1: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Deprecated in favor of operator or tf.math.divide.\n"
     ]
    }
   ],
   "source": [
    "div = tf.div(node1, node2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Divisão entre os 2 tensores é:  3\n"
     ]
    }
   ],
   "source": [
    "# Sessão TF\n",
    "with tf.Session() as sess:\n",
    "    print('\\nDivisão entre os 2 tensores é: ', sess.run(div))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiplicação"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para aprender a teoria sobre operações com matrizes: https://pt.khanacademy.org/math/precalculus/precalc-matrices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para aprender a teoria e prática sobre operações com matrizes: https://www.datascienceacademy.com.br/pages/formacao-inteligencia-artificial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Criando tensores\n",
    "tensor_a = tf.constant([[4., 2.]])\n",
    "tensor_b = tf.constant([[3.],[7.]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const_7:0\", shape=(1, 2), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "print(tensor_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const_8:0\", shape=(2, 1), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "print(tensor_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Multiplicação\n",
    "# tf.multiply(X, Y) executa multiplicação element-wise \n",
    "# https://www.tensorflow.org/api_docs/python/tf/multiply\n",
    "prod = tf.multiply(tensor_a, tensor_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "tensor_a: \n",
      " [[4. 2.]]\n",
      "\n",
      "tensor_b: \n",
      " [[3.]\n",
      " [7.]]\n",
      "\n",
      "Produto Element-wise Entre os Tensores: \n",
      " [[12.  6.]\n",
      " [28. 14.]]\n"
     ]
    }
   ],
   "source": [
    "# Executa a sessão\n",
    "with tf.Session() as sess:\n",
    "    print('\\ntensor_a: \\n', sess.run(tensor_a))\n",
    "    print('\\ntensor_b: \\n', sess.run(tensor_b))\n",
    "    print('\\nProduto Element-wise Entre os Tensores: \\n', sess.run(prod))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Outro exemplo de Multiplicação de Matrizes\n",
    "mat_a = tf.constant([[2, 3], [9, 2], [4, 5]])\n",
    "mat_b = tf.constant([[6, 4, 5], [3, 7, 2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const_9:0\", shape=(3, 2), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(mat_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Const_10:0\", shape=(2, 3), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(mat_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Multiplicação\n",
    "# tf.matmul(X, Y) executa multiplicação entre matrizes \n",
    "# https://www.tensorflow.org/api_docs/python/tf/matmul\n",
    "mat_prod = tf.matmul(mat_a, mat_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tensor mat_a: \n",
      " [[2 3]\n",
      " [9 2]\n",
      " [4 5]]\n",
      "\n",
      "Tensor mat_b: \n",
      " [[6 4 5]\n",
      " [3 7 2]]\n",
      "\n",
      "Produto Element-wise Entre os Tensores (Matrizes): \n",
      " [[21 29 16]\n",
      " [60 50 49]\n",
      " [39 51 30]]\n"
     ]
    }
   ],
   "source": [
    "# Executa a sessão\n",
    "with tf.Session() as sess:\n",
    "    print('\\nTensor mat_a: \\n', sess.run(mat_a))\n",
    "    print('\\nTensor mat_b: \\n', sess.run(mat_b))\n",
    "    print('\\nProduto Element-wise Entre os Tensores (Matrizes): \\n', sess.run(mat_prod))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/matrizes.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usando Variáveis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O TensorFlow também possui nodes variáveis que podem conter dados variáveis. Elas são usados principalmente para manter e atualizar parâmetros de um modelo de treinamento.\n",
    "\n",
    "Variáveis são buffers na memória contendo tensores. Elas devem ser inicializados e podem ser salvas durante e após o treinamento. Você pode restaurar os valores salvos posteriormente para exercitar ou analisar o modelo.\n",
    "\n",
    "Uma diferença importante a notar entre uma constante e uma variável é:\n",
    "\n",
    "O valor de uma constante é armazenado no grafo e seu valor é replicado onde o grafo é carregado. Uma variável é armazenada separadamente e pode estar em um servidor de parâmetros."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tensor Original:\n",
      " [[0. 0.]\n",
      " [0. 0.]]\n",
      "\n",
      "Tensor depois da adição:\n",
      " [[1. 1.]\n",
      " [1. 1.]]\n"
     ]
    }
   ],
   "source": [
    "# Import\n",
    "import tensorflow as tf\n",
    " \n",
    "# Criando um node no grafo computacional\n",
    "node = tf.Variable(tf.zeros([2,2]))\n",
    " \n",
    "# Executando o grafo computacional\n",
    "with tf.Session() as sess:\n",
    " \n",
    "    # Inicializando as variábeis\n",
    "    sess.run(tf.global_variables_initializer())\n",
    " \n",
    "    # Avaliando o node\n",
    "    print(\"\\nTensor Original:\\n\", sess.run(node))\n",
    " \n",
    "    # Adição element-wise no tensor\n",
    "    node = node.assign(node + tf.ones([2,2]))\n",
    " \n",
    "    # Avaliando o node novamente\n",
    "    print(\"\\nTensor depois da adição:\\n\", sess.run(node))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usando Placeholders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Um grafo pode ser parametrizado para aceitar dados externos e podemos reservar áreas conhecidas como espaços reservados (Placeholders). Um espaço reservado é uma promessa para fornecer um valor mais tarde.\n",
    "\n",
    "Ao avaliar o grafo envolvendo nós de espaço reservado, um parâmetro feed_dict é passado para a sessão."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3 6 9]\n",
      " [2 4 6]\n",
      " [1 2 3]]\n"
     ]
    }
   ],
   "source": [
    "# Import\n",
    "import tensorflow as tf\n",
    " \n",
    "# Criando nodes no Grafo Computacional\n",
    "a = tf.placeholder(tf.int32, shape=(3,1))\n",
    "b = tf.placeholder(tf.int32, shape=(1,3))\n",
    "c = tf.matmul(a,b)\n",
    " \n",
    "# Executando o Grafo Computacional\n",
    "with tf.Session() as sess:\n",
    "    print(sess.run(c, feed_dict={a:[[3],[2],[1]], b:[[1,2,3]]}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('imagens/matrizes.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conheça a Formação Inteligência Artificial, um programa completo, 100% online e 100% em português, com 402 horas em 9 cursos de nível intermediário/avançado, que vão ajudá-lo a se tornar um dos profissionais mais cobiçados do mercado de tecnologia. Clique no link abaixo, faça sua inscrição, comece hoje mesmo e aumente sua empregabilidade:\n",
    "\n",
    "https://www.datascienceacademy.com.br/pages/formacao-inteligencia-artificial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Fim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Obrigado - Data Science Academy - <a href=\"http://facebook.com/dsacademybr\">facebook.com/dsacademybr</a>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}