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@sekstini
Created November 1, 2023 20:46
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Testing MiniFormer memory consumption with and without torch.compile
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "e1c1ad1f-585e-4cea-becc-3ae1220bdc02",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"from einops import rearrange\n",
"from torch.profiler import profile, ProfilerActivity\n",
"\n",
"torch.set_float32_matmul_precision(\"high\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3398b9e4-8347-45d7-a0e3-f139bf5089a2",
"metadata": {},
"outputs": [],
"source": [
"class TriangleMultiplicative(nn.Module):\n",
" def __init__(\n",
" self,\n",
" *,\n",
" dim: int,\n",
" hidden_dim: int | None = None,\n",
" mix: str = \"ingoing\"\n",
" ):\n",
" super().__init__()\n",
" assert mix in {\"ingoing\", \"outgoing\"}, \"mix must be either ingoing or outgoing\"\n",
"\n",
" hidden_dim = hidden_dim or dim\n",
" self.norm = nn.LayerNorm(dim)\n",
"\n",
" self.left_proj = nn.Linear(dim, hidden_dim)\n",
" self.right_proj = nn.Linear(dim, hidden_dim)\n",
"\n",
" self.left_gate = nn.Linear(dim, hidden_dim)\n",
" self.right_gate = nn.Linear(dim, hidden_dim)\n",
" self.out_gate = nn.Linear(dim, hidden_dim)\n",
"\n",
" # initialize all gating to be identity\n",
"\n",
" for gate in (self.left_gate, self.right_gate, self.out_gate):\n",
" nn.init.constant_(gate.weight, 0.)\n",
" nn.init.constant_(gate.bias, 1.)\n",
"\n",
" if mix == \"outgoing\":\n",
" self.mix_einsum_eq = \"... i k d, ... j k d -> ... i j d\"\n",
" elif mix == \"ingoing\":\n",
" self.mix_einsum_eq = \"... k j d, ... k i d -> ... i j d\"\n",
"\n",
" self.to_out_norm = nn.LayerNorm(hidden_dim)\n",
" self.to_out = nn.Linear(hidden_dim, dim)\n",
"\n",
" def forward(self, x: torch.Tensor, mask: torch.Tensor | None = None):\n",
" assert x.shape[1] == x.shape[2], \"feature map must be symmetrical\"\n",
" if mask is not None:\n",
" mask = rearrange(mask, \"b i j -> b i j ()\")\n",
"\n",
" x = self.norm(x)\n",
"\n",
" left = self.left_proj(x)\n",
" right = self.right_proj(x)\n",
"\n",
" if mask is not None:\n",
" left = left * mask\n",
" right = right * mask\n",
"\n",
" left_gate = self.left_gate(x).sigmoid()\n",
" right_gate = self.right_gate(x).sigmoid()\n",
" out_gate = self.out_gate(x).sigmoid()\n",
"\n",
" left = left * left_gate\n",
" right = right * right_gate\n",
"\n",
" out = torch.einsum(self.mix_einsum_eq, left, right)\n",
"\n",
" out = self.to_out_norm(out)\n",
" out = out * out_gate\n",
" return self.to_out(out)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6e34a44e-834c-45e2-b698-9fdf92ce794c",
"metadata": {},
"outputs": [],
"source": [
"class MLP(nn.Module):\n",
" def __init__(self, dim: int, intermediate_dim: int):\n",
" super().__init__()\n",
" self.proj_in = nn.Linear(dim, intermediate_dim)\n",
" self.proj_out = nn.Linear(intermediate_dim, dim)\n",
"\n",
" def forward(self, x: torch.Tensor):\n",
" return self.proj_out(F.relu(self.proj_in(x)))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "dd7d0ead-f114-4a84-a7a0-d5717cf0c3b8",
"metadata": {},
"outputs": [],
"source": [
"class MiniFormerBlock(nn.Module):\n",
" def __init__(self, dim: int):\n",
" super().__init__()\n",
" self.tri_up_out = TriangleMultiplicative(dim=dim, mix=\"outgoing\")\n",
" self.tri_up_in = TriangleMultiplicative(dim=dim, mix=\"ingoing\")\n",
" self.transition = MLP(dim=dim, intermediate_dim=4*dim)\n",
"\n",
" def forward(self, x: torch.Tensor):\n",
" x = x + self.tri_up_out(x)\n",
" x = x + self.tri_up_in(x)\n",
" x = x + self.transition(x)\n",
" return x\n",
"\n",
"class MiniFormer(nn.Sequential):\n",
" def __init__(self, n_layer: int, dim: int):\n",
" super().__init__(*(MiniFormerBlock(dim) for _ in range(n_layer)))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "20dcb69f-2be0-4ff7-9b5b-d2e4d97557c9",
"metadata": {},
"outputs": [],
"source": [
"def param_count(m: nn.Module) -> int:\n",
" return sum(math.prod(x.shape) for x in m.parameters())"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "149d1ebc-4920-41aa-9bd2-257544bb94cf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3.3088, 'M params')"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"device, dtype = \"cuda\", torch.float16\n",
"\n",
"with torch.device(device):\n",
" miniformer = MiniFormer(n_layer=10, dim=128).to(dtype)\n",
" \n",
"param_count(miniformer) / 1e6, \"M params\""
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "29b0993f-93a8-4e2c-b138-aec8c8c976f0",
"metadata": {},
"outputs": [],
"source": [
"x = torch.randn(1, 256, 256, 128, device=device, dtype=dtype)"
]
},
{
"cell_type": "markdown",
"id": "937b8433-a3a1-4a4d-95ba-6a884ed2af03",
"metadata": {},
"source": [
"### Without compile"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "2a0de342-20c7-4345-8d3b-8047363af9bc",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"STAGE:2023-11-01 21:43:01 314436:314436 ActivityProfilerController.cpp:312] Completed Stage: Warm Up\n",
"STAGE:2023-11-01 21:43:01 314436:314436 ActivityProfilerController.cpp:318] Completed Stage: Collection\n",
"STAGE:2023-11-01 21:43:01 314436:314436 ActivityProfilerController.cpp:322] Completed Stage: Post Processing\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 1600x960 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# warmup\n",
"for _ in range(3):\n",
" y = miniformer(x).sum()\n",
" y.backward()\n",
" del y\n",
"\n",
"torch.cuda.empty_cache()\n",
"torch.cuda.synchronize()\n",
"\n",
"profiler_args = dict(activities=[ProfilerActivity.CPU], profile_memory=True, record_shapes=True, with_stack=True)\n",
"\n",
"with profile(**profiler_args) as prof:\n",
" z = miniformer(x).sum()\n",
" z.backward()\n",
" del z\n",
"\n",
"prof.export_memory_timeline(\"mem_with-grads.html\", device=\"cuda:0\")"
]
},
{
"cell_type": "markdown",
"id": "580eb63d-48f1-4f8f-8a92-38b0a64be8f0",
"metadata": {},
"source": [
"### With compile"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "198be6da-2b9c-41fd-80bf-d2810779d69f",
"metadata": {},
"outputs": [],
"source": [
"miniformer.compile(mode=\"reduce-overhead\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "59c8056b-8c72-4fc8-8c68-143e4e7071af",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"STAGE:2023-11-01 21:43:35 314436:314436 ActivityProfilerController.cpp:312] Completed Stage: Warm Up\n",
"STAGE:2023-11-01 21:43:35 314436:314436 ActivityProfilerController.cpp:318] Completed Stage: Collection\n",
"STAGE:2023-11-01 21:43:35 314436:314436 ActivityProfilerController.cpp:322] Completed Stage: Post Processing\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1600x960 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# warmup\n",
"for _ in range(3):\n",
" y = miniformer(x).sum()\n",
" y.backward()\n",
" del y\n",
"\n",
"torch.cuda.empty_cache()\n",
"torch.cuda.synchronize()\n",
"\n",
"profiler_args = dict(activities=[ProfilerActivity.CPU], profile_memory=True, record_shapes=True, with_stack=True)\n",
"\n",
"with profile(**profiler_args) as prof:\n",
" z = miniformer(x).sum()\n",
" z.backward()\n",
" del z\n",
"\n",
"prof.export_memory_timeline(\"mem_with-grads_compile.html\", device=\"cuda:0\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.10.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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