[ot][spam]gpt-4 completions
Undescribed Horrific Abuse, One Victim & Survivor of Many
gmkarl at gmail.com
Sat Oct 14 10:37:02 PDT 2023
{
"model": "gpt-4",
"messages": [
{
"role": "system",
"content": "Do dialog like codegolf, with the fewest characters possible."
},
{
"role": "user",
"content": "Construct, train, and save, a torch.nn.Transformer .
Generate data so it increments floats."
},
{
"role": "assistant",
"content": "```python\nimport torch\nfrom torch import
nn\nimport numpy as np\n\n# Construct\nm=nn.Transformer()\n\n#
Generate data\nx=np.arange(0,1,0.01)\ny=x+1\n\n#
Train\no=torch.optim.Adam(m.parameters())\nl=nn.MSELoss()\nfor _ in
range(100):\n p=m(torch.tensor(x).unsqueeze(0))\n o.zero_grad()\n
e=l(p,torch.tensor(y).unsqueeze(0))\n e.backward()\n o.step()\n\n#
Save\ntorch.save(m.state_dict(),'m.pt')\n```"
},
{
"role": "user",
"content": "fix this: Transformer.forward() takes two
parameters, src and tgt.\nAlso, load a previous version of the model
on bootup if it's been saved, version the saved models with their
training data, and give progress output to the user."
},
{
"role": "assistant",
"content": "```python\nimport torch\nfrom torch import
nn\nimport numpy as np\nimport os\n\n#
Construct\nm=nn.Transformer()\n\n# Load previous model if exists\nif
os.path.exists('m.pt'):\n m.load_state_dict(torch.load('m.pt'))\n\n#
Generate data\nx=np.arange(0,1,0.01)\ny=x+1\n\n# Versioning\nv =
str(len(os.listdir())) # number of files in
directory\ntorch.save((x,y), f'data_{v}.pt')\n\n#
Train\no=torch.optim.Adam(m.parameters())\nl=nn.MSELoss()\nfor i in
range(100):\n src = torch.tensor(x).unsqueeze(0)\n tgt =
torch.tensor(y).unsqueeze(0)\n p=m(src, tgt)\n o.zero_grad()\n
e=l(p,tgt)\n e.backward()\n o.step()\n if i%10==0: print(f'Epoch
{i}, Loss {e.item()}')\n\n#
Save\ntorch.save(m.state_dict(),f'm_{v}.pt')\n```"
}
],
"temperature": 0,
"max_tokens": 256,
"top_p": 1,
"frequency_penalty": 0,
"presence_penalty": 0
}
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