{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "pythos parser bug.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mi0XmIW7387j",
        "colab_type": "text"
      },
      "source": [
        "Traceback (most recent call last):\n",
        "  File \"untitled.py\", line 4, in <module>\n",
        "    ,torch.ones(10,6*5*6)))\n",
        "  File \"/usr/local/lib/python3.6/dist-packages/torch/nn/modules/linear.py\", line 72, in __init__\n",
        "    self.weight = Parameter(torch.Tensor(out_features, in_features))\n",
        "TypeError: new() received an invalid combination of arguments - got (Tensor, Tensor), but expected one of:\n",
        " * (*, torch.device device)\n",
        "      didn't match because some of the arguments have invalid types: (Tensor, Tensor)\n",
        " * (torch.Storage storage)\n",
        " * (Tensor other)\n",
        " * (tuple of ints size, *, torch.device device)\n",
        " * (object data, *, torch.device device)\n",
        "\n",
        "---------------------------------------------------------------------------\n",
        "TypeError                                 Traceback (most recent call last)\n",
        "<ipython-input-45-c6a1d2a47653> in <module>()\n",
        "      3 print(torch.nn.Linear(\n",
        "      4 torch.as_strided(torch.ones((4,6*5*5*70*10)),(4,6*5*5,10),(4,2,-1))\n",
        "----> 5 ,torch.ones(10,6*5*6)))\n",
        "      6 #(4,2,3),(2,3,1))\n",
        "\n",
        "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/linear.py in __init__(self, in_features, out_features, bias)\n",
        "     70         self.in_features = in_features\n",
        "     71         self.out_features = out_features\n",
        "---> 72         self.weight = Parameter(torch.Tensor(out_features, in_features))\n",
        "     73         if bias:\n",
        "     74             self.bias = Parameter(torch.Tensor(out_features))\n",
        "\n",
        "TypeError: new() received an invalid combination of arguments - got (Tensor, Tensor), but expected one of:\n",
        " * (*, torch.device device)\n",
        "      didn't match because some of the arguments have invalid types: (!Tensor!, !Tensor!)\n",
        " * (torch.Storage storage)\n",
        " * (Tensor other)\n",
        " * (tuple of ints size, *, torch.device device)\n",
        " * (object data, *, torch.device device)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g2YWcUi933Ej",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "#torch.nn.Linear(\n",
        "torch.as_strided(torch.ones((4,6*5*5*70*10)),(4,6*5*5,10),(4,2,-1))\n",
        ",torch.ones(10,6*5*6)#)\n",
        "#(4,2,3),(2,3,1))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EIGhdU6q4G5x",
        "colab_type": "text"
      },
      "source": [
        "---------------------------------------------------------------------------\n",
        "TypeError                                 Traceback (most recent call last)\n",
        "<ipython-input-50-8b8f68dfdd40> in <module>()\n",
        "      2 #torch.nn.Linear(\n",
        "      3 torch.as_strided(torch.ones((4,6*5*5*70*10)),(4,6*5*5,10),(4,2,-1))\n",
        "----> 4 torch.ones(\"(10,6*5*6)\")\n",
        "      5 #(4,2,3),(2,3,1))\n",
        "\n",
        "TypeError: ones(): argument 'size' (position 1) must be tuple of ints, not str\n",
        "import torch\n",
        "#torch.nn.Linear(\n",
        "torch.as_strided(torch.ones((4,6*5*5*70*10)),(4,6*5*5,10),(4,2,-1))\n",
        ",torch.ones(10,6*5*6)#)\n",
        "#(4,2,3),(2,3,1))"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dhDLviK-4HZC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "#torch.nn.Linear(\n",
        "torch.as_strided(torch.ones((4,6*5*5*70*10)),(4,6*5*5,10),(4,2,-1))\n",
        ",torch.ones(10,6*5*6)#)\n",
        "#(4,2,3),(2,3,1))"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}