109 lines
4.9 KiB
Python
109 lines
4.9 KiB
Python
import time
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import json
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from eacgm.bpf import BccBPF
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from eacgm.sampler import eBPFSampler
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from eacgm.collector import to_perfetto
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func_sym = {
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"TorchAdd": "_ZN5torch8autogradL15THPVariable_addEP7_objectS2_S2_",
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"TorchSub": "_ZN5torch8autogradL15THPVariable_subEP7_objectS2_S2_",
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"TorchMul": "_ZN5torch8autogradL15THPVariable_mulEP7_objectS2_S2_",
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"TorchMatmul": "_ZN5torch8autogradL18THPVariable_matmulEP7_objectS2_S2_",
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"TorchDiv": "_ZN5torch8autogradL15THPVariable_divEP7_objectS2_S2_",
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"TorchLinear": "_ZN5torch8autogradL18THPVariable_linearEP7_objectS2_S2_",
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"TorchConv2d": "_ZN5torch8autogradL18THPVariable_conv2dEP7_objectS2_S2_",
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"TorchReLU": "_ZN5torch8autogradL16THPVariable_reluEP7_objectS2_S2_",
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"TorchSigmoid": "_ZN5torch8autogradL19THPVariable_sigmoidEP7_objectS2_S2_",
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"TorchTanh": "_ZN5torch8autogradL16THPVariable_tanhEP7_objectS2_S2_",
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"TorchSoftmax": "_ZN5torch8autogradL19THPVariable_softmaxEP7_objectS2_S2_",
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"TorchMSELoss": "_ZN5torch8autogradL20THPVariable_mse_lossEP7_objectS2_S2_",
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"TorchBCELoss": "_ZN5torch8autogradL32THPVariable_binary_cross_entropyEP7_objectS2_S2_",
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"TorchCrossEntropyLoss": "_ZN5torch8autogradL30THPVariable_cross_entropy_lossEP7_objectS2_S2_",
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"TorchConvTranspose2d": "_ZN5torch8autogradL28THPVariable_conv_transpose2dEP7_objectS2_S2_",
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"TorchMaxUnpool2d": "_ZN5torch8autogradL24THPVariable_max_unpool2dEP7_objectS2_S2_",
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"TorchBatchNorm2d": "_ZN5torch8autogradL22THPVariable_batch_normEP7_objectS2_S2_",
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"TorchAvgPool2d": "_ZN5torch8autogradL22THPVariable_avg_pool2dEP7_objectS2_S2_",
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"TorchMaxPool2d": "_ZN5torch8autogradL22THPVariable_max_pool2dEP7_objectS2_S2_",
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"TorchDropout": "_ZN5torch8autogradL19THPVariable_dropoutEP7_objectS2_S2_",
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"TorchEmbedding": "_ZN5torch8autogradL21THPVariable_embeddingEP7_objectS2_S2_",
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"TorchLSTM": "_ZN5torch8autogradL16THPVariable_lstmEP7_objectS2_S2_",
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"TorchAdaptiveMaxPool2d": "_ZN5torch8autogradL31THPVariable_adaptive_max_pool2dEP7_objectS2_S2_",
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"TorchAdaptiveAvgPool2d": "_ZN5torch8autogradL31THPVariable_adaptive_avg_pool2dEP7_objectS2_S2_",
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}
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template = """
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int <TorchSym>Entry(struct pt_regs *ctx){
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u64 ts = bpf_ktime_get_ns();
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bpf_trace_printk("%ld@start@<TorchFunc>\\n", ts);
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return 0;
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};
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int <TorchSym>Exit(struct pt_regs *ctx){
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u64 ts = bpf_ktime_get_ns();
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bpf_trace_printk("%ld@end@<TorchFunc>\\n", ts);
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return 0;
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};
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"""
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text = ""
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for func in func_sym:
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sym = func_sym[func]
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text += template.replace("<TorchSym>", sym).replace("<TorchFunc>", func)
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bpf = BccBPF("TorcheBPF", text, ["-w"])
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attach_config = [
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{
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"name": "TorchSampler",
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"exe_path": [
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"/home/txx/data/miniconda3/envs/eACGM/lib/python3.12/site-packages/torch/./lib/libtorch_python.so",
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],
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"exe_sym": [
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"_ZN5torch8autogradL15THPVariable_addEP7_objectS2_S2_",
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"_ZN5torch8autogradL15THPVariable_subEP7_objectS2_S2_",
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"_ZN5torch8autogradL15THPVariable_mulEP7_objectS2_S2_",
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"_ZN5torch8autogradL18THPVariable_matmulEP7_objectS2_S2_",
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"_ZN5torch8autogradL15THPVariable_divEP7_objectS2_S2_",
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"_ZN5torch8autogradL18THPVariable_linearEP7_objectS2_S2_",
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"_ZN5torch8autogradL18THPVariable_conv2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL16THPVariable_reluEP7_objectS2_S2_",
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"_ZN5torch8autogradL19THPVariable_sigmoidEP7_objectS2_S2_",
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"_ZN5torch8autogradL16THPVariable_tanhEP7_objectS2_S2_",
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"_ZN5torch8autogradL19THPVariable_softmaxEP7_objectS2_S2_",
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"_ZN5torch8autogradL20THPVariable_mse_lossEP7_objectS2_S2_",
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"_ZN5torch8autogradL32THPVariable_binary_cross_entropyEP7_objectS2_S2_",
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"_ZN5torch8autogradL30THPVariable_cross_entropy_lossEP7_objectS2_S2_",
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"_ZN5torch8autogradL28THPVariable_conv_transpose2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL24THPVariable_max_unpool2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL22THPVariable_batch_normEP7_objectS2_S2_",
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"_ZN5torch8autogradL22THPVariable_avg_pool2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL22THPVariable_max_pool2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL19THPVariable_dropoutEP7_objectS2_S2_",
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"_ZN5torch8autogradL21THPVariable_embeddingEP7_objectS2_S2_",
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"_ZN5torch8autogradL16THPVariable_lstmEP7_objectS2_S2_",
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"_ZN5torch8autogradL31THPVariable_adaptive_max_pool2dEP7_objectS2_S2_",
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"_ZN5torch8autogradL31THPVariable_adaptive_avg_pool2dEP7_objectS2_S2_",
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]
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},
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]
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sampler = eBPFSampler(bpf)
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sampler.run(attach_config)
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states = []
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while True:
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try:
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samples = sampler.sample(time_stamp=1)
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states += samples
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# for sample in samples:
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# print(sample)
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# print("---")
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except KeyboardInterrupt:
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break
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sampler.close()
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collector = to_perfetto(states)
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json.dump(collector, open("torch.json", "w", encoding="utf-8"), indent=4) |