{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import torch\n",
    "\n",
    "# complex valued tensor class\n",
    "from cplxmodule import cplx\n",
    "\n",
    "# converters\n",
    "from cplxmodule.nn import RealToCplx, CplxToReal, CplxToCplx\n",
    "\n",
    "# layers of encapsulating other complex valued layers\n",
    "from cplxmodule.nn import CplxSequential\n",
    "\n",
    "# common layers\n",
    "from cplxmodule.nn import CplxConv1d, CplxLinear\n",
    "\n",
    "# activation layers\n",
    "from cplxmodule.nn import CplxModReLU"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "n_features, n_channels = 16, 4\n",
    "z = torch.randn(256, n_channels, n_features * 2)\n",
    "\n",
    "complex_model = CplxSequential(\n",
    "    CplxLinear(n_features, n_features, bias=True),\n",
    "\n",
    "    # complex: batch x n_channels x n_features\n",
    "    CplxConv1d(n_channels, 3 * n_channels, kernel_size=4, stride=1, bias=False),\n",
    "\n",
    "    # complex: batch x (3 * n_channels) x (n_features - (4-1))\n",
    "    CplxModReLU(threshold=0.15),\n",
    "\n",
    "    # complex: batch x (3 * n_channels) x (n_features - (4-1))\n",
    "    CplxToCplx[torch.nn.Flatten](start_dim=-2),\n",
    "\n",
    "    CplxToCplx[torch.tanh](),\n",
    ")"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/nn/modules/container.py:587: UserWarning: Setting attributes on ParameterDict is not supported.\n",
      "  warnings.warn(\"Setting attributes on ParameterDict is not supported.\")\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "real_input_model = torch.nn.Sequential(\n",
    "    # real: batch x (n_features * 2)\n",
    "    torch.nn.Linear(n_features * 2, n_features * 2),\n",
    "\n",
    "    # real: batch x (n_features * 2)\n",
    "    RealToCplx(),\n",
    "\n",
    "    # complex: batch x n_features\n",
    "    complex_model,\n",
    "\n",
    "    # complex: batch x (3 * n_channels * (n_features - (4-1)))\n",
    "    CplxToReal(),\n",
    "\n",
    "    # real: batch x ((3 * n_channels * (n_features - (4-1))) * 2)\n",
    ")"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "traced_module = torch.jit.trace(real_input_model, z)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.\n",
      "To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at  /pytorch/aten/src/ATen/native/BinaryOps.cpp:467.)\n",
      "  return torch.floor_divide(self, other)\n",
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/utils/views.py:41: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\n",
      "  if rem != 0:\n",
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/utils/views.py:46: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\n",
      "  if shape[dim] == 2 and squeeze:\n",
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py:47: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\n",
      "  if real.shape != imag.shape:\n",
      "/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py:633: TracerWarning: Converting a tensor to a Python integer might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\n",
      "  n_out = int(weight.shape[0])\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "script_module = torch.jit.script(complex_model)"
   ],
   "outputs": [
    {
     "output_type": "error",
     "ename": "AssertionError",
     "evalue": "Expected Module but got <class 'cplxmodule.cplx.Cplx'>",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-8b6357d9d133>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscript\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomplex_model\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36mscript\u001b[0;34m(obj, optimize, _frames_up, _rcb)\u001b[0m\n\u001b[1;32m   1094\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mModule\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1095\u001b[0m         \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcall_prepare_scriptable_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1096\u001b[0;31m         return torch.jit._recursive.create_script_module(\n\u001b[0m\u001b[1;32m   1097\u001b[0m             \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_recursive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfer_methods_to_compile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1098\u001b[0m         )\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module\u001b[0;34m(nn_module, stubs_fn, share_types)\u001b[0m\n\u001b[1;32m    410\u001b[0m     \u001b[0mconcrete_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_module_concrete_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshare_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    411\u001b[0m     \u001b[0mAttributeTypeIsSupportedChecker\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 412\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    413\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    414\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module_impl\u001b[0;34m(nn_module, concrete_type, stubs_fn)\u001b[0m\n\u001b[1;32m    472\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    473\u001b[0m     \u001b[0;31m# Actually create the ScriptModule, initializing it with the function we just defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m     \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minit_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    475\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    476\u001b[0m     \u001b[0;31m# Compile methods if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36m_construct\u001b[0;34m(cpp_module, init_fn)\u001b[0m\n\u001b[1;32m    495\u001b[0m             \"\"\"\n\u001b[1;32m    496\u001b[0m             \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 497\u001b[0;31m             \u001b[0minit_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    498\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    499\u001b[0m             \u001b[0;31m# Finalize the ScriptModule: replace the nn.Module state with our\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36minit_fn\u001b[0;34m(script_module)\u001b[0m\n\u001b[1;32m    450\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    451\u001b[0m                 \u001b[0;31m# always reuse the provided stubs_fn to infer the methods to compile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 452\u001b[0;31m                 \u001b[0mscripted\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msub_concrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    453\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    454\u001b[0m             \u001b[0mcpp_module\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscripted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module_impl\u001b[0;34m(nn_module, concrete_type, stubs_fn)\u001b[0m\n\u001b[1;32m    472\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    473\u001b[0m     \u001b[0;31m# Actually create the ScriptModule, initializing it with the function we just defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m     \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minit_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    475\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    476\u001b[0m     \u001b[0;31m# Compile methods if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36m_construct\u001b[0;34m(cpp_module, init_fn)\u001b[0m\n\u001b[1;32m    495\u001b[0m             \"\"\"\n\u001b[1;32m    496\u001b[0m             \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 497\u001b[0;31m             \u001b[0minit_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    498\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    499\u001b[0m             \u001b[0;31m# Finalize the ScriptModule: replace the nn.Module state with our\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36minit_fn\u001b[0;34m(script_module)\u001b[0m\n\u001b[1;32m    441\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msub_concrete_type\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconcrete_type\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_modules\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    442\u001b[0m             \u001b[0morig_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 443\u001b[0;31m             \u001b[0;32massert\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mModule\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Expected Module but got {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    444\u001b[0m             \u001b[0mmodule_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msub_concrete_type\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit_type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    445\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodule_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mInterfaceType\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAssertionError\u001b[0m: Expected Module but got <class 'cplxmodule.cplx.Cplx'>"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "script_module = torch.jit.script(real_input_model)"
   ],
   "outputs": [
    {
     "output_type": "error",
     "ename": "NotSupportedError",
     "evalue": "Compiled functions can't take variable number of arguments or use keyword-only arguments with defaults:\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py\", line 195\n    def apply(self, f, *a, **k):\n                            ~~ <--- HERE\n        r\"\"\"Applies the function to real and imaginary parts.\"\"\"\n        return type(self)(f(self.__real, *a, **k), f(self.__imag, *a, **k))\n'__torch__.cplxmodule.cplx.Cplx' is being compiled since it was called from 'from_interleaved_real'\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py\", line 414\ndef from_interleaved_real(input, copy=True, dim=-1):\n    \"\"\"Map real tensor input `... x [D * 2]` to a pair (re, im) with dim `... x D`.\"\"\"\n    output = Cplx(*complex_view(input, dim, squeeze=False))\n    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n    return output.clone() if copy else output\n'from_interleaved_real' is being compiled since it was called from 'InterleavedRealToCplx.forward'\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/nn/modules/casting.py\", line 28\n    def forward(self, input):\n        return cplx.from_interleaved_real(input, self.copy, self.dim)\n               ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNotSupportedError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-3ce02b220edf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscript\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreal_input_model\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36mscript\u001b[0;34m(obj, optimize, _frames_up, _rcb)\u001b[0m\n\u001b[1;32m   1094\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mModule\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1095\u001b[0m         \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcall_prepare_scriptable_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1096\u001b[0;31m         return torch.jit._recursive.create_script_module(\n\u001b[0m\u001b[1;32m   1097\u001b[0m             \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_recursive\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfer_methods_to_compile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1098\u001b[0m         )\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module\u001b[0;34m(nn_module, stubs_fn, share_types)\u001b[0m\n\u001b[1;32m    410\u001b[0m     \u001b[0mconcrete_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_module_concrete_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshare_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    411\u001b[0m     \u001b[0mAttributeTypeIsSupportedChecker\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 412\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    413\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    414\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnn_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module_impl\u001b[0;34m(nn_module, concrete_type, stubs_fn)\u001b[0m\n\u001b[1;32m    472\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    473\u001b[0m     \u001b[0;31m# Actually create the ScriptModule, initializing it with the function we just defined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m     \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_construct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minit_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    475\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    476\u001b[0m     \u001b[0;31m# Compile methods if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36m_construct\u001b[0;34m(cpp_module, init_fn)\u001b[0m\n\u001b[1;32m    495\u001b[0m             \"\"\"\n\u001b[1;32m    496\u001b[0m             \u001b[0mscript_module\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRecursiveScriptModule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 497\u001b[0;31m             \u001b[0minit_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    498\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    499\u001b[0m             \u001b[0;31m# Finalize the ScriptModule: replace the nn.Module state with our\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36minit_fn\u001b[0;34m(script_module)\u001b[0m\n\u001b[1;32m    450\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    451\u001b[0m                 \u001b[0;31m# always reuse the provided stubs_fn to infer the methods to compile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 452\u001b[0;31m                 \u001b[0mscripted\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_script_module_impl\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msub_concrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstubs_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    453\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    454\u001b[0m             \u001b[0mcpp_module\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscripted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_script_module_impl\u001b[0;34m(nn_module, concrete_type, stubs_fn)\u001b[0m\n\u001b[1;32m    476\u001b[0m     \u001b[0;31m# Compile methods if necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    477\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mconcrete_type\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mconcrete_type_store\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmethods_compiled\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m         \u001b[0mcreate_methods_and_properties_from_stubs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod_stubs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproperty_stubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    479\u001b[0m         \u001b[0;31m# Create hooks after methods to ensure no name collisions between hooks and methods.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    480\u001b[0m         \u001b[0;31m# If done before, hooks can overshadow methods that aren't exported.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mcreate_methods_and_properties_from_stubs\u001b[0;34m(concrete_type, method_stubs, property_stubs)\u001b[0m\n\u001b[1;32m    353\u001b[0m     \u001b[0mproperty_rcbs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresolution_callback\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mproperty_stubs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    354\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 355\u001b[0;31m     \u001b[0mconcrete_type\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_create_methods_and_properties\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mproperty_defs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproperty_rcbs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod_defs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod_rcbs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod_defaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    357\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcreate_hooks_from_stubs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconcrete_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhook_stubs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpre_hook_stubs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_recursive.py\u001b[0m in \u001b[0;36mtry_compile_fn\u001b[0;34m(fn, loc)\u001b[0m\n\u001b[1;32m    793\u001b[0m     \u001b[0;31m# object\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    794\u001b[0m     \u001b[0mrcb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_jit_internal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreateResolutionCallbackFromClosure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 795\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscript\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_rcb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    796\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    797\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrap_cpp_module\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcpp_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36mscript\u001b[0;34m(obj, optimize, _frames_up, _rcb)\u001b[0m\n\u001b[1;32m   1141\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0m_rcb\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1142\u001b[0m             \u001b[0m_rcb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_jit_internal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreateResolutionCallbackFromClosure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1143\u001b[0;31m         fn = torch._C._jit_script_compile(\n\u001b[0m\u001b[1;32m   1144\u001b[0m             \u001b[0mqualified_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mast\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_rcb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mget_default_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1145\u001b[0m         )\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/annotations.py\u001b[0m in \u001b[0;36mtry_ann_to_type\u001b[0;34m(ann, loc)\u001b[0m\n\u001b[1;32m    362\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mmaybe_script_class\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    363\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jit_internal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcan_compile_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mann\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 364\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_script\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_recursive_compile_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mann\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    365\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    366\u001b[0m     \u001b[0;31m# Maybe resolve a NamedTuple to a Tuple Type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36m_recursive_compile_class\u001b[0;34m(obj, loc)\u001b[0m\n\u001b[1;32m   1258\u001b[0m     \u001b[0merror_stack\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCallStack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_qual_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1259\u001b[0m     \u001b[0mrcb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_jit_internal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreateResolutionCallbackForClassMethods\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1260\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_compile_and_register_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrcb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_qual_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1261\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1262\u001b[0m \u001b[0mCompilationUnit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCompilationUnit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/_script.py\u001b[0m in \u001b[0;36m_compile_and_register_class\u001b[0;34m(obj, rcb, qualified_name)\u001b[0m\n\u001b[1;32m    134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    135\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_compile_and_register_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrcb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mqualified_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 136\u001b[0;31m     \u001b[0mast\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_jit_class_def\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    137\u001b[0m     \u001b[0mdefaults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrontend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_default_args_for_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    138\u001b[0m     \u001b[0mscript_class\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jit_script_class_compile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mqualified_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mast\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdefaults\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/frontend.py\u001b[0m in \u001b[0;36mget_jit_class_def\u001b[0;34m(cls, self_name)\u001b[0m\n\u001b[1;32m    196\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mismethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"__self__\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    197\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 198\u001b[0;31m     methods = [get_jit_def(obj,\n\u001b[0m\u001b[1;32m    199\u001b[0m                            \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    200\u001b[0m                            \u001b[0mself_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/frontend.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    196\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mismethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"__self__\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    197\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 198\u001b[0;31m     methods = [get_jit_def(obj,\n\u001b[0m\u001b[1;32m    199\u001b[0m                            \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    200\u001b[0m                            \u001b[0mself_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/frontend.py\u001b[0m in \u001b[0;36mget_jit_def\u001b[0;34m(fn, def_name, self_name, is_classmethod)\u001b[0m\n\u001b[1;32m    306\u001b[0m         \u001b[0mpdt_arg_types\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtype_trace_db\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_args_types\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mqualname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    307\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 308\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mbuild_def\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfn_def\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype_line\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdef_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpdt_arg_types\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpdt_arg_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    309\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m \u001b[0;31m# TODO: more robust handling of recognizing ignore context manager\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/frontend.py\u001b[0m in \u001b[0;36mbuild_def\u001b[0;34m(ctx, py_def, type_line, def_name, self_name, pdt_arg_types)\u001b[0m\n\u001b[1;32m    344\u001b[0m                        py_def.col_offset + len(\"def\"))\n\u001b[1;32m    345\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 346\u001b[0;31m     \u001b[0mparam_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuild_param_list\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpy_def\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpdt_arg_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    347\u001b[0m     \u001b[0mreturn_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    348\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpy_def\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'returns'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/torch/jit/frontend.py\u001b[0m in \u001b[0;36mbuild_param_list\u001b[0;34m(ctx, py_args, self_name, pdt_arg_types)\u001b[0m\n\u001b[1;32m    368\u001b[0m         \u001b[0mexpr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpy_args\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkwarg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    369\u001b[0m         \u001b[0mctx_range\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_range\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlineno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcol_offset\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcol_offset\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 370\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mNotSupportedError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mctx_range\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_vararg_kwarg_err\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    371\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mpy_args\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvararg\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    372\u001b[0m         \u001b[0mexpr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpy_args\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvararg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNotSupportedError\u001b[0m: Compiled functions can't take variable number of arguments or use keyword-only arguments with defaults:\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py\", line 195\n    def apply(self, f, *a, **k):\n                            ~~ <--- HERE\n        r\"\"\"Applies the function to real and imaginary parts.\"\"\"\n        return type(self)(f(self.__real, *a, **k), f(self.__imag, *a, **k))\n'__torch__.cplxmodule.cplx.Cplx' is being compiled since it was called from 'from_interleaved_real'\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/cplx.py\", line 414\ndef from_interleaved_real(input, copy=True, dim=-1):\n    \"\"\"Map real tensor input `... x [D * 2]` to a pair (re, im) with dim `... x D`.\"\"\"\n    output = Cplx(*complex_view(input, dim, squeeze=False))\n    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n    return output.clone() if copy else output\n'from_interleaved_real' is being compiled since it was called from 'InterleavedRealToCplx.forward'\n  File \"/home/shogg/.pyenv/versions/3.8.0/envs/mrii/lib/python3.8/site-packages/cplxmodule/nn/modules/casting.py\", line 28\n    def forward(self, input):\n        return cplx.from_interleaved_real(input, self.copy, self.dim)\n               ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
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